Remote Sensing and Image Analysis in Plant Pathology 810-660nm

   5 55 rg  5      rg 

REMOTE SENSG  AGE ANALYSIS IN PLANT PAHOY g . r y o . l s n w o e e i v s u e l r l a a u n o n r s n e a . p w r o w F w . 4 m 1 o / r 7 f 2 / d 1 e 0 d a n o o l n a n w a o r a D P . 8 o 2 D 5 - l a 9 r 8 e 4 : d 3 e 3 . F 5 a c 9 i 9 g 1 l o . l o o n h c t e a T p o e t y d a h d P i s . r v e e v i R . n u U n y n b A

Hans-Eric Nilsson mto for Phyopate, pnt of Plant Patlogy Swish Univsity of Agicultual Sciences PO Box 7 7 S77 Uppsla Swen KY S

phytohty, visu ssn n pogy, omty, vgphy, IRthphy IRthphy R,   uoc

S

Tis paper views vrious applications of mo sensing and image analysis in plant patology It describes tecnical mets and tei possibities but also empasizs  biolocal pruisits and sictions of praccal appli caons Te subjec r copr y nonduce nd non tods to dett nd assess plant diseases nd sess objvely and costffvely, even toug to date we cannot idenfy te specic cause of te dmag As a supplement to conventional metods, tese new eo ve grt potential to facilitate d incrse incrse accuracy accuracy nd prisio prisionn in i n plant pto logica resear researc c ODUCON

Remote sensing and diial iae aalysis a metods of acquisition and interpretation of mesuments of an object witout pysic contact tween  urng device and te objt e objct can  analyz may m nonaivey nd witout dag e spic prop of e eeton, ealty or diseased influene inf luene te amount amount and qualty of radation radation re re d or emitd om te leaves and canopies applicaon of tis tecnology to pytopatological res suc as pytopoey is of gr interes A plnt pl nt bome tssed ts sed wn any biotic or abiotc abiot c factor factor advers adversely ely aff growt and development Sess can e acut or cronic, and can cceerate 489

4

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NSON

ny chg that resemble the senescence syndrome (2) Ss or dsease is expressed in ny ways. Poblems in water spply or cono of tissue water balce cose stoma and impede photosynthesis, redce evapospraton, evapospra ton, and ncreae lef sface tempee Otr symptos inclu mohologcal changes such as leaf curlng, change in eaf angle, wilng or stuntng, and chlorosis, crosis, or premare abscission of plt pts Decton and rid accurate quancaon of early smptoms e often difcult Remo sensing is a mns of ctng and assessing chges n plants and cnopies. However, re e my m y ns of sess, nerous infectious diseaes and physiologc phy siologca a problems, problems , as el  injuries cased by insects d/or nematod Fhermo, damage ofn slts in thinner crop pans but more ba soi or weed infes tations. Notwihsng te tle of ts pe,  do not resct ferences ony to applicaons of mo sensing mets in pnt paoogy and pyph oy Successl use of remote sensing is dependent on the accurate study of hlthy and diseased plants and caopi wih conventional methods To evauate inuencg facto, e must copa remo sensing data om heahy plants wih daa om pns under sess Gener ascts of remote sensing and convenona assesment of vegetion e o discussed VISUAL DISEASE ASSESSMETS

Or visl system, the hn eye and brin, is a good eample of remote sensing; e aire, yze, ehance, d store images in enoos aes and at high spd A ined peson can select om te mass of informaon that is available visaly and pick ot specic disease symptoms By conast most remote sensing insumen inteate al a l the recored da, which then mst be comptezed, redce, d enhced before it cn be nalyzed and evauated. ere a various meo of making visual disease assessments Some are bsed on the Weber-eh Weber -ehner ner la: Visl aci is propoionl to he logarim of e intensity of e stims (145). is la h lge seps in te scale ond % infted ea d deeing steps at boh ends of he scale Oher hods e ed  ed on o n ine reatioips reatioips etn stimi d d pcepon nd have a consant stepise incrse fom 0 to 1% visal damage (54 140, 146) Many resecers have sed pvisional scaes adpted to each actual projt (146). he provisionl sce may e cacad to a rcentge se ve vae ced d d    dx 27 c is distinct fm fq fq  Even tog tog hn vision v ision is nie nie te te e individl ind ividl dfferenc dfferenc in ligt or color perepon d ths in te ry of estimating color, shape, size, and patte of factors lie diseae symptoms Accommoon and spati contst sensivity sensivity  nden to a e-conin e-conin vision (313) Unsit-

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491

able illuminaon in color d nnsity, as well s the background color, may all inuence visu assessmen Tirns and lck of concenation also ru prision Visul inreren is lso impot; for example  having asssed heavly infd plots it is esy to underestima slght infec tions or aer havng ha vng assess slight infctions it is ey to ovesa eas that  hvily infd. Sheo et  (320), in a tst with two oups o ve experienc exper ienc scors found  ovestion was st when the ifect  w smllest often ng wo to three s the actual e When two lves h equal tota spotd s the lef wih smaler spots was usul scored higher Regrsion lysis showed that overestimion w inveel proporonal to the naral logrithm of the disease  for ll scorers d also drectly proronal proro nal to the number of spots s pots for ve scorers scorers Substan vraon twn rs at vsul disase assessnt hs als o en deonsad by Nuter & Schultz (278) Shokes et l (322) Weber & Jrg (361 d sona infortion) d severl of my own expmen (unpublish) A view o accuracy relability d illusions in dsese assessment is given by Campbell & Madden (5). One sdy comri co mrised sed 223 color photoraphs of vrious-sized ngl infec tion-spots from tre golf gens in 19 E Nilsson npublished daa). e exprint was originally devis by B Gerhrdson  evaluate biological conl of ngl infons through through the use of acterl acter l isolaes Spic funga sots wee docuened by color photogrhy monhly from May to tor once usng a digial cmera (Kodak DCS20) as well  a hand-held Croscan radiometer The cues were rst gradd by 11 plant athologiss in relaon to  amount of infectd ara and en evaluat by ultisal image analysis There were signcant diences in ssessment accucy tween t rs  te intercept slope d vraon One rter with some deee of rgn color blindnss overesiaed slight isase infections and sub sntilly undrstimd hav infons in compison wih he average of his colleagues A twelf person who sued om more seve regen reg en color blinness had s excted grt difcules in assessg the disase severity  many diseses caused bo by infections (eg some val infections) and physiologicl ssses (eg dmage om air polluon) the symptoms  not advncd enough enou gh to be visul visu l at e time of o f assessment Frdericksen Frdericksen & Skelly (107) port that net photosynec rate decreased up to 1% fo vsible smptos o ozone inju bme evient on Pn n Ehrh. and Lrdrn Lrdrn  lp r r L. and yellow olr Vaous orns ae of dierent relative imoance for plnt owth  studies of lef rust of wht, Sck et al (318) estimd that the g lea and t wo laves iediately below conbute 26 12 nd 3% to the nal gn g n ave ge disease sevety sevety weight respectively The linear rerssion of yield on avege



g . r y o . l s n w o e e i v s u e l r l a a u n o n r s n e a . p w r o w F w . 4 m 1 o / r 7 f 2 / d 1 e 0 d a n o o l n a n w a o r a D P . 8 o 2 D 5 - l a 9 r 8 e 4 : d 3 e 3 . F 5 a c 9 i 9 g 1 l o . l o o n h c t e a T p o e t y d a h d P i s . r v e e v i R . n u U n y n b A

NSSON

r ler was inican wi a lo of 07 an an R  3D 00 When he emaed lf  everiy of eah leaf w weh by he relave oni buon of tha leaf o ob ob  an effecve everity (ES) r ller he reion bewn e ES an yiel lo was hgly igncn w R  0.6 an lope  0 Viual asemen of plan ea my be fcl by vaous ie (0 0 57027278280 70272 78280 assn o publh cale (0 32836) 32836) compuraie ainn proram uch  DISAS PRO an (2627627) 27)DSAN (35)n MATE (Ger AALFA.PRO A ALFA.PRO (26276 Wer Sofwe Euin Germany; peronal infoion). Trainin by uch compur pra can be very co eecive. Wer & Jr (36; G Wer personal informaon) umen ubnal vaaon wn aine  unaine raer n accury n reptabliy i asin cere powy mlew. Aer aining wh ESTIMATE he accuracy of 0 ra ncre on avae ava e from R  0.80 o R  0.2. However even w ining ining variaon amon  rater rate r rema an impoan ource ource of eor in vual ln e en (. Ree enn y o o a more objeive an conen mean of asesng crop lo an may  a valuable upplemen o cnvenonl meo (ee 7 7 273 32 HE Nlon, unpuble) [or cuo on meo of plng te plans n area o enure accue repreenon of te nne pln ppuon  aer  refe o ( 5 6  7 6 8 2023336 337360)] Sie eec le thoe cue by culvpfc roe energyon ung retnce recon ple r ulple nfon ynergc n cove patoen n cemcl conl gen ae ll potn con eon even n mpln o compre vul emen an mo m o enng a STRMTL RMOT SSG

Te rm remoe enng  uully rece o numen ta aure elecoagnec ron reece or em from n obec obec  he nuns ror raiton n vaou p of e elecrognec elecrognec pecm ulavole (UV  nm) vle (c 077 n) ne n (NIR, 773 25 nm) el ne (2.55 m) m nm) nre (MR 325 cwave ec (73). ere are ome ference n e lure on hee wave rane rane an R  ofen ofen ue na na  of NR e uman eye cor ree viu l rnge re (R) grn (G) n blue  bu eniviy o  o r over 6507 nm  lg A roeer cn recor mpon el alo n NIR an loner wveleng ecnque for recorng infon in nonconc enng nclue: cm-

REMOT EG  AGE AYI

g . r y o . l s n o w e e i s v u e r l l a a u n n o s n r a . e p w r o w F w . 4 m 1 / o r 7 f 2 d / e 1 d 0 a n o o l n a w n a o r a D . P 8 o 2 D 5 - l 9 a 8 r e 4 : d 3 e 3 . F 5 a c 9 i 9 g 1 l o . l o o n h t c e a T p o e t y d a h d P i s . r v e e v i R . n u U n y n b A

9

es wi lms and lts in diffeing combinations; scili eleconic insments  radiometers, video syms son insnt aa ins n e use of vious pforms, heights, d distnces satelis, spe hue, high-atitude and oer airca unaned powed plaor, ba n, heicots, radiopilot model aic grond-baed ckmounte hyaic  or other paorms d handhed sytems and cose rge photo  y m and maocopy, b optic maco- and miccos e amount of ret ight (raiance) a a peen of incoming light (iradi) is usuly cale the n fto If the adia om a heay leaf is  by a suitabe adiote it is possible to dett a sight ree in blue (45080 nm) and  (67 nm), a litte more in  (550 nm), d ubttily moe i N at 75  he light rectce i the viua ge i a ut of the inteni of light op tion by vaious plant pigments such as chorohy and xanthophy. Any physiologicl sss, disse, or edc amont of hotoynetic ignts caus an increase in red and be etane and oten o ats the yeow egion Moove, NIR c oftn de ubtntialy Chge in pal ignatur due to cieies of nuiens and daage by pathogen pets nd envionmental ftos have been widely eoed (eg. 113 84 185 281) t is some scient to yze oy te eve decre n  rence (270) Howeve, better inomaon can be obtained by combing data om vaios sca ange ch as R o (IR-R)/(IR+R) The  atio is often closey coeated to the la aa index (LA) wheeas te atte (the nomaiz dieence vegeton index o NDvi) i oen coey coe ted to gn biomass Chges in hee rtios my be a etive estmte o  when data om dient pot o a of a ed e comaedven if the ic reaon of the e cannot be idene Mny othe foae or vegeon indce have been deveod to duce msc data to a inge nmbe to aes chaactetic sch as e ea biomas, and ess. Some reeche ccte Dvi cicay for ctan IR-bad whe othe e dieent a bd combination and name to dingih tween qantitie o condition. Sic example incude nfod vegeton index (Tvi) eendic vegeon index (Pvi) oi adjsted vegetaon index (SAvi) aomed soidted vegetaon index (TSAvi), MSAvi (modid SAvi), weight NDvi (WDvi), bighe (BN), yeown (YN) gnne (GN) gn vegetation index (Gvi) noaied pignt chorophy index (NPCi; uing 680 and 430 nm) and hysioogic retce ndex (PRi) PRi i dene by Penea et a (24) ad Gamon et a (108) as Dvi ing 0 d 30 n Aden o t oec eect nd so rece ve eutd in SARvi (242) F adjustn have been ggeted by G & Guyot (12)




NSSON

Gamon et al 18 ma dal now-band spetal etane meas n of sflowe leaves. The PR corelated well wth he epoxton stte (EP) of the xanhophyll cycle pgments d wth the ecency of photsyn tss n conol and noen sess aopies but not n wa ses aop ngong mdday wln Both the conol and -sess canop had mdday dlnes n vsble ecte, and the eectnce change n the een (near 55 nm) w spcally notcble n the -sess copy  the canop had a sbstal cle n  frm 8: A.M to noon In he warsss canopy thee was lle dal change n gn, but a slght nease n ble and a lage nase n d tane P calculaed on 55 and 531 nm ave t st coelaton to EP (calclate om mol concenons of e thr xthophyll cycle pgmens volxanth, anthxnthn, d zxn) for sess, whes the combnaton of 57 ad 531 nm was best for water sss P s assm to mpove conventon emote sensng sng the (IR R)/(R+R) rao Ado nformon on the se of scl ratos (mnly for mes ent of bomass poduon) an be found n the follown efeenes: wheat 5 12 15 1 175; wheat cltvas 3; soybean 17 18; z 17 75 37; sunowe 8 2; sohm 311 312; cotton 37; agave, sweet gum 18; Amnths sp (e pgment) 77; gass bomass 222; gssld 37; s d foss 7 7 18; PC 2; MAv ; fcto eff 12; othe cps ad dsees o genel spects 11 17 7 727 1 25225 25 257 2523 Todd et al 33 found that Dv, v and Gv fod much tte

on gazed angelands whee the senesent vegetaton omponent s mnmed as comped wth naed ss, and that d eance vales 3 of ndsat 5 e moe sefl n dscnatng tween senescent vegeon nd hgh-eflcng sol backgound Howeve fo low-eng sols the othe nde should be supeo Baush 2 ad Q et al 38 ggete a moded Av (Mv) whee a sol-facto (Lfato) spplemented the odnay Dv fo bette senstvty to sol cove n stdes of co and coton caopes an & eale 1 Evet e a  d Wegand e a 3 3 dem onsted good aeement when compng R ad vaos vegetaton ndces and bophyscal pametes of lflfa gases and wheat and co, es tvely, cod va a mlspcl vdeo d adomete sysms n cent y, sch h povdd eve moe evdence of the seflness of vegetaton ndce nvolvng ohe wavebds such a md-nfaed togehe wh R and R fo stude of anopy wate status 18 57 7 8 1 18 38 Malthus et al 21 ndc a the mos poisn  eetae we beyond he e 77 nm n stuies of su beet aopes nfeted by bt yelows vs

M EIG  IMAGE AYI


5

The avaiabity of more advanced nowband diomes has spured in terst i copy sp propees that  aso in the id-infed region This ron is greaty inuenced by biochemic propeies of the eaves such as the contents of C H N O srch ceuose, ignin, and water (2, 56, 75, 78, 294, 2298, 362364, 376) Pry & Lnschager (295) reviewed the histoy and fomu of some for doe vegetaton indices Mny of these indices ae cacuated using data om oer sats a raiometers e omuae may ee to e m to aord ith the propes of wer sensors, s we ith te spa propeties, gowth ahitectue, and wing conditions specic to newer cuvs Such modifcaons shoud  based on we-deined pant maria (eg  om heathy anopies suppente y data om nopies infecte to vros isese eves y spi pathoges), d shou e professioy ss. Pt re so spp isoge es of os rop pt spies for appropiate fed epeiments to be conduct on caey seected sites The test canopy coud  design via fertiion or iigaon, for exmpe, for optim vation s a test mateia.  impott aspt o rdiome of rop anopies is the variao  sor ange duing the day and its inuence on cnopy eectnce that ay e reated to pant row oientaon (166, 305) Bgu (26) in pticu sessed the efft of sun ange on scta vegetation indices for vaious homogenicies of the canopy. Lord et a (208) repoted tha sun nge afftd the d more th t NIR ectance of four crops at vaious row dirons ad distancs (wht, NNWSSE rows 1835 cm apt; baey, NNW-SSE rows 18 cm apt co, NNW -SSE rows  cm apat; and sunfower, N-S rows 92 cm apart). Suh an et is aso reated to growth stage pant si, canopy archict  soi oerage Not tat a 2m ro iste is ommo  eres  Swen, wheras 15 cm or more is common esewhere. A mere 3m differece in w spa an signicanty afft the reationship tween recorded soi and canopy ectance and thus the ectnce of R and NIR, nd mst consequenty e consided at handhed riomey Chnges in diua spect propees e aso caused by variations i moisre sss (161 305 323 HE Nisso upuish)    ss tia. oence to war sess of individua cuvs of many crop species vais, as does the inuence on sess of insuffcient soi water, the effts of frtiiers  disases, or othr growing codions Def o eves iuencs the sct retne (303). Piter (302) demonsd a signicant coeation betw dew densi and the ratios of NR (769 nm) and yeowish en (52 nm) as we as twn MIR (20802350 nm) and red (63690 nm). Hunt (148) demonsa a signicant coreation betwn eaf-water thickness d MIRNIR nd Dow ing et a (84) found coeaions within bands in the range 14  2nm




NON

Dewfal, w density, and duration  also important om the plan pathoo gis's poin-ofview  son ow on reoreon phooaphy). The sca signu is also nuenced by he amoun of pigns, eaf agle, leaf suae xtu, diseases and sess, plan growh stage, and growing and measument condions 162). Alon of leaf angles and circadian eaf movement in sding sunowers infted by Psmns gs were repoed by Kennedy 177) and cultivar differences in he way barley spik ed towards he sun were obsered in my ed expern i Swe Usually, soi niogen and war songly inuence canopy spa signaur 1, 262, 23) e facrs as well s variel diens in pt owh and developmen may mask the e of minor disease infons. phie or panophile cereal vriees may reveal differns in spa siaur 165, 3 , 311 HE Nilsson, unpublished da) Pubesence ad awns ay inuence reectance 98, 11, 111, 114, 237, 262, 263) A ren view of stereophotomy of plants wi vying leaf angles was made by Herr

139) One of the ed eints cd out in wden in 2 by  and a suden, Annei Carlsson, demonsaed an environmental effec of eaf spa properies I comprised wo potato culivars differently resisant o lae bligh disease (Pypr s (Mont) de Bary) and had n sprayed a various mes for conol of late bight However, due to the lal climate condiions, the we no visual symptoms of late blight or visual physiologica sss on any of the cuvars at the Copscan radiome on 12 August, bu  spal signatus of the plots were substntially inuenced by effs om the fungicide spyed onto the leaves two days ealier but only sightly on ose sprayed two wks before (eg. 3% de in R d 35% i Blue of the rs group) The agnde of he irradiane leed as polarized ligh depends o he geoic gen of the canopy and the angle of the incin igh on the laves, as well as on the characriscs of the laf sua porn facors  he optical index of refraon and he surfe ughness charscs of  cucle 354) Leaf cule propeties vary with scies and uvs, deveop sae, envronmena odiions, and sss 22, 23, 12, 126, 351355) Polariation phenona of eaves can be interesng in, for example, studies of how vis infon inuences eaf surface pperties and hey can ofn be sn va a polariing fer Remoe sensing of vegeation by sallies ypically uses bad spa bands of the order of 1  width This spal resolution is adequate for ps of  specm where reflectance ony shows dual chge wih wavelength d no ne sucu is evident However, vegeon shows sh rence changes in so spa rnges, noably the socaled r edge" or he shrp change in leaf ectance bewn 68 and 75 nm due  canopy

M SENSING AND IMAGE ANAYSIS


497

popees Ths chage has aed ceased aeo o owd mul spa domey, oaby  eamg he s o secod vave of a ow ad ece scal cuve (50, 52, 3, 144, 192, 194, 220, 294, 309). T ed edge s a uque feaue of g vegeao ause  uls om wo speca ocal pees of la ssue hgh eal lea sca causg lage e d ecace ad chloophyll asopo gvg low ed ecace Hoe e al (44) poed ou ha ed edge measumes ae valuale fo sesss of vegeve chloohyll saus ad lea aa de dely of oud cove vaaos, ad hus ae pculaly sule fo ealy sess deco. Howeve, he d edge s a comle coou composed of a ume of compoes ad vag accodg o pla gowh sage (3). PHOGRAPHY,AERAL PHOTOGRAPHYAN PHOGRAMMETRY

Ael phooaphy was s used  he 920s (245, 246, 335) o suvey nfeco y ymcm mnm (She) Dugg  Te, ad n he ely 930s ad lalms wee used  sudes of vus dsses of poao ad obacco (25). Aeal hoogahy usg oh coveoal ad faed lms was used dug he secod wold wa o de camouage, e pla maeal ha had bee cu ad showed sympoms of wa sess ad wl Ths eece was pu o o use afe he w  sdes of vegeao sesses ad dsses  aculu ad foesy Colwel (7) dem osa he oea of aea phoogahy us pachomac ad aed  o dec ad quafy cop dseases such as ceeal uss ad vs dseas of cs. he mpoa oee wok  aeal hooaphy s epod y (28, 0, 3, 447, 32a, 4, 43, 53158, 25, 229, 330, 36, 344, 358, 359). The success of he souhe co blgh wach pojec  e SA Hmn pm myd demosaed he efcacy of lge-scale applcao of aeal IRphoogahy o co dsease suvellace, ad povded supo fo ue emoe sesg  agculue (23, ) Aeal fd hoogahy h ee wdely used  suveys of fous ad ofecous cop dseases  my coues Clak e al (68) used aeal -hoogphy o esma damage y dseases such as spo bloch of aley, cw s ad aley yellow dw vus of oas (BYDV), ad owdey mldew of wa  eld plo epemes Blauez & Edwads (35) used olo phoogaphy ad spal ece fo sudes of omao ad poo dseases Blazquez & Edwads (36) made desomec sues of colo ad colo aed () phoogaphs of dseaed cucumbe leaves, ad Blazquez (33) made smla sudes of CIR hooahs of a dseased cus ove Blazquez e l (41) ad Gves e al (127) suded BYDV ad cel aphd

4


NON

neson n wn wea by aeral poogrphy. Knder (181) used 70 and 5 m aerial CIR phoograpy of coia crry (Vcc spp) culvaons affd by various sesses diseasesad pess Aeria phooa py s en apped o a r exn n fosy an n are raps ase e  fewer ve assessmen mes availabe n fory. Aal pooapy s a valuabe oo n seng e mos suabe area for ed plo expermen So-poogpy as a pona for poogmeic ureents of e s ad cicure of heahy and sessed pt. Aso  se of rereon pooapy for nondescve assesen of ew on e lea se 2 218 H E Nsson pbsed) h an appan applcaon n pypaology. rly ms we many analyd usng densoey bu ore advaed e pressng n spal analyss ncdng enancens o fae evalaon ave beo pop  e d-95 I ebrked on sudes of ake-a and bcde daage n cereals usng 5  B&W (black and wi) na ms and o e 970s sed Koak chrome inad  44 in Swen (eg 5 un pblse da) d n Tzana for sdes of copr cencywa sss n varos ecos seases of wea Togeh w a yeow er I se a polarizing r a proved e sess dscriinaion subsanally Te B&W "Kodak Hgh S Ind Fil 4 (d Kak Wraen lers #87c or #9b) we used for discriinaon of vegetaon and bare soil. Ren experimens ave used s radopoed aircra as paos for low-ale aera phoograpy o srey crop dsses or monor envron na probems 02106147 422122465). Te sysem deve oped by Fouc n South Aica has  vdeaeras on bod  aircra one w-ange cara for navigaonaoher for taking easumensand a sepae vdeama rdng e arcraf nsmens  ge of e alude cos corse ig angle h poson e s sown on e ground oor dsplay Sil expns ave rty n sed n Uppsaa sng a o aircra w a 5 wngspan tha ies ve sowy only a few e above  eld pos ere s a wide ange veaera for navaon an an IRcamera for ak esrens Te vd ma  smie by rado o a rou-based T monor (8). Rado-piloed arcraf w gapacy vdeocaes and upped w Gobal Posonng Sysm (GPS) for rorng accurae posions are likey   ure A Swsh aser opc navigaon sysem esad o have a GPS accy s cose as 0 cm s curreny beng  n e ro EUREKA proj "Auofaing/mar R Homqvs personal nforon). Such a GPS and rao-piloed reoe sensing syste g alow surveys of ailtul eds for ssed an isease eas in order o apply conol res only were nded. An aave paor for reoe sensing of

M SNSING A IMAG ANYSIS

99

eld plot expents is a lit-weight ound ehile, with a robot run by solar-powered elents and conlled by the nagaon sysm. S'E-BORNE ND ERIL RDIOMRY


e Arican Landsat 1 was launched on 23 July, 1972, and was suceded by ndsat 2, 3, 4, 5, and 6 (No. 6 has bn lost) and the uropean SPOT sallite (Syst me Probataire pour l' Obseaon de la Te). Landsat 1, 2, and 3 had sensors in our spal bands (56, 67, 78 and 8 11 , and nds Themac Mapper 4 and 5 hae two additional MIR bands and one in te mal region (450520, 520, 63690, 760, 15150, 202350 nm and 10.412.5 J), in dition to isible and Nbands. The ndsat satellites also hae other sensors (11) The SPOT sait h thr broadbnd olor snsos 09 00, 7770 nm) wit 20 m gund resolution and one panchromatic sensor (59 nm) wit 10 m soluon. These satellis hae cold etensie auable emo sensing da om aicultu and oresy, including data on plant sesses, disses, and pests. SPOT gies e st geomeic resoluion, wheas te spal soluon o t more rent Landsa is betr adapted or egetaton studi (tre are more specl bands suitle or plant pigments as well as or war absorpon bands in the MIR on and a band in he theal region). These high-altude sysms  o alue or sureillance oer lage eas but their gic resolution is insucient or applcaton as n operational tool in phyto patomey. The measuements are oen impeded by cloud coer and the per om measument untl te data ae aalable or ealuation in phy topatoy is long. The SPOT can be tited up to 27°, but it is risky to compare data m dierent measurement angles. e sateltes pass o Sweden too early in t moing or phyto patomey. Hen, measuents e made oer copy that sotimes still has dew on the leaes and oth s ater the dewl has ded. Dewall has a proound inuence on spa et (302, 303; peon obserations); it is tereo dicult to compae data accuately. There e so wi dier ences in owing conditions betwn aicultul regions.  te south, the growing peiod is about 240 days, around ppsalaStkholm it is about 1802 days, and n the not about 1150 days. In soute Sweden, spring cerls are sown in the second ha o Mach or st wk o Apri, und ppsala in late Apil or ealy May and in the noth in late May or the rst wk o June. Te  also regional diences in soil, clima, day length, and aiultua pctices and use o culs. The deelopnt o a cereal crop is delayed by about thee to ou days or eah 1 m inease in altitude aboe sea leel (23). It shoud also be emphasied that 3-4 days or



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NON

 wk i  long pio where ubil change ca happen in eelopmen n al proee of an agcultu ad hoticultual crop, which inu ences the acuay in evluaon o the spl dta o assessment o owt n picng of iee  ee Airboe diomey i wiely ue in agriculue ad o for ueil ln of s, isees, ad envonmental sess (162)  avge ove ie measumen is at the most suitable time and height c  electe and coorda with conenonal ground assessments In rent ys r e imang rior uch  Aioe Viible o nfr mging Sy em (AVRS) he bn u boh i he SA (7, 12, 32, 33)  in Euro (4,6) Aiboe hypesl iaging radiomt sys ms hae en ed for pplicaon in vegeon studies (285, ): these e lo o intes  phytopathome OUNDBSD ND HNDHD O SNS

So rio cn be handhel or othewise gounbas, e.g Exoch OAX m rior (MSR)which ha or p b imil o Lna 3 (560,  70, 780 n 810 nm), o B Mou Mub Rdiomet, which has eight l bn imilar to dsa Themaic Mapper (4552, 5260, 62, 393, 5 1, 5180, 2nm and 1.412.5 Jm) ing  Exo 0A MSR ound on an expadable nheld pole upplied with  war leel for conl o vertical auen, Nilon (252254) obtained goo coeltion tween a ectance dt n vous dsass o cels d oilsd e. Sil nt exsts n Exotech 0A RMS dta ad stripe st, stem sts an bley yellow dwa ir o wh (9339) ee e nuou repo of goundbased adioetes ing used in eld exn  rious gculural cp specie in studies of pln growth, amout of bioass, the efet of vaous gowing condons, d aage by nuent a polluton ss, disee and pests. However, insucient inor on on owt geoi coerge, ieae identication an ssnt, growing conion or meuremen conitions oen makes repord rul icul o compa n elue Te radiometers we appenly ck mound in most o tse sdes (S Reence 1). U-Cor U-18 pole radomt as a sl age 110 n,whle  Specon gineering S5 h a rge o 110  and the version SCE393 h  rge of 112 nm inally, he Analyical Sal Deice' ASP Psonal scomeer  an ASP FielScF e very fs isments with b opc probs fo the  o 5 nm (512 steps o 14 nm)  5-25 n, resctvely. III s  new hgh-esoluon

MOT SNSG  IMAG ANYSIS

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0

mu-purpose raior or ast measuments in the range o 4910 nm (52). A Swdsh bre opc sysm bing deveod (so f for the aborato) h a very fast opaon with a roution of up to 30, seps   rge 375-1055 nm ("M 3, Now Optics  Ksta, Sweden psona infor on). These high soluon insments  inresting or studi o bi cemca ea components d spa detais of disease sympto A review of ier io and radiome was given by Milton (233) So o the ave raoms y  suppemend wih GPS So insumen ony measu sca data om one diron at a time. To este incoming sunlght (irdiae) uent raiance asurents  ui ov a caibration pa (e.g. BaS coad standard white pate) wi known spec ectance properties calibrations must be made coctly (91 16) Meuremen o the copy must be alatd with those o the calibraion pa, follow by calculation of sunlight innsiy for he same mont as each canopy meurement. Athough laborous, this approh can give good ru on ce sunny ays, but not with chging cloud cover  ecelent solution for aicultul eld plot expiments is t Coc do Sy, veloped by V Pederon (Cropscan Inc., US) The ight-weight radiometer measur rradiance and raiance simultaneously and is thus ess penant of varyng coudiness. The sensors rord 3  wide bands cen aund 450, 5, 550 6, 650 7, 750 d 8 nm. etaled descripons o the Cropscan system e given in (255257, 287, 288, 290, 291). A newer version o the Cpscan system uses an mprove dalogger (LC'' using PC-cds or pgram and data ) and a 16channel radiometer.  have supplend my Cpscan sysm with ex sensors for simueous ordings of  temperature, relative air humdity and wind sd as wel as a sensor for eome o the canopy temrure (25). The ther r as 45° to the canopy to minimize soil inction In ng msurements ov vegetation with goo soil coverage, eg. cereas, clov, alalfa, asses, oise rape or peas, the radiomet is usually kept  15 m above the canopy (55 61), whereas over tato and sug bt canopies, e radiomet is kept a a height of 3 cm above individua plan to avoid soil rence. Very gd corrlations have bn demonsate betwn rnce o individua pts and visually assessed pcege of ea ara ctd by at bght (yoo f)  pots (8 259, 329 330 HE Nilsson unpubish), mild yelow vrus ad powdery mdew (Eh ogo C. (syn   Vanha) eltzien) in sugar t (2) Cropscan radioy ha also bn usel in studies of the accuracy of a new ngicide spy and in dosesponse stuies of ngicides and rbicides in potato, oisd re, and wheat (259), on sd-ent dosages for con lled infon evels of bey s isease (oo g S Ito




NSSN

& Kribay) in six-row barley (E Nlsson & L Johnsson; unpublished), n in sd eaent el lot exent or conol o ahds Rholohu   L) an necton by barley yellow dwar vrs n oats (58 Several o my el exerment n cereals emonte a sgncant coelaon wn gran yeld or dseases n the ierences n Cropscandata rord on vrious days (254256 262; and unblshed). Other repors on use of he Cropsca radiomeer nclue e ollowng reerence 34 13 2 266268 27275 277 287289 29 9. In Austlia t has bn used wih good reul or esation o cotton boll yield, when the plans ere wilted and brown (P Cull, personal inoron) The Croscan domer sys is desgned or use in eld plot exp n t a t otenta to ontor ant ot  eveomnt, to ett n o supplementary assessments to ratonalze and acilitate assessnts and to ncase he precision and objeciveness o early deton o  nd ndaated conol eass Interacive radioetc easuens d vi ual observations and notatons are also possible. The Cropsc syste is ey to use and takes < 2 s to record sal da ro a st are In over 2 Cropsca asunts snce 1982 my average eaurng rate i  4 st as  o n ornary e ot exemens. A helcoter as platorm or e Croscan dioeter was test or suey ng o cro rowth an vrous e area n large agculral els in wes Sween n 994 ee ata were coare wt t conventonal ound data ad handhel Crosca data recore along he ght lines over the els cs such as shang by the ouer ens o the helicoper rotor blade we also taen nto account (A Calsson rsonal normaton) boratory measrements o the dise otcal retance o poto  n e vble an nearne bas 52nm) to deect Polylu uun Pho xigu var !ov and Furiu oln; var coulu have bn reported (28 07) and in the range 4 to 26  on warelon leaves Cirulu vulgri Schrad) nected by downy mildew Pudooo o cu (Berk & Cur) Rotow), a Fuu wlt Furu oo  nivu (FSm) Snyer & Hanen) 7; ee alo 7 or revie o remote senng or cro roton) VEORAY

Although tere has en nterest n ung vieo cameras or mo sensing or moe an a ecae 8999629 69 t se o aerial vdeorahy has expanded uring the past ve to six year Int developments in thnque an mehos have been mae by the resech group (eg Drs DE Ecobr, J vertt W Gauman,  Rchardon, and CL Wega) at USDA-ARS at Welaco, exas, as well a by Dr C ng an

g . r y o . l s n o w e e i v s u e r l l a a u n n o s n r a . e p w r o w F w . 4 m 1 / o r 7 f 2 d / e 1 d 0 a n o o l n a w n a o r a D . P 8 o 2 D 5 - l 9 a 8 r e 4 : d 3 e 3 . F 5 a c 9 i 9 g 1 l o . l o o n h c t e a T p o e t d y a h d P i . s v r e e v i R . n u U n y n b A

Fgue 1

Tree leaves of oile ra (Bc  v  MCzger) infected by Vecl de Ke.,  uded ung Leca mae ay er Te  lea h  area of 655 2• Sta gnatres o cic pot were denti d re wi idecl col were displyed by e imge nayz n mkd s d  Figus 2

a 3 Te  eas  134 ad 42% reively Te gray cale tral igaure a o saaon of  markd area e indicaed o e lf in Figre 2 ad 3.

M EIG D IMGE LYI


0

coaborator at Carton Univi,Ottawa,Caada, and Dr MV Na at Utah St Univrity Logan Utah Th Bioviion Coour IR Sytem (22; Coyot Entrpri,Inc.,Tx i a ingl ln cam Th light i plit into in thr bam ha  rorded by pa nor, ch with nm pecl band wid Th imag cn  xamind on a monitor pray or in combination,whr t imag wi  iilr to tat cordd by Kok EktachromInfrd ilm 3. T Xybion Sytem i a ingl ln olidtat camra with a fat roting whl wi ix bandp tr (219, 33 thr vido ym ar combinaon of wo or mo parae vidocamra with bdpa tr in th viibl ad NIR ran (93, 99, 241 243,244 2,3 Th imag olution of digital camra i ldom mor thn 52  52 pixl (picr lmnt (9 219 and i not comprabl wit a ood m uch a thro nd m 2443, although th iag can b improv by incorporang ima txur into th data anayi pr (3 Ht t al (13 and Wigad t l (31 found both CR-vido and CRphotophy go for smnt of  a and pst of aicultul p Kttlr t al (1 found diffrnc in intrprtation btwn CIR photoaphy nd CIR vidography C vidopy had th bt pctrl nitiviy bu patial uprority wa vidnt upon vua intrtation of th CIRlm Go coation btwn IRR ratio and vriou vgtation indi om arial vidography and hdhld mutipctrl rfecanc dta of ld plo ha bn dmonatd for lfafa (0,gra (,95,co (36,d what af ru (3 Wigand t l (3 39 iniat that automtic gai conol in vido camr may compicat mumporal naly of crop and culti var Computr owar can nhnc and proc automation routin for digitl ultipctl vido img! (34,244 Nw yt with gatr reoution hav cnly bn dvlopd: th B&W cara Koda Vid Mapu (13 th Kodak CDS2IR th Kodak Profionl DCS420IR and Kodk DCS460 and th DALSA IAD9 204 Masnor camra. A rent and xlnt tchnica rviw of vriou digital fram vido camra ytm (DFC i givn by King (12 Th principl limitation of DFC in owcot rmoe ning i h lrg digital imag i An bit 024  04 DC produ ima of ovr  Mbyt ach and with 1bit, 4  40 imagr produc ovr 32 Mbyt pr img Th lattr ar obviouy out of ran uin ordinary dk top or poabl computr t tnfr nd torag rat owvr, nhancd com pur and mmory dvlopmnt y ovrcom th problm. A common 120  1024 nor produc imae that t on a highdnity 3" dit, and mod PC-crd and porab otomanc di ytm provd data poabiity nd a of ditibution Anothr diadvang of digitl iaging i that highquality hadcopy production of imag i xniv.

5




he odak CD42-IR came has a specal range o 412 m, wheas he CD460 model so  opaes only n he vsble age (resoluo = 112 x 1524, and 248 x 372 pxels, respvely). oh caras ca be od dry o a rable Macosh compuer A "color whee acces sary and band-pass lers allow or exposus n several scral bands. pal sowe om Koda allows he user o acqu he mage nomao om e cara's cd ader no ADOBE Phooshop sowe o he com pur scn Exsure qualy cn be esed and mage processg uncons allow e maes such as hose o dsease sympoms, o e enhced selecd, and examned n he eld. Images o deren spa nges can be analyz, as dscussed above on radomec daa (such as IRR) The caras have a bul- mcphone h allows sound noaons wh each ndvdual mage ewer versos o poable compuers wh mproved scrn, memory, by aaes ad mage alyss sowe should enhance applcaon o remoe sensg as much as phoogrhy Vdeomages, unlke IR-lms, e nsanly accessble or evauaon ue e al (331) repor ha vdeography allowed rapd scrnng o nue sss (Ca+ Fe+ and ) o vaous hoculal cops A nowband 680 m l genelly produced eaes sensvy or ealy sss deecon, and pseudo colo lookup ables rmed rl- scenng o he rence. u & ue (332) developd a mage Capure and Analyss ysem or ar-real me quancao o eld crop sss areas usng vdeoaphy Wegd e al (367) ed on  success o aborne muspcral vdeography n monog crop owh d assessmen o sal sss n sugacae Anoh nresng vdeo sysem or closerange sudes s he Japanese Keyence Poable Fber Opc Mcroscope V61 (Keyence Corporaon Osaka) The r opc probe ca be d wh vaous mcroope ad macroscope leses he sysem s ully poable, and he mage ca be ds played on a color scen or sored on oppy dsks. Anoher veo s he Fnlay Poable TV-mcoscope (Fnla crovson Co. Ld ouham, Wa wcshreUK). ITEMAY

Canopy and plan lea emperaus have bn suded or abou 15 yes, bu  was no unl he 1920s ha reseache coelaed lea emraue o evapospao (19) oneh & zecz (2) Tner () and Wegand & amke (368) rs used IRheography (cordng o ermal emace  he sca range o 814 �m, somemes 35 �m) o sudy pla lea empeure. The adven o lghwegh poabe nsmens n he 19s and 1970s alowed use o IR-eography o sudy laonshps bewee waer sss, lea emraue, canopyar emraue, ad sol waer saus n vaous

MOT ENING AND IMAGE ANALYI


0

cp species (159. Millard et  (21, 22 used airrne theral gy to demse varions in cnopy tempertue in  bley eld Json et  (68 and Idso et al (9151 develod the term waer ss deee day (SD as compare with growing dege dy (ODD. son et  (6, 67 developed the tm crop wr sess index (CWSI 'Toole & Haeld 28 studied the eect of wind and demoned tht CWSI values msud at low windspeed overtiated the wr sess but underesmated it when measured at high windsed. However numerous rerche have us this concept (9,  9,  5  ,  59,  62, 22, 25, which is also imporant in pahol ogy as wter sss is involved in many infous plnt diseases. Another crop war stss ndex is reviewed by Campbell & Normn (55. Pnter et al (06 found that infections of sug beet ots by h h Edon Fitp. and of coon roos by Phych  n increaed leaf tempetures by °C above ht of althy plants Siml ndngs have bn obseved on  plts infd by root ros csed by  n (Mt Appel & Wr., h   Trow, and Rhcn n KUhn in the enhouse by Tu & Tan (6 and by Mengisu et  (227 with brown sm rot of soy caused by Phph  gg (Allngton & Charl. W.Oams. Tu & Tan (6 suggeste screening for oot rot sistace by IR-thermogphy, d in Sween, I prosed -hermogra phy and IR-videography for scrning of he most vigorous ee sdlings befo their dsbution for forestation Fouch (0 d Fouch & Bysen ( demonsd tht use of compuer pssed images o lowalude airboe IR-themogrphy nd IR-vidgphy is a quick method of asssing diseases and moisure sess in soy nd whet crops s well as avdo es, and also in monsting the sptil varion in moistu sss and in esmating sess condions for irrgation scheduling Duce (85 eind t infon by common rt rot,  c (WO.Sm. Sacc of two cultivs of spig whet nd bey iodicly om 98 to 1985; he found signicant diences in disease rngs beween he cultiva, but no sigicant differences in lef tempertre corded using a hand-held IRther mor (at Fes owth stges 0,   1 ad 1 1 .2 I stared to use Reogrhy by using a hndheld in 980 in studies of vaous plnt diseses 250. The thnque hs subsequently bn used in eld expents and so grnhouse expernts minly with two IRthermo tes, Telm Ag2s (25 1257, 262, 26 nd Evest  (257. e later pper reviews suls of my expimnts on thermogrphy durng  981988 comrising nine crop spcies and various biotic and �biotic sesses. As an exmple, in one eld expement, comprising 0 oat cultivs with dier ences in root gwth, root cpcit, d rought tolerce, d gown in  sandy sol t conolled soil moisure evels,  difference of l  in g lef tempeures was rorded ween cltivrs with the best nd the least toler-

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NON

ance to drought Even grear diences in leaf temperature were rorded in  grnhouse experiment with cucumber plants inoculted or not inoculated wh ctera nfectos n her vessels. he le temperure of e helthy plans was 6° nd of the fted plns 3. When  fn tempoaly crcult the r (mp  ) the lves of the nfecd plnts mn t aout 3 whle he lf mperature of he healthy plans fell to 890 ut later irsed to their previous level  eld exmens with IR-thermomey t Uppsala n sping wht nd arley compsng culvars wth morphologcal dfferences (fol develop nt d ot owt) dsprtes n nnsy of rrgaon nd nogen fer tlzaton resulted n sustntial vraton in leaf and cnopy mperatures Spse N-level and no irrigon causd weak root growth particularly in one ley cultvr, d cosequenty csed lef tempratue Afr hevy rai ths oe culv produced new gr tllers wth lower lef tmptu han the pvious leves ere were also dfferences among the baley cultivas in amount of wns on their spkes and in rpenng On some cutivars he wns remaned gen longer which so inuenced the obseved canopy mperature 6 63) Awns nd leaf pubescece as well as leaf color can aect engy lnce and cnopy temperture and therefore the results of Rhemome ( 99 8 2 5) In a preliminary experment I oserved that the ag leaves of oats infected y aley yellow dwaf vus were 3 warmer than vsually healthy leaves However t can  dcult to evalute how much of the temperure icrase was due to he vrus infton or to eec by he vrus vectors eg various insects Water sess in plants inuences vrous pysologca paramets photosynthec eciency d levels of osmotic compounds e (286) which n  rent revew by Cbera et l (5 is suggesd to increase susceptblty to phids It is also mentoned ht phd nfestton causes doughtstress symptom in leve of ley even in e psence of sufcent root mostu Cbre et a () so epo tt inceng apid infesons of baley can subsntally inuence amounts of soluble sugars proline glycinebetaine chlorophyll nd con assimilon d photosynthetic rate as well s e leaf water potentl n brley he wter pontals of arley leaves ifested with oly 8 phds (S. gramineum) per plant we sgnfctly dfferent from the nonnfesd conol and  phids per plnt decrsed le wter potentil om .5 to .86 MP in comprson wth nonnfested The mechanism by whch the grnugs cause such a drop n lef wter potental s unown ut the nscts damge the cucle nd epdrmis the cells lose war d it s concluded hat severe aphid attcks cn cause wter sress When he aphds sck lef cell sp hey utlie ee amno cds ( Brsh & J Weull personl informaton and ejt a lot of soluble sugas wc   lye o

M ENING AND MAGE ANALYI


07

honeyew on the leaf suface inluence the light refectance and evapoan spiraon Differees of    or 5°C in flag leaf temeraure of cereals ue to root and vasculr diseases such as barley infected by Penph  gmne n wheat infec by ephlspum gmneum Nis & Ika have often en rorded in my eld expeiments (251 252 256 Similar effects have en rore in oisd rape infected by ellum le Keb d clen sclem (Lib e Bary (25 A slight to moerate infection y e- disease Geumnnmces gmns (Sacc Arx & Olivier var. c Walker in wht once caused an incase in ag leaf temerature of 7 over healthy plan (257 Signicant corlaons have been emonsatd in several of my eld expements between cumulative "CnopyAir temerature (x) and isese sevety  or gain yield ( (252 25 262 263 HE Nisson unpubished siilr to those of SDD discussed above On numerous occsions I have observed that slight wind gusts of 25 s or more cause a momentry drse in leaf temperatu and tha the te erare drop as wel as the time neede to eturn to the previous vaue s corelated with the sevey of root and vascula dseases or in other words to tolerance to water stss Although tempeatue dros and intervls ae most inteesng to study wind gusts may alo comlicate routine measurements of canoy temperaures and mask detection of minor disse infons nd make evaluations dicult Smith et al (25 reportd that sipe rust on wheat initialy reuced stoaal closu nd disrud the cuticle Evaoansiration om the leaves inceased and the infected leaves wee O210° cool tan the controls duing ealy disease develoment As the isease progressed however infeted eves senesced more raiy evaotrnsiration ecased an eaf temperare incrasd We can also assume that dese sucia hhae ad hyha ats on the leaf surface cn inuence leaf temerature recorded by ermogra hy The literature contains many orts on differences beween races and stins of various pathogens fungi and vuses on the temerature or infeon oma They may give socalled tyica or secic symptoms at one air temeature but react diferently at oly a few degrees higher or lower a temeture Uneven soil moistue in ot exeiments may result in variations of leaf temratre and consequenty in the develoment of spos in spore germination and in isease syptoms Research into iscrimnation ween rces nd strains of leaf athogens as well as cultivars should with ference to the above ndings  sulemente wit Rthermogaphy and icrocli mate studies including aduate conol of wind movemen and reative air humidit (258

0

NON

thermaphy shuld be cnsded a valuable tl n plant pathlgy, phytpamey, d epdemlgy IRermgraphy shuld  cnsdere manly as a supplement t ther mte sensng meths rather thn a stand alne methd t evaluate actrs such as cult d erenes n susceptlt r resstnce t sess ACE AND ASSIE EMOE SENSIN g . r y o . l s n o w e e i s v u e r l l a a u n n o s n r a . e p w r o w F w . 4 m 1 / o r 7 f 2 d / e 1 d 0 a n o o l n a w n a o r a D . P 8 o 2 D 5 - l 9 a 8 r e 4 : d 3 e 3 . F 5 a c 9 i 9 g 1 l o . l o o n h t c e a T p o e t y d a h d P i s . r v e e v i R . n u U n y n b A

Te scussn tus  has een n passve remte sensng, e te use  ms r elnc nsuments t meaure the elmagnetc sla enegy red m te vegen A prerequste r detetn nd assessment  stss and dsease s the hmgencty  the canpy and cen sla lght cndtns see abve Actve emte sensng methds, develd ve the past  yers, rt ntensve energy pulses  scc waveengt aganst t egetatn; the sulng ntern s mntred and the physlgcal status  the vegen s analyzed Amng such acve rem sensng methds e Lght Detn and Rngng (LAR), whch uses laser lght anagus t R Dectn and Rangng (RADAR) remte sensng (0) MO NG G LDD FLOECENCE

The urescence  ceran plant cnstuents has lng n use n the study and elucdatn  phtsynthess and related physlgcal mechansms and ctns ly urescence asurements used plt extracts hmgenates r chaacrzed elements  the plant cell The develpment  hghntenst lght sces such  te laser has made t pssle t ect uale urescen n te ntact plant als y remte sensng  cntrast t electace speca where nly spectl changes resulng m t asrbance  lgt by chlrphyl and water a appant urescence spa have mma that elate t spc plant cnsttuen and the electnc states As te cncenatn and dan state  mny plant cnsttuents are unctns  the vgr  the plat urescence measunts can n  lad t bhec and physlgcal changes nduced by stss r pahgen (61  6 6 192 195 199) In Nvee 989, the "EUREKA prject LASFLEUR stred as a Erpean cratve search ert t nvestga the uture applcatn aeld lasernduced plant urescence r snpc, rne envnmenta mntrng  vegettn and he   helh  plants n agrculture and sy (  1 1 12 21 2 ) ' Anlyss  e uscence rat  RNIR (such as F6930 r

M SNSNG AN MAG ANAYSS


09

F685F7 nm) alows measuremen of he amoun of lef chlorophyll nd hus sess effecs on he leaf (51 52 87 88 193 1982 31) V-laser-illuminaed leaves emi no only red chlorophyll uorescence hey also uoresce lue and grn (63 6 2) The red chlophyll uorescence spa of een leaves long used in phoosynhesis research (176) possesses wo uorescence mxim near 690 nm (F690) and 735 nm (F735) (199). The raio F690F735 can e used as a sss indiaor of he phoosynhec appa raus and applied as a nondsrucve indicaor of he in vivo chlorophyll conen (192 193) The lue uorescene of een veeaion ded as a genuine pn signaure almos 60 yers ago (176) possesses a maximum near 50 nm (F50) and a shoulder in he grn ion near 530 nm (F530) (6) The o 50 F690 which can differ eween plan ypes ecause of rowh condiions appears o e a suiale sress indcaor of plans accessile for remoe sensing (6 65 131 132 197 198 201) The nau of he lue uoscng plan susnce(s) is no clear u here is armen ha various plan phenolics  he major compounds responsile (327) Phenolics are of scial impor ance in plan pahology Remoe measuremens of luorescene have een widely used in vegeaon sudies: hea damage (317) frzing or chilling injury (6 18 32) high nd low herma sess and waer sess of oak Q  L.) nd soyn Gln  ( Meri.) (228) Khuk e al used remo measuremens of chlorophyll uorescence in sudies of he aing process and ozone damage (179). Krajicek & Vrova (188) and Valenni e a 350) mde ailed sudie of laser-induced uorescence speca of vious plan spies wih environ menal sss. McFarlane e al (223) wih a Fraunhofer line discrimnaor used sunlih-induced luorescence in a 656.3 nm raunhofer line o sdy waer sss of lemon rs. Usng a pulsd 33 nm noen laser McMuey e  (225) dscriminaed ewn levels of niogen ferlizaon and deciency of ield co (Za y  y nalyzin uorescence a 4 525 685 and 70  Simil hniques have en used o de oher nuien deciencies n co and soyan (62 6 65) and ice plans (333). EW Chaplle & JE McMurey (personal communicaon) demonsad dierences in luorescence scra due o  M and K deciencies and powde mildew of cerea lev Siniican dierences in uorescence in he range 720750  were o sered in sudies of pea and ean leaves infecd y vises usng a ve hh resoluon M 5 radiomeer HE ilsson unpulished). Daey e  (82) and Osmond e al {282} used ideo mang in sudes of vriaion in phoosynhec aciviy nd he effs of virus infon on lev y close rnge nondescve mesuns of chlorophyll luoscen. The gr poenial of high-spd video imagng of he uorescence inuenced y

10


O

the effecs of vis infection on photosynthtic activity as demonsad by PF Daley during my visit in 12 80 81) A edish system fo mlticolor imaging of vegeon orescece fol loing lase excition as develod fo emo measrements at distces of p to 50 m 87 17 1) Floescence spca at selectd points ithin the detton a ae msud ith an imageintnsied diod aay syste. Iag pocssng allos xtction of informaon lad to th physiological stats of vegetaon A simiar exriment comprsing monitong of healthy nd chlooc leaves of Fagus slvatca and Pcea abes is repoed by Edne et al 88) nd of e d slightly senescent leaves of Ace ptanoes 88 171) The advanced insment system has appant potential fo stdies of plant sss and diseases RADAR AD MICROWAVE REMO SESIG

The use o adar ad icroave adiometry in remote sensing of soils ad vegeation has osed consideable intest in ent yars; his the is less enced by clod condions d hs potential in stdi of moisue conditions of soils d plat copies inclding ate sss d shold be of inst to plant pathologists  12 20) DIGA IMAGE AASIS

Dital image analysis has come an important tool in biological srch. Examples of its application inclde aalysis of satelli imags al photo gaphs ad videographs macscopic and micscopic images onst con of mltispecal 3Dimages in cofocal microscopy and oscence lif stud ies acostic images ncleic magnec sonance imges (NMR images in electron microscopy and animaon of timelapse images rcordd in very slight illmnaon to avoid the problems cased by too intensive light) Ino t al  152) evied vido tchnology and i application in vido micoscopy inclding lamicroscopy ad confocal microscopy Image pcssing dces the toal information to a managble amont enhances edges and othe dtails makes gomeic correcons etc po to analysis of measements o identicaon of size ea shape pat o conng scic details Digital images can be added or sbacted ad diffences betn to images displayed. ne iage ca be divided by anot pixel for pixel in orde to make aos sch as betn a ed ad a ifrared ige othe calclations as discssed above fo adiomet ne gt advantage is that e ca display paticul aeas in scic o contrast colos nd ths facilit visal intetation and intective alysis by the operator d the copte. Sc contrtnhanced ies re so 

M ENNG AN MAGE ANY


51

excellen ool i n lues nd demonsations in pln pahology. The enhance  ayzed imges ca e pred ou or sored in a mass-mory (eg opca disk).  he compuer is connecd o a newor i is easy o transmi imges bewee dsa researche. Today here s good sowae d hdwae avalable on e mke for digial image analysis boh or MPC-compables and Macinosh compu e Vous sowe eios can e adily appld o phyopahology, nd in y cases i is arly easy o modiy hem or pcu purposs. he inesn ay appear cosy b in relaon o wha we can do ia his hology in phyopahology and phyopahomery he invesmen is pro able o scienicly and economicaly no orgeing increas rsona caiiy Nurous pars hae en publshed on ige analyss n aoe remoe sensing mos o hem conce osy ad ewer agculura crops So o  repors coe phyopahology Jacson e a (158) ave an ely demon son o how aera IR-color phooaphs can be enhanced nd colorcode o ae isua nerpaon o he isbuion and seery o roo ro in pe elds hanges o wnrllig in alala om one ye o ohr are shown by Bsu e a (20) usng sila mehods Among more recen repor  on aeral IRphoogaphy and coprad ge anlysis o sdy environmena sess in snower and Dch elm disase (202, 20, e eecs (29) ley yellow dwar rus and cerea aphid inesons in winer whea (27, cus sess (1 91 , 31 0), dseases o omao poao cucumber and waeelon pl nd cius rees (35, 36, 38, 41), dmage by nemaodes o coon and roo ros o coon alala an pecans (11) Blqe & Hedey () nd Blaque e al  made copr-aded spcophoomeic meas uremens o 35  color IRilms o oao leaes an ond good coelaon bewn rangs o he rao o 480/610 nm n lea non by bacea an y la ligh Slar sudies o cius re heah are repored y Blazuez (2) using raios o specra peas a 510520 and 6620 nm Digial image aalysis a macro nd mcroscopc levels in plan paology is aracing ncing ineres d has en usd n sudes o ous nec ios dseass and sss o many pln spcies (13, 15, 38, 9, 1 15, 1 16, 187, 1 90, 2047, 230, 239, 248250, 268, 272, 321 , 326, 328, 342, 349, 356), bu here is no room in hs chaper for uher deails y sing digil image alysis in connecion wih conocal microscopy i is also possile o nondesucively analye ling plan cells and ssues, eg eens o cyoplasmc acions o Ca2+ and W in mlliseconds (21, 31  MA Browne persona inomaion a he Royal Mcroscopic Socey meeng Mico-94 in Lonon 194) In mode nstumens we can ge na-simula neos eciions o seveal laser lis and record orescence rom spos in he living cell no only in s   and z coordnaes  also anaye speca

1

NON

signatures and nctions in -lapse and study the physiology of disease phenona nondestrucvely also at very high spd. It is a version of analysis that n soe aspts is uch dierent o but has also uch in coon wi remote sensing. NM GG


NMR Nuclear Magnetic Resonance Imaging) analysis is a rather new but very advance nondesuctive iage analysis thnology with great potential in phytopathology. Pfeffer & erasimowic () vewed NMR-sctros copy and ts application in agricultural resh and gave exaples of  studies of living roots and fruits of  plts while Gross et al (8) dscusse NM applications to studies of roo and stes gwth and ans po in the vessels and effect of chemial agents. Brown et al (48) use NMRI in studies of changing war connt in vivo in elagonu Morrson et al () stu the distbution of sugar in unrpe and paraly r apes by NMR mcro-imaging and ohnson et a (17) studie tomato root gals case by Mgy g using NRI. Bottomley et al (4) used NMRI in studies of water ansport in root systems of Via aa L with lightsssed foliage. Another exaple of noninvasve histochemistry of plat aterial by NMRI is ported by Ss et al (  ) Vrious versions of  mcroscopy for anatoca studies of ripening fruits of raspbey d goosebey uits Res spp.) are repo by Williason et al (774). Goodan et al (    ) repo applicaons ofNRI for noninvasive anatoica icroscopy ad studies of infon by BO/s cneea Pers & Fr. in uits of raspbe Ruus e L) Halloin et al () used  in studies of disease development in sugbts caused by Rhzocon solan. SUMMY

Reote sensng comprises sever nondesuctive meods to acqure ad anaye spal propeies of vegetaon fro various distces rging o satllites to ground-basd platforms. Multspctral imaging alows nondesuc tive nalyses of plants pathogens and plant diseases to  ade down to microscopic and ultmicroscopic levels. Tchniques and ethods of multi spal radio photography videogrphy IR-thermography active ad passive reote sensing rad and mirowave reote sensing laser-inducd uorescence ultispctral image analsis and  all have a great potentia in phytopathology and phytopathomey Although we cnnot yet identify a spic disease or stress by cunt versions of reo sensing we can oen detect (even previsually) d quanfy its intnsity and also facilitate rationlize ad ncse accuacy of rsearch

MO ENING AND MAGE ANALYI


53

in pytopatology ly dection is impornt for needadapted conol asur Meuremens using for example Cropscan radiomey in te sumr c pode aluable ata nondesucvely not only fo monitoing plan gowt and indications of supplementay studies but also be of grt value if t eld plots cannot  avted later on due to bad weater conditions or oter rsons Aeia potoapy is a vauable tool in selecting te most suitable ea for eld plot experiments Mo eac is needed into ow arious synergisc and comve masng diseses and environmenta effts inence spec proties of cps ad cultivs. Access to ceaper ad more accua insunts for routine applications sonnel training and good inteation collaboraon to facilita te dissemination of infomaon  l vil. Te accury of conentional disease assessment tods must  enanced fo use in compaisons wit remote sensing data. A disee or stress measumen using remote sensig in e eld is still pimiy a compison of data from stss  wit tose om te soundin ety copy n te te more adanced insments and eater experience sould facilita and increase accurac in plan disease esearc. AW I t F Nutter and my colleagues B Gerdson nd S Bisamm for tei crical ading of te manuscript n for teir vauable comments Special tanks o VD Pedeson for numerous discussions advice and suppo on te Cropscan Radiometer Sysm. Sincere tks e lso due to N Rollison and H oud for linguistic ssistce. Any u w capter,  we  an artle cted in  u w chapter, may  puchas fm the Annu Revew Preprnt and Rerint ee. ··7·7; 9·7 em: ap@c1o

Ltertre Cted . Anonm  9 "   .

3

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Groth Stages ad Dsease Assessme K Middesex. UK: Minis Agric Fis F Anms 978. Crop sctra om CE eld meuremes NASA· Jnson Space en ouston, TX Large Area Crop Invent Exri· mn E R 69. JSC·B7.U 9  Deled  f Dlt in p Aa JK Sioway  98 Asssing wnter wheat d mt prucion vi

c ce muemen R mote Ses Eiro 1 1 6777

6 A A Ca T A. Msie DR 19 D1 ig mon n f eence espons of pns to ch11ing Remote Ses Er 47877 7. Ak TE. Nue  . Bnks PA

989. Measurng herbici njury to soy· n g  aom Wd S

82527 8. Ans K 2. Mepn mte

lng "SU·just ". Ine J S U ic ci Upa p 2 9 AYis S Knz  1972 Bsimm

514

SSO  optmalen Stchonang f phatlisc

1

Untersuchungen

Pol  74:57

Atan GA Neae CU. 1 An  sment o vio vegetation indis f t eval o bioysical poies o alala r Ben Work

tls or physological sties r  Mcs S 948 (At.) . Bar . 1985.  np to cp identication a conition asnt 3.

RB Hffr R 1971. ettion o outhrn corn ligt ing colo ina aeral photography. Pr Ben Wo

op or Ael hoog Vog Pln S, 1h, pp 136 Fall


Church VA Am S hogramm Rete Se. 1 1 . Asr G. 1989 eo d Applco of pl emoe Seng Nw Y Wey 73 p 1 2 Asr G Kemasu T Yoshida M. 1985. imat o leaf a index rom al reectce o wheat uer dffrnt tl pti and  angl 1 3.

l Phyophoogy 81 16 . Bac H Dmcran A Mauser W. 19. The ue of AVS data or e termintion o agricultural plant development a water content Eu

Spe Ageny E), Erh b 

69-10 1 5.

16.

Ball T, Gdner JS, Johson DA, Hess W. 12 mage a lyss of un iosp whih inft mntha hyo

phogy 811

Bainger C 19. Natue of he re ectae red edge n aratory d FL air imaging sctrometr data rom tred fous ost. In m

ge Peng  Pr Wokhop Ne, 1989, ed. C Elvdg, pp. 8.

Falls Church, VA: Am S. Ph gramm Remote Sens 1 7. Bt F, Guot G 1  1  tnal nd limit of vegetat inces for LAI and APAR sessment. ee SeI E 1 8.

19.

p Color Aerl hoor l S 3rd, Gelle, FL pp 1 146. Falls

Church V A Am. S. ogrm. Remot Se.  Bausch WC 3. So crn efcts on rectacebse op ccets  co. eme Se Enron 613

5.

Bawn F. 1933 Inad togaphy and plant vr disse Nure

6

Bgu A. 19. af a n inrcpted phtosynthtically active aiation, and stral vgtaton n A senstvity alysis for regularclumd canpes emoe Se Eiron 65

eme n Enron 17 1- 11

Ba M, Berger RD Davol TA 199. Cor dgtzaon o vido mag o  leaves to temi the intnsty o t u y Uomye ppendu-

ron 3516173

B  Guyot G Bege A, a! P, Pod A 1988. Cplmnty of mdinfred wih visible and neinfra for monitng wheat canpes.

eme e Ero 6135 Bahlc  Nken LN Wegand CL

197. Aeal hemal can to dtr m tmpatues o sls d cp copes dfferng n water strs. Agro J 3-8 0. Basu PK, ackson H, Walln  1978. Afafa d and is caus n mxed hay elds dterned by aera phtgrphy and gr survy  J PlI Sc 5818  1 . Batten BE. 9. Supr vid rate cn al micrcy a h ptyss

Pr EEE 73 17 1-85 Bauer ME, Mrzysk  MacDald

13 168

59

Benc  Ae K, Ferguson AH. 973. Aerynac and energy balae com paro tween awnd and nonawned brley. Agr  6537377 8. Blakeman H. 10. T intication of crop dsse a sess y aral phogrphy S Ref 32a, . 5 9. Blanchette A. 198 New technique to masure ree dfect using an image anayr P  3 30. Blazquez CH. 197. eme nsing of folar disas o vgtabl cr wth infr color photography. Fl Se 7.

Hotc S 85136

Blazquez C. 1976. The role  reme snsig in phytpathology and cro pr uctn     35 (Atr) 3. B1azquez CH. 11 Measurents of crus t health wth a scanng den stomter from ra cr rared p tgraphs  D . 753707 33. B1azquz CH 1993, Coelatin of densmc measuements of aeal clr infd phoaphy with visualad f cus grves lI Ds.

31.

777779

3

Blaquez   4 ettion o prob lems in hgh wr vltage transmsson a dsbutn lis wth an frard scanr/vido ystem roc Be

Wokop Coor Arl Phoogr eog eour  4th, pp. 03-

14 Falls Church, VA: Am. Soc h tgramm cm Ses 35. Blazque  Edwars J 1983. I frard lor phtgray and sctral re

MO SNSING A MAG ANASIS tae of mato a tat dieas.

J pp hotogr. ng 93337

g r . y o . l s n w o e e i v s u e l r l a a u n n o s n r a . e p w r o w F w . 4 m 1 / o r 7 f 2 d / e 1 d 0 a n o o l n a w n o a r a D . P 8 o 2 D 5 - l 9 a 8 r e 4 : d 3 e F 3 . 5 a c 9 i 9 g 1 l o . o l o n h t c e a T p o e t y d a h d P i . s v r e e v i R . n u U n y n b A

3 Bazquez CH Edws GJ 984 Densoc sudes f coor a co inr ptras ofdadccm leaves a plant. J. magig Tech no 0:7 37 Bazquez CH Edwad GJ 9 Sp ectance of eat and dissed wateln leaves. n pp. Bio. 08:49 38 Bazquez CH Edw GJ Nemec S 9. Imge anass o xem atati n sffd cts rts infected wt usrum soi hytothoogy 76:293 39 Bazquez CH Hde  9. Lae

i ection in ato eld wih 35 m cor nfra aal poa

50 Buscma C Lchtentale  988 Refctace and coryll uo cence signatues of lav See Ref 192 pp. 3232 5 1 . uschma C Lchteth   1988. Cmplete uocee sta temined during te nductin knec ung a dioarray dect See Ref. 192 p 779 52. cma CE Nagel KS Kni  19 tmte f fat mument of in vvo efectae apta a ureee n the isbe d n nfrd Remot Se nron 4818  53. Cabra HM Arg VH Ccuera LJ. 993 Metac cges n baey sdngs a dien aphid inesaion

leves. hthemisry 35379 54 Campll CL Mn LV 19. 

phy htpathog 76:3 40. lazquez CH Heley LE eay  9. Cte add sctet measurns f col and coo nfrared ransparnces of omao btral leaf sp hytopathoogy 76   4 . Blazquez CH Richadn  Nion R Eo D 988. Densitetc measuement and mage analsis of aia colo nfrared ptgraps  maging Techno. 4372 4 Botome PA Rge HH oste TH 19. NMR maging sows water disribion a ransp n plan r sys-

56

838789 43 m AM. 199  L/ki/g Xba/d

58

rucio  at ee pmoog. New Yk Wley 532 pp 55. Campl GS Nm M. 0. 

57

ems in it r Nt  Si US

rar acscattering a optc reecte with ro rowth modes. PD

44 45. 46. 47 48

49

tesis Wgeningen Agric Univ The ethla 169 pp chey H. 14 Aea phaphy f he study of pato bght epidemics. Word Rev. est Cotro 3 68�4 recley GH. 16. Th aial ph tay f tato blight epimics  R. eraut. Soc. 700886 Brencle GH. 1 8 Aeria pap fr t stud f plat disees. I ev. htopath 6:22 ecley GH D CV. 1962. Pato blght ering by arial phtogrphy. Nat. gri dis. Sev.   Re. 5721 25 Brwn JM Jhn GA Kram PJ 19 In vivo magtic oce micrcpy f chagg wate cet  ergom hororn r at hsio 82 1 15 ure MK Lelac DC 19 Rapid measemet of fie t legth using phctrnic image aalysis. cog 612�9

515

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60

main f pant waer staus frm n temrat: an analsis of  inve problem.  Ref. 326a p 2557 Card DH Peteon D Matn Q. 19. Pection of lea emist by the use of visble a nr infrared reectace sctpy Remote Se. vir0� 261347 Carlson  Yager ON Shaw RH 1971 Factrs affecng sa ors  lav th sa empss on leaf wate status. gr  63489 Calsn A Niso H 3 Reme sesig of agrcutura eld pot emets. str 6th S COgr Montrea a p  5 Cchi P Mazzighi  Pantai L Valeti R illi D elis P 19. Rete sesig of chophy a u reece f vegetatin cpi   Nea a f  mem hniqs te S vir. 7:1828 Cecchi P Pata L azzani M Ramoi  19 Te g scta s lution uorcence DAR FDAR3 a the nitorng of t envronnt. r / ir ete Ses I xhib.  Sturg Fe I: 

61 Chaplle EW ictealer HK. 994 urescee meurements of vegeta tin. Remote Ses. vir. 47 62 Chaplle EW McMuy JE II Kim MS 1991. decao  e pgment responsbe fo te blue flusn ad in the e uduc ues (LI) sca f g plat a t tentia us f ths band in emely estimat rates of ptsynthesis Re me Ses vio 362318

56


NSSON

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 ee and lorhy entaon

Remot S ir. 3576 78 Can P Dug , Macr  Plummr E, Peeson DL 2 Reectance sctroopy of fr whe eas f the estimai of cheica conraion Remote S nvir. 39153 79 uan PJ, Wiliaon  1987 GL et n mesen o  ar infrr a le in ri ae. Reme Ses. vir 531816 80. Daley PF. 1993 Choy uor cence aysis a agng n pan sr an ia Astr. t SPP Cgr. Mra Ca p 11 81 Daey PF 1995 Chophy ur cence alyss a iaging in pant st a se C  Plan PhoL 16n ps 82 Daey  Ras K Ba  Berry JA 1988. Toay ofposynic activty of leav oain o vi mages of chorhy uore Plat PhysioL 90:12338 83 Deades  Kaas  19 Remote sensi of cr cition Pr Symp Ct A Sstms Ap proach 10 Decisio Making Charlston SC, e. A Weiss pp. 9

84 Downn HG er GA Hllay KW Cibla WG 13.  raiti equi vaen war icess of eaves Ret S. Evir 46107 8 Dzek LJ 987. Infrd theroy of leaf emrature easrens and cmmon r r of sng whet and spring arley. Plw Soil 10128790 86 De DA acon RD, Musick JJ 19. Winer wat veeaion indic calcaed fm cbinaios of seven sa b Rmot S. vron. 1827 87 r H, Joson J, Svarg S, Wallnd E. 9. lsn ldr mltolor man of veation. Appl Opt. 33:247179 88 dnr H osson J Sva S Wallnd E Bazni M, et  1992 Lasrindced uoree toing  veetatin n scy RSe Ad. Rete Se. I  119 89. ws GJ. 982. ar infr aral vdeo evalua for frz amae. Pr. Fla. Sate Hortic. c 95:13 90 Edwds G Baz CH. 19 Prlmnay ermens wih mo ing o etec cits canr. Pr. Fla. State Hor/i. . 98;68 91 pema G  Sud of es in eld measuents of t bdreciol reance factor. Remot Se Eni r 35379

M SENSING AND IMAGE ANALYSIS

g . r y o . l s n w o e e i v s u e r l l a a u n n o s n r a . e p w r o w F w . 4 m 1 / o r 7 f 2 d / e 1 d 0 a n o o l n a w n a o r a D . P 8 o 2 D 5 - l 9 a 8 r e 4 : d 3 e 3 . F 5 a c 9 i 9 g 1 l o . l o o n h c t e a T p o e t d y a h d P i . s v r e e v i R . n u U n y n b A

9 Esc DE Bowen HW, aman HW, C R 983 Use of a ne infred vo rdng system f te detcton of freeedamag ct eaves J Rio Gran Valle Hori S 3661� 93 Ev JH,  DE 0.  su o ideo systes for mote se ing apicatis. Pr Bien Workshop olor erial Pogr Vogr P S Reed Fl 12 ea 198 pp 29 als Cr, VA Am. S Prm Remoe Ses 94 v JH Eob DE A MA Davis M. 1  Comison of ground ectce a ria vo data f estimat range phytomass a cor S Ref 10 pp 1 27-34 95 v JH E DE Bla C Hussey MA Nixon PR 19 Evu aton o  mdnraed (145 to 0 /m) with a backandwhite infrad vio cara Phoogn Eg Re oe  5265 96 Evtt JH, Esbar DE, Via R, Niega R, Davis MR 1 1 Air vio systems f agrcultura asse ment Remoe  EirO 352312 97 Ev JH, Nix R 1985 ase c vo imgery A tenta me s ng to or range magement. Phogra ng Reoe Se 5 1 67579 98 Everitt J, Rcardson AJ. 1987 Can opy etae o seven rangand pant scies with vrabe ea pubeence Phoogra Eng Reoe  53 157175 99 Ferguson H, Esli  Aa K 1973 Canopy temratur o bey as u eed b mpoga cactests Ag . 65458 100 ilajdc N, Sutton TB. 19 Optmum spng size for determnng dfferent aspcts of Alteia blotc of appe cau b Alera al Pla Dis 787 1924 101 Fors GA, Jeger MJ. 1987 Fact affng e estmaton of dse in testy n smuated pt suctures J lan Di ro 94 1 1  102 Fo S 986 Agrutua reac with RC araft. adbou Weekblad 413032 103 Fo S. 1 Asssnt of crop sss codtons usng ow attu r ial lor inra ptogra a c puter possng. S Re 10  182 104 oh  1 4 Estimaon of crop water stress n soan a weat usng ow attude a inrared teometr and co inred phogrph. Se Re 34 pp 1 7484 105 Fouc S, Byn W 19 Re

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mey pioted arcra  ow atu aer sueillae n arcuu. S Ref 93 pp 277-85 106 ouc  Byn NW 14 Low alttude survellce of agricutur crops usng ixv motey pi  oe a. S Ref  . 31 107 rcksen TS, Sey JM 19 Re aton of visibe and physioica foli inuy fr oone exp in dwd ree sces. Phopahoog :1: 137 l  amon JA, Pee J, Fied CB 1992 A narrow-waveband sptal inx tht track dual changes in ptosynic

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eciency Reoe Se Eniro 1  354 ao BC, tz AFH 14 Eaction of dry leaf scta feas fom e tae sctra of green vegation. Re e es EI i 476974 Gaman W, Cdes R. 19 Efft of leaf pucee of ura auran aa on li rea Bo G 130 1 5862 Gaman HW, Cardenas  1973 Lght reeace by leaets of snt, n mal, and glaous soyn les. gron  658338 Gam HW, Escob DE, Bowen  1983 A vdeo system to detrate intertons o arinfred adiaton wh plant leaves. Reo  Eiron 33636 Gama W Esc DE, odgue . 1973 Discrimnaon among plnt nutrient deciences w retan measumens Repintd in or r  Photograph n 'he Pla enes ad Relaed elds: A Cpendi 1713  GJ Edwas, 19  1 1 2-6 als Chur, VA Am. S hoogramm Remote Sens. 3 pp. am HW Menges RM Escobar DE, Ev , Bowen L 19 Pu scence afts sctra a imagey of sverlaf sunower (Heliah argo phlls Wed Si 264370 erten DM Wie MY 19 Vido mage anass o gng and yed oss n win!r weat atie to  rot. Phopaholog 74872 erten DM, Wese M 1987 Mcr comtersssted vdeo mage analysis o gng n wnter wa Phoo ga Eg Ree S 38388 Glligan CA. 1980 Siz d sa of smplng uts for estmatng incn o sap eesp (Rhizooia erealis n plo o weat.  Ag i 99461



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5th /  Phys M Sig Remote Se orvel  7226.

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REMOT SENSING ND IMGE NSIS NASA ae ien p in s

 f Miion o Pla Er. S Re  88  Hnt  Jr 1991. Airbr reme se

ng f cany we hcess caled fm leafsoe  . 1 Reo ns. 12:39 . I B, acksn RD, Pinte PJ J Reginat  Haeld JL. 1981. N mazn e sessgry o envimentl vability. Agr. Meleoro

g . r y o . l s n w o e e i v s u e r l l a a u n n o s n r a . e p w r o w F w . 4 m 1 / o r 7 f 2 d / e 1 d 0 a n o o l n a w n a o r a D . P 8 o 2 D 5 - l 9 a 8 r e 4 : d 3 e 3 . F 5 a c 9 i 9 g 1 l o . l o o n h c t e a T p o e t d y a h d P i . s v r e e v i R . n u U n y n b A

1 5.

57

58.

159.

a watr dincis in sgca nde vabe diness Remoe e Env  1

 196:15

24-6 66 Jon R, Pin PJ Jr, o , Reginato  1 979 Whea scr e-

'oo� 2 5 � S, Wale  J, Be MW, Ellis

155

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16.

151 I B, Regina RJ, Hateld JL, Walk G, acksn  Pint PJ J  A generzatn f he srsegeey ce f yield predicin o ae a disiy of ogr.

5.

biic and ioic pan sress.  Rev Phyloh. 24267 16 kn RD, dso  Reginat  Pnr PJ r. 1981. Canop r  a crop wate stss i ica. Wer

55

50. I B, kn RD, eginat RJ. 77 Remte sensing f p yelds.

153.

19

GW, Hnn E. 1987 Vdeo Micos o New Yrk: Plenm 5 pp Jkn HR. 1. Deection of pant ase sypo J  Phlogr As 32458 kn HR, Hgn WA Wallen YR Phils LE, ner J. 1971. Potato late bli inensi levels  deened by micensiote sdies of flcooaa ptogas   o o Asso 91016 kn HR Wlen YR. 1970. Com parisn of oica denity diffeences in aia pographs ween plant can py an ls with varin suface mois  J Bo Phoogr. As 4747 kn HR, Wallen YR 9 Mi  renitoer mearemen of qen a phogap o ed a infe with bcterial blight. hopholog 659618 kn H Wallen YR 976  epiphytoly f late blight of poato mir by seqential col infrared aia phogrhy.  App. Phlogr. En 220712 Jkn H Wallen YR, Dwnr  19. Analysis and electonic area measmen of complex arial ph gahic imas.  App Photogr Eg : 0 1 6 Jkn RD 1982. Canopy temrature and cp wae sess Ad Irrg. 4-

5 . Jkn D. 1983. Stra indices in n-sace m S Eviro 14 1 161 Jkn RD. 198 Assessing moiture

st in whe with handheld rdiomeer PI 56 842 162 Jkn RD. 19 Remote sensi of

kn RD Pine PJ J 1986. a sponse of archicuraly diff wat anopies Rmo Sns Envon

ectance, interaction ewn c congration sn lvaion a aimth ale App Opt 373 67. kn D, ine  , egino  Ido S. 1 98 Handld rdiometry. Agric Re  We. e UD  Ed dm 1916 16 Jcn , Reginato  o S 1977. Wheat canopy emrat A practical tool f evalaing wae requirmn Wer Resor Res 166

6. kn , Slater PN ne  r. 9 Discimition f growth and waer re in wat b vaou vegetation indces thrgh ce d tubid amosphs. Rmo S Envin 1 17-8

1

Jne WC. 97. A manal of assessment ey f pant diseas.  Dep Agc. ubl 148197 1 7 1  Johnson   Fuors e

oop fo meda ad eomea dgc, pp  Diss. .

hys, I Tec, Lun nv, Swen

172 Johnon GW, aley  Bck  Matyac CA 9. Studies of diseased

r tisue ig ncler magnetic e nane imaging Phyoogy 76 7 7 Kaln E 8 kk p. 1  Unv r Uppaa 174 Kasi  14 Minplatfoini mat aeia oograpy S e. , 67 1

17

Kauth  Thomas GS 1976 The teled cap  A graic decption of t scal-mal dvlopn  ari cutual co  sn b Landsat P Symp Mche Prng ofRemey eed D, pp 4- AR, Purdue



Unv, Wet Lafayette IN auy  ih A  Chlo phluenz und Koensuresimilation I. Mieilng: ds ozenzerhaltn gr aen  hm Z 474

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NON

77 Kenny BW. 1986 Altrtion of lf als d cicadan leaf movemes in sdling suowes ifected by Pedo mon ee Phoho 76 1085-86 78 Kele  E DE Evi JH. 1992 Iig in nttability dif fenc wn lo iad tog ay a co nfred vio da S Ref 10 . 19-6 179 Khak VI Morgun VN Rk BN Willis DL. 19 Chloyll u ee a delayed uoce  tenti tls in me nng A eion of so ts of re in mrative analysis ee e Env 479810 180 Kimes OS Makham BL Tuck CJ McMy . 1981 emal ela tio wn sra sne and ag ic varabs of a c ca Reme n Envr 11401-11 181 Kin CR. 1992 Reme sensin  a cany mash ograhy and viogray in plt iens. See Ref. 0, pp 878 18 King D. 14 Digia fa cameras: the xt geneation of low ct emot sens. See Ref. 4  92 18 King D Wash  Ciuffra F. 1992 Eevaon dnation usng aire digital fre camera imagery. See Ref 10 p. 147-57 184 Klosson  Kause GH. 1981 Frzing injury in odcimted and unrden spinnach eaves  Effts of freezing on chlorhyll uosn a light scaerng eactio Pl 151752 185 Knpling EB 7 Physica and physi oogica bis f differees in ra  ahy a das pans. S Ref 11  8-2 186 Knping EB. 1970 Physical and hysioogica basis for t rtan of vis ibe d neinfrred adtion from vegetation. Remoe Se Evr 1  1559 187 Kokko EG Co RL Kozub GC L B 1 Quanication by image analy sis of subrwn inne discoration in wat caued by coon rt t Phoho 897 1 188 Kraicek V Vva M. 14 Lasinduc luorcee sctra of pnt Remoe n Envron 4751-54 189 Kr z J 1988 Mesuring pnt disee In xrmel Tes n Pl Dee Emolo ed J Kra J Rem pp 550 New York: Sprnger 90 Lai L. 994 Qunticati of foliar dis using te our opute iage anyis PhYOholo 1

191 Lee . 1989 Aerial oghy f e detion of sl  C  P Phol 111776 192 Lichenaler HK  1988 Alc  of Chlohll lorecee n Phoohe Ree S Ph olo Hdrolo nd Reoe Senn odon Kluwe  . 19 ichtnte HK 988 In vivo cl ophyll fuoscence  a tl f s dettion in plan.  Ref. 192 . 12942 194 Lichnhale HK. 1988 Re  ing of chooyll usn n earay and in ersrial vegetaion An intrucion. See Ref 192 . 8797 195 Lichnhae HK Bauhmma C Rinle U Schmuc G 19 Ali cai of chohyl uoree n ecoysioogy. Rd Envro o h 2529708 196 Lichnhale HK Hak R Rle U. 19  chohyll ee ao F670 in leaves of iffern ho rpll ontent o R 5 2998 197 Lichtenhale HK Lang M St F 1991 Nature and vati of bue flu ree sta of testrial plan.   e e e   pp. 83 Helsinki Eso Finland 198 Lichtenthale HK ang M St F. 1991 Leied blue usn a red chlorhy uoresn signa tur of diffently igmen leas See Ref. 12 . 7270 199 Lichtenae HK Rindle U 1988 The re of choryl usn in the dtection of sress nditions in  CC C  A C 19

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00 Lichenhaer HK Sto F. 19 La sinduced chorophyll uesn a bue ureence of gren vegeta tion Pr h RL Sm To loe p 21 EARSeL BoulognBillancour 201 Lichtehae HK St F Lg M 1992  ntur of t different laindud ursn signture of   EARSeL Ad Remoe    202 202 Liesand TM Meisner DM French DW hnsson  1981 Evuation of dgitl phographc enhanent f Dutch elm dase tcti Phoo rm E Ree Seil 48 158192 20 Liend  Sly ML Listrom M Goldbltt M Jnson W Meis e DE ' 1 98  Envirnent a s rl data relating to sunowe crop

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condti aessment RSL Rep. 83:2:1 47 Remote Sens La, Univ Minn St Paul Linw SE 983 Estmating ia sevety of single pl hytot ogy 737681 Linw SE. Aen GL 19 Micromper meuements of pathogen ijy to ws d S . (Sul )38 Linw SE. We  198 Use of digit deo image alysis in plt ds sssn hyoo 71 890 Liw SE. ebb  983 Qnti cation of foli plant se symp to by momputergitiz video image aalysis hytopathology 3 52 Lod D. Des dins  D PA 9 Sunagle effs on  red and nr ifred fltanc of  diffent r anies C 1 Ree SeI. 14:455 Lu G. Paloscia S. Pamloi P 9 Mirowave radiomtry f monitoring agicult cs See Ref 3a.  30853 Mad LV 19 uantication of dise progessio r. Ec. 2159 76 Madn V 19 Saistical analyss a mprso of disse pogess curves I ant Dea pmoogy e K Leond.  Fry. pp 5 New York: Macmilla Madn LV 15 Modellig yield losses t the eld scale . 6 I ongr. MOrea  a/� 1 la aol 16: prs Madn V. Ke K. oue  9 Exriment design f determination of yield lses de to m dwf m saic vir hytothoogy 7489 Mathus TJ. Andrieu B. Dson  Jggd KW. Steven M 3 Caidate high sctral resolution ined inds f op cover Reme SeI. ni� 46:22 Manr  Cr GR 196 Aea phogrphic meths of tato dse detection Mae Agr. Ep. S Bll. 646 pp 114 Manr E. Cr G 1982 U of rabe vdap f era iad detection of tato disees a Dis.  Mattsso 1 94 lmic Jonaton n nghtrerd a photogaphy wh speal ega o egisaio ade in retroreected  Lu Ui Naugerska Is  Rp N No 2356

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522

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245.

24. 247.

8 49

250.

Neblette CB 192 Aeial photay f the study of plant diseases. oto Er Mg. 8:46 Neblette CB. 1928 Aiple oa py for pla disea suves or Mg 59:75 Nilon HE 19 Stdes o f  and ft ro dseases of cals ad grss I On rista to poou g n Sacc brvgk A/r 3 80 Nilsson H 1980 Remote nsing and image peing f disee sess ment rot Eo 2214 Nilsso H 1980 Appcaton of emte sensing and image analysis at mac coic and microopic levels i plant pathology. See Ref.  pp.  Nsson  1983 Remoe nng o vegetai amage  Pla pahology acs and cr ls asssnt.

r. RNR Symp. Appl. Reote Se Resour. Mge, tte p 38102

alls Church, VA: Am  Phogramm Reme  25. Nilsson HE. 983. emratursteging hos pantsnd av ko art av stimsjka. Vxtskydotiser 47:8 252. Nilsson H 1984 Remot sing of 6ro bry d by by s dase. Vxtsdpp ork 36:

149 253 Nilon H 985. Remoe nsing of oil se ra ifec by Serotn stem t a Veiumilt Vt kydrpp ordbruk 33:33 254 Nilsson H 985. Remote nsing of 2 by  by  b deae. Vskyddrpp orruk 341 01 255. Nson H 986. Rete seg in plt pthology: infoati on meth  dlomnt kpp ordbruk 39951 I Seh 256 Nilsson H. 987 ments on handheld radiomty and Rtrm gaphy of winte wheat i eld plot eent Vtddspp. ordbr 8 257 Nilsson HE. 1   . Handheld radiome and Rthogaphy of plant dseses in fied pot exrments. Int  Remoe Ses  2545-57 258. Nilsson H. 15 Remote ing and imae alysis methods in pytopathomet. See Ref. 212 259 Nilsson HE Alness K. 199 Handheld adiometry of eld epints in  tat damaged by a rbd ad by ate gh  o.  260 Nilsson H Bamstorp A. 4. Rem sening of ld eime in sug  Beren Orn Ser Be

M SESIG AD IMAGE AALSIS

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aes Cenaening 57131-35. In Swedis Nilss  onsson L 988. Reme sensing of plnt dises in eld plot epns. Vxsks 10k 4922 Nilss , Linr H. 987 Rem sensin o w and aley in a eld pl exment with ffent levels of nen flzaon and igi. Vsks. 10k 451-26 Nilss , Linr H 987 Rtr mrapy of ny temratus of wat a ley at diffent nien feilizaon and rg Vtsky sa. 10k 43:1-49 Nn LD. 988 e pnomena o seneee and agi n n n Pn ed LD Nn C Leold, pp  -50. New York caic. 526 pp Nowling S ueller  4.  low ct mulsperal arr vd mage system  vegettion ontong on range and st lans. Se Re.   18 Nutr W r 98 Detcion of pnt dase gadiens using a a-ld multiscl radioeer PhYtgy 77:3 Nuttr F Jr 1989. Detton and msement o plant disse gradent in peut with multisal radiometer Phtathgy 799583 Nuttr F r 10. Ree seng a age als f crop loss ssess ent In C ss ssesse  Re pp 93105. Manla The Phlpps In Ri R t Nutter FW Jr 13. DI PRO A coputer a for trnng of vsual dise asssment Demot tion  h IS Conr Monal Can ada Nuttr F r, Aldan SC. 1987. U of late leafst dss graents to evalute se asssent sches  aury prsion reuton and se Phytathgy 77:  700 Nutter F Jr Cunfer BM. 1988 Quan ticaton o bley yield loss caused by Rhnchs seas usg vsual vesus remote nsng aessment et s Phytthgy 78: 530 Nutter F r Gleson  enco H Csta NC 199 Eft of vsual rete seng and ge aalss  ssent mes on intrarter and n er-raer lbly esates in the dollar st - ntgrass ptyste Phytathgy 8 : 1 182 Nutter  r Gleson  eno H Chstias NC. 13. Assessng the ac

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cacy, intra-rar ability, d in r-rater liaility ofdise sssmen sysems Phtthgy 8382 Nutter FW r, Lll  Bnman TB 19. Utlizion o a mus raoeer o evalua fngcde e ccy to control late le st in anu. Phytathgy 02� Nutr  Jr, tll  eon  1985 Use o a lowct, musa radomter to estiat yield lo in  nuts caud by late leasp (ec sU nat) Phh 75502 Nutter F Jr Littwiller D. 13 L FLF.PRO - A copuerz ise assent training nd evaluaion pr gam or oli disea of afala. Dem onsation a  S C, onl, Canad Nutter FW Jr, Peson D 19 Yield los eling: oleran  he. Phytathgy 74:872-73 Nutter  Jr, Schultz M 1995 Im provng t accuracy a cision o ias essets slct o meh s a u of cpur-aid tainng progams.  1 P Pat. 6:n pss Nuter  Jr, Wawitlkt O 989 DI.PRO  A pur prra or evaluation and ipving a n's ailty to assess dsee oio Phytthgy 7935 OBren RD, v Bggen AHC. 1992 Accuracy precision a oli to yild lo of se severty sca  c r o lettuce htth 82:9 Olson CE Jr. 19. Ely m det ton of psologc sss in st stands. S Ref 1 13 pp. 173�8 Osmond CB Bey  Balacan S BcenOsmd C, Daley PF, Hg son RAJ 19 Pental coquenc of vrus nction for sdesun ccli on n leaves. t. cta 1032629 Osvad H 1959 Ak nttte Svek Leratur B Stkolm 596 pp OToole JC Hatfeld JL 1983. Et o wd on t crop water sss iex rved by nred hemoy. gn 1 7:81 117 Oen L I Raf TB, Sella RG Hb E 1 94. Vsble yrsral iagng for airr envrnmenl sensg See Re  :284-95 Palcg LG, spnal 0 eds 1981 T Phsgy a hest f Dght Resste  Pas. Sydney: Acec 492 pp Pedeson D 1984. Multisal rdi-

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NHSSON ometry ing a 1 bit anaogtigia onr inrfa wit a pable mi crputer Phytopahoogy 74872 Pn YD 1986. imation of e cy of fi fungicides on barley by mutisca radie Phto 76957 Pn  1 986. Stradieic ading of ey nies grown fm fungc trted se Phytothoogy 761 147 Pn YD iectn G 1 98 A owt compt ta auisition sys tem for rding visibe and infrared f fm be o ci. S Ref 337 pp 717 Pedeon YD Gudmestad N 19. Euaion of foi disees of barey w musa sens P Am Phytopaho  4 149 Pederson YD Nuer W Jr 1 98 Low c rtable multistra rioer f assnt of ons a seeriy of fi diase of bey P PE t . pt  36:12 Pennycer SP Schaen  Shap EL ands D 1982. Sctra csi cation of wa infected with barley yellow dwarf and sr s Phyto patho 721 Penls J Gamon JA Fredeen AL Merino J ied CB 19 Reance inds assiaed wit pysiological canes n nn and waterlied sunower eaves Rete eI. Eli. 48:136 Pery CR Lauechlaer  19 utona eqivenc o sra veetaion indic Remote  Ei 14:12 Deleted in f Peeson DL A D Mason PA Cd DH Swrg N et a. 1 988. Remoe sensing of fest cy and eaf bi cica contens Rete eI. El. 481 Peerson DL Runnng SW. 1989. Applicatis in fs science a manage ment n heoy a Appitios o ptic Remote sig ed. G Asrar pp. 42973. ew Yk Wiley Pfeffer PE Gerioicz WV. 1989 Na Magti Reoae  Agi te oca Raon, FL R. 441 pp. Phils L Wallen YR. 19. IRcolor f cr disese idenicaio. Phog. g. 55 1 1 1625 Pils L Wallen YR. 1970.  use of or inrared poogray in esiating ls in whe an uction n Hn County. Ono   a o 54 Pinr PJ Jr. 1986. fec of dew on

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EM ENING AND IMAGE ANALYI blac disas. Pla D R 59 6

37 Schrir U Bey JA. 1977 Heain

duc cnges of chorhyll fluores cenc in int eavs clad wih damage of he posntic apparaus Paa 6-8 31 Sc  Teng PS Rlfs AP. 195 The re of wa leaves in grain yield a l t lses. Phtohog 75


1 9 Sarp, P CR Scn A B wrigh  Sas D e al. 95

oning ca s development wi a sral radomter Phtotl-

ogy 759�9

0 Sewd R, B CC Hr MR, Zid K 198 llusions in visual aessmen of t oopor eaf s of orchds. Phtotho 7373 77 32. Sine J Jr, Co JC 13 Digita

ima analysis sysm for determining tissb immuay resuts for rat sunting disse of sugarca. P

D 7751 13  Shes  Berg R Smih DH, Rp J 197 Reliability of dsea

assessment predures: A ca study wih la leafs of anut. OUagex

44 1 33 Sla PN, Jacson R 9 Atmos-

pherc effecs on radiaion eced fom soil a vegeaion as measurd by orbial seors using various scannng dito. Al Ot  9" 34 Smillie  Hetringt SE. 93 Ss oleran and sessinduc injur in crop plts measurd y cl rhyll uore in vivo. Plt Phsol 7:

35 Smi RCG, Heriage AD, Stapr , B HD 19 Eff of s r (Pua stros W.) and irriga-

ion on the yield an foliage temratr of wat. Feld Cros Res 4:395 36 Spr A, Smih MAL. 99 Image anysis mpic measmes f iue water status and otr etermiions Agro. J.  9 0 3 Steven D Cl A, e 19 Alcatos o Remote esg  Agr ltre. n Bttt  p

37 Sto F Lg  Lichtehaler HK 994 B ue, green, and rd uesnce

emiion signatrs of green, etiol, a wte leavs. Remotees Er

767 3 Stonse . 14 Assessment of An-

dean an ias using visua keys.

Plat PathoL 43597 39 Strmrg A, Bia S, Nilon HE. 994 ced systemc resswce



to tato t blight ..  sis. Sw. Uv Ac  Uppa E  Phtothol. Sumitd

330 SrOmrg A, Nilsson H Brisham S. 13 nced systemc sisa to

tato lae lig in a eld exment sued wth vsu ssss a  moe snsing. Absr. th PP Cgr• Mtreal p  5 331 Sue GW Bs R Stu CA. 19 ICAS quantication of nuen sss in cutu crs. S Ref 9  . 1097 33 Stue GW Stu CA. 9 Qni

cai of eld crop sr ar using vidaphy. See Ref. 93 . 8898 333. Sua N, Moan CN. 14 ar indud r cloropyll usn sgnaus  nuren sress ica in rice lans. Remote e. Er. 47

4550 334 anner CB. 3. Plan temraus. AgI J 55111 335 aus  Ezeel WN Nebee CB. 99 Aila otography in  study of coton ro . Phtothog 19109 336 eng PS ed 97 Cro oss Assessme Wd Pest Maagemet. St Pau, N: Am Phyotol. S. 70  33 eng  rupa V  9 Assss-

ment of lses wich consrain prucion and cro impvmen in agricultr and fsr. Pr. EC takma Commemote . Cro oss As-

ssset. Ms Pbl  St Pa Agrc

Exp Stn., Univ inn. 37 pp. 8 Tomason A, Bee CW Jackson B, Mailanr MP 994 iffeniaing ttomand ree scies with mul vderay. Photogmm.

Eg. Ree . 605559 339 omsen A. 992. timaion of leaf-

areainx (LAI from raiation me mens. dsskr Plaea. eal-

sere Beret S97 340 Thunen JG, Wdy LM. 14 New

sens cology fo acung ysctral image. See Ref. 60  :33 1  1alka M Wite N Erington R Fricr M. 4. Confal excittion ratio imaging of Ca+ and + dung bluelight espon n ants  R icc c. 936  odd , Kommedl T 19 mage

alysis and visual estimas for evalu ating diee reactis of corn to Fusari sta t. Pla Ds 78878 343 o SW off RM Milchus  993 Comaris of fo vegetation indices f estimatig aoveground biomas on gred raela. Pr APR·ACM AI CIV. Ne Or

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Baenzige H Dixon RG. 1977 An el tonicay snd aerial phoapc tec ie to msure wint injy in aafa.  J Pln S. 57:7-51 Wayne MT Cpl  198 S ping s f deenng seve ity of alfafa leaf st dises Phopholog 77:1572 Wer GE, Jg E. 1991 E in dias sesment sury Pho holog 81:238 Wessman CA. 19 Evaluai of can opy bihemist. In m Sng o Biosph FUioing e RJ H HA My pp. 1 3556 New Yk Springe Wessman CA,  JO, Peten DL, Melio JM. 1988 Remote nsi of canopy cmisry and nen cycing in temrate fost ecystes. N 335: 154-56 Wessman CA  JO, Peten DL, Melio JM 988 Folia alysis ing a inrad ae sp n J Fo. Res. 8:1 1 Whitmy G Muphy FJ. 1973 Ultra low aeial appication f a ado conolled mel aipane P N Mosq Een. Assoc. 16:445 Wiegand CL Eob DE Evei JH. 992 Comprison of vegetation indic from aial vid and andeld iomee oevaios f we ad c See Ref 0 pp. 9809 Wiegand C Esc DE ingle SE. 19 Detting gowt 'varaton and salt stress in sgarane using vidgaphy S Ref 34 pp. 18 Wiegnd C Namken N. 16 Inu ees of pa moist st, solr raiation, a r temratu on cotton leaf temrature. Ag J 58:58286 Wiegand C, Ras JO Eo DE, Evi JH. 992 Photographic and viraphic oevatio f detemning and mapping te rese of cotton to i sainiy Rmo  Envio 49:2224 Wignd C Richdson AJ, Escobr DE Gerrma AH. 1991 Vegettion inces in cr asssments. . m Ss. Evio. 3505-19 Wiegand CL S W J Eo DE. 9 Comparison of mutistal viraphy a color infred ptog rapy versus crop ye  Ref. 1 p 2347 Wiliamn B Gdan BA Cek JA 992 Nuce magntic renan NR microimaging of rining ed raspry fits. ew Pol. 129:2128 Wiliamn B Gman BA Cek J. 13 The sructure of mature g

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