Remote Sens 2012, 4, 180-193; doi:10.3390/rs4010180 Article OPEN ACCESS Remote Sensing ISSN 2072-4292 www.mdpi.com/journl/remotesensing Use of Vriogrm Prmeters in Anlysis of Hyperspectrl Imging Dt Acquired from Dul-Stressed Crop Leves Christin Nnsen 1,2 1 2 Texs AgriLife Reserch, Texs A&M System, 1102 Est FM 1294, Lubbock, TX 79403, USA The UWA Institute of Agriculture, School of Animl Biology, The University of Western Austrli, 35 Stirling Highwy, Crwley, Perth, WA 6009, Austrli; E-Mil: io@uw.edu.u; Tel.: +61-8-6488-4717; Fx: +61-8-6488-7354 Received: 25 October 2011; in revised form: 10 Jnury 2012 / Accepted: 10 Jnury 2012 / Published: 11 Jnury 2012 Abstrct: A detiled introduction to vriogrm nlysis of reflectnce dt is provided, nd vriogrm prmeters (nugget, sill, nd rnge vlues) were exmined s possible indictors of biotic (irrigtion regime) nd biotic (spider mite infesttion) stressors. Reflectnce dt ws cquired from 2 mize hybrids (Ze mys L.) t multiple time points in 2 dt sets (229 hyperspectrl imges), nd dt from 160 individul spectrl bnds in the spectrum from 405 to 907 nm were nlyzed. Bsed on 480 nlyses of vrince (160 spectrl bnds 3 vriogrm prmeters), it ws seen tht most of the combintions of spectrl bnds nd vriogrm prmeters were unsuitble s stress indictors minly becuse of significnt difference between the 2 dt sets. However, severl combintions of spectrl bnds nd vriogrm prmeters (especilly nugget vlues) could be considered unique indictors of either biotic or biotic stress. Furthermore, nugget vlues t 683 nd 775 nm responded significntly to biotic stress, nd nugget vlues t 731 nm nd rnge vlues t 715 nm responded significntly to biotic stress. Bsed on qulittive chrcteriztion of ctul hyperspectrl imges, it ws seen tht even subtle chnges in sptil ptterns of reflectnce vlues cn elicit severl-fold chnges in vriogrm prmeters despite non-significnt chnges in verge nd medin reflectnce vlues nd in width of 95% confidence limits. Such scttered stress expression is in ccordnce with documented within-lef vrition in both minerl content nd chlorophyll concentrtion nd therefore supports the need for reflectnce-bsed stress detection t high sptil resolution (mny hyperspectrl reflectnce profiles cquired from single lef) nd my be used to explin or chrcterize within-lef forging ptterns of herbivorous rthropods.
Remote Sens. 2012, 4 181 Keywords: hyperspectrl imging; crop stress; vriogrm nlysis; mize; drought; spider mites 1. Introduction There re numerous studies of stress detection in crop leves bsed on reflectnce dt cquired with either single sensor devices or imging devices, including: biotic stress [1 4], slinity stress [5], nutrient deficiency [6], nd drought stress [3,7]. Crter nd Knpp [8] provided thorough review of reflectnce bsed detection of biotic nd biotic stressors (including dehydrtion, flooding, freezing, ozone, herbicides, competition, disese, insects, nd deficiencies in ectomycorrhizl development nd N fertiliztion) within the 400 850 nm wvelength rnge when imposed on wide rnge of plnt species (grsses, conifers, nd deciduous trees). Irrespectively of biotic or biotic stressor, Crter nd Knpp [8] concluded tht in most studies there ppers to be n increse in reflectnce in response to plnt stress, nd this increse is generlly most noticeble ner the red edge t 700 nm. A possible explntion for such increse in reflectnce is tht stressors prtilly compromise the photosynthetic efficiency of the plnt, so comprtively more rdiometric energy is reflected bck to the tmosphere thn from non-stressed plnt. If such increse in lef reflectnce occurs in response to given stressor, then follow-up question is whether it is due to generl reflectnce increse cross given lef (in ll pixels) or whether it is ssocited with proportionlly higher reflectnce in scttered points within ech lef? Severl studies hve demonstrted within-lef vrition in distribution of minerls [9] nd chlorophyll [10], so it seems resonble to ssume tht there is sptil vribility within lef in terms of expression of stress response. In ddition to importnt questions bout the sptil distribution of stress expression within leves, it is lso importnt to ddress spectrl spect of the findings by Crter nd Knpp [8]. From n cdemic stndpoint, it is obviously quite interesting tht plnts tend to hve quse-universl stress reflectnce response ner 700 nm, but it mens tht prcticl pplictions of reflectnce bsed stress detection systems my be limited, unless more unique reflectnce fetures cn be ssocited with different biotic nd biotic stressors. Tht is, under rel-world/commercil conditions crop plnts will likely be dversely ffected by severl stressors simultneously, nd/or there my be importnt interctions between stressors. Thus, specific stress detection tools re needed, so tht different stressors cn be detected nd quntified independently. For instnce, it is widely known tht crops become more susceptible to spider mite (Acri: Tetrnychide) infesttions (exmple of biotic stressor), when crops re grown under drought stressed conditions (cotton, Gossypium spp. [11], sorghum, Sorghum bicolor (L.) Moench [12], nd mize [13 15]). This ssocition between spider mites nd drought stress suggests tht erly detection of drought stress cn possibly serve 2 complementry purposes: (1) to optimize irrigtion regimes, nd (2) lert growers bout when pro-ctive miticide pplictions my be wrrnted. It is importnt to emphsize tht reflectnce bsed detection of crop stress is minly of interest if it cn be used to detect emerging dverse effects of biotic nd/or biotoc stressors, before symptoms become obvious to the Humn eye. In other words, the true potentil of reflectnce bsed detection is ssocited with n bility to detect subtle/emerging stress levels, so tht mngement prctices cn be djusted before significnt crop
Remote Sens. 2012, 4 182 yield losses hve occurred. In ddition, severl studies hve described reflectnce bsed detection of emerging spider mite infesttions [1,3,4]. Recently, use of vriogrm prmeters hs been demonstrted s well-suited for dul-detection of biotic nd biotic stress in crop plnts [3,4,16]. However, better insight into the reltionship between reflectnce vlues nd vriogrm prmeters is needed in order to interpret nd discuss vriogrm prmeters s stress indictors in n gro-ecologicl context nd to understnd within-lef stress expression. The min purpose of this study ws 3-fold: (1) provide detiled theoreticl description of vriogrm nlysis when pplied to reflectnce dt from hyperspectrl imges, (2) identify combintions of spectrl rnges between 405 nd 907 nm nd vriogrm prmeters, which my be considered suitble for detection of biotic (experimentl irrigtion regimes) nd biotic [spider mites (Acri: Tetrnychide)] stressors, nd (3) bsed on descriptive sttistics nd visuliztion of imging dt, chrcterize spectrl responses to biotic nd biotic stressors. Thus, this study provides detiled insight into the reltionships between stressors effect on reflectnce vlues within crop leves nd between reflectnce vlues nd estimted vriogrm prmeters. Due to the interest in detection nd chrcteriztion of subtle/emerging stress levels, mize plnts were subjected to firly modest levels of biotic nd biotic stress levels. 2. Vriogrm Anlysis: A Theoreticl Bckground In the 1930 s, geosttistics were conceptully proposed by Dr. Krige s n pproch to optimize gold ore mining in Southern Afric, nd Dr. Mtheron developed the mthemticl models of this concept in the 1960 s nd 1970 s [17]. Tody with geogrphic informtion systems (GIS) being pplied to epidemiologicl, ecologicl, socio-economic, ocenogrphic, meteorologicl nd mny other types of studies, geosttistics s discipline is widely ccepted s being 1 of the most powerful nd robust pproches to sptil dt nlysis. For more exhustive descriptions of vriogrm nlysis, it is recommended to consult Armstrong [17] nd Isks nd Srivstv [18]. The fundmentl ssumption of geosttistics is tht difference (i.e., semi-vrince or co-vrince) in reflectnce vlues between points within the imge cube is correlted with the distnce between pixels. Furthermore, it is ssumed possible to develop model tht describes the sptil structure or reltionship between distnce between pixels nd vrince of reflectnce vlues. This type of sptil structure nlysis cn be conducted with reflectnce dt from hyperspectrl imges, becuse ech pixel (hyperspectrl profile) is in grid with set of x- nd y-coordintes within ech imge cube. Importntly, trditionl pplictions of geosttistics involve dt sets where only restricted number of point observtions re known (i.e., drilling holes in n re with high likelihood of gold deposits), nd most commonly 1 of the principl objectives ssocited with geosttisticl nlyses is directly linked to predictions of counts t unsmpled loctions (i.e., to predict the highest likelihood of rich gold deposits). Regrding hyperspectrl imges, the entire dt universe is known, tht is, ctul reflectnce vlues re vilble from ll geogrphic positions (pixels), so the objective is not to predict vlues t unsmpled loctions but to chrcterize their sptil structure nd use the sptil structure s n indictor of the trget object, in this cse stress expression within mize leves. In other words, it is ssumed tht reflectnce dt cquired from different trget objects (for instnce, crop leves from plnts subjected to different stress levels) lso will hve different sptil structures. A semi-vriogrm nlysis
Remote Sens. 2012, 4 183 chrcterizes the reltionship between distnce between pired observtions nd the semi-vrince (vrince divided by 2) of observtions of these pired observtions (Figure 1()). The sptil structure of given dt set is either rndom or non-rndom. Rndom, or lck of sptil dependence, mens tht the vrince ssocited with reflectnce vlues within n imge is independent of the distnce between pixels. The curve fit in the semi-vriogrm is stright line denoted pure nugget vriogrm [19]. A dt set with non-rndom sptil structure, shows sptil dependence [19,20] or sptil continuity [18]. Non-rndom, sptil dependence mong observtions points my follow n symptotic curve tht grdully increses with lg distnce up to certin point by which the vrince of counts levels off nd becomes rndom, which is the distnce by which point observtions (i.e., reflectnce vlues in single spectrl bnd) re no longer sptilly correlted (Figure 1()). As prt of developing the vriogrm, regression curve fit is used to model the sptil structure nd estimte 3 stndrd prmeters: nugget, rnge, nd sill (Figure 1()). The nugget represents n estimte of the semi-vrince or co-vrince between observtions collected t zero lg distnce prt or 2 reflectnce vlues from the sme pixel. Theoreticlly the nugget should be zero for semi-vrince nd infinitely high for co-vrince, nd it equls the noise or stochsticity in the dt set. The sill is n estimte of the totl vrince explined by the sptil structure nlysis. The rnge is n estimte of the mximum distnce t which point observtions re sptilly correlted, beyond this lg distnce intervl point observtions re to be considered sptilly uncorrelted. Two regression fits re commonly used in regression fits of vriogrm dt: 3 D c F v b 1 e (1) is n exponentil curve fit [18], in which denotes the nugget, b the sill, nd c the rnge. 3 3D D F v b 3 (2) 2c 2c is n sphericl curve fit [18], in which denotes the nugget, b the sill, nd c the rnge. The procedures of sptil structure nlysis pplied to hyperspectrl imging dt re best explined with n exmple, in this cse reflectnce vlues from mize lef in single spectrl bnd nd with 100 pixels rrnged in 10 by 10 grid pttern (Figure 1(b)). Accordingly, the distnce between pired pixels rnges from 1 to 14.1, nd the totl number of pired distnces (N) is 4,950 (Eqution (3)). N N 1 P (3) 2 The 4,950 distnce combintions re grouped into fixed lg distnce intervls, which re projected long the x-xis in vriogrm, nd the y-xis in vriogrm depicts either the verge semi-vrince or co-vrince for ech lg distnce intervl. Obviously, there re not equl numbers of distnce pirs for ll lg distnce intervls, nd Figure 1(c) shows semi-vrince or co-vrince of the dt in Figure 1(b) when divided into 13 lg distnce intervls. It is seen tht there re only 2 distnce pirs for the longest lg distnce intervl, while there were 850 pirs for lg distnce = 4. Averge semi-vrince nd co-vrince estimtes for the first 9 lg distnce intervls were bsed on 340 850 pirs, while estimtes for the lst 4 lg distnce intervls were bsed on <100 pirs nd therefore more errtic. Thus, it cn be rgued tht these lg distnce intervls should be excluded s they re bsed on
Remote Sens. 2012, 4 184 comprtively less dt thn the initil 9 estimtes of either semi-vrince or co-vrince. Figure 1(c) lso shows tht verge semi-vrince increses nd reches plteu t lg distnce of bout 4, nd tht is lso the lg distnce t which the co-vrince becomes negtive. Plteu of semi-vrince nd/or negtive co-vrince suggests lg distnce by which point observtions re no longer sptilly correlted nd tht the rnge vlue hs been reched. Importntly, the rnge estimte should not exceed the shortest distnce within the imge file. Thus, regrding the dt set presented in Figure 1(c), vriogrm prmeter estimtes should be discrded if the rnge vlue estimte exceeds 10. Figure 1. Bsic description of vriogrm nlysis pplied to reflectnce dt. Semi-vrince Sill Nugget Rnge b 10 0.33 0.35 0.33 0.31 0.32 0.3 0.31 0.32 0.33 0.32 9 0.31 0.35 0.33 0.32 0.31 0.31 0.32 0.32 0.32 0.34 Northing of pixels 8 0.36 0.33 0.33 0.32 0.32 0.29 0.32 0.32 0.33 0.31 7 0.31 0.34 0.34 0.31 0.31 0.29 0.31 0.32 0.32 0.29 6 0.3 0.33 0.32 0.33 0.28 0.29 0.3 0.3 0.31 0.3 5 0.31 0.29 0.31 0.32 0.3 0.3 0.3 0.29 0.33 0.31 4 0.32 0.33 0.33 0.34 0.29 0.29 0.29 0.3 0.31 0.3 3 0.33 0.3 0.32 0.33 0.31 0.29 0.3 0.32 0.32 0.29 2 0.31 0.32 0.32 0.34 0.32 0.27 0.29 0.31 0.33 0.29 Semi-vrince c 0.00050 0.00045 0.00040 0.00035 0.00030 0.00025 0.00020 0.00015 Lg distnce 342 Semi-vrince Co-vrince 448 60 520 850 608 684 522 444 368 94 2 4 6 8 10 12 8 2 0.00015 0.00010 0.00005 0.00000-0.00005-0.00010-0.00015-0.00020-0.00025 Co-vrince d 1 0.32 0.31 0.31 0.35 0.31 0.29 0.3 0.32 0.32 0.29 Semi-vrince 1 2 3 4 5 6 7 8 9 10 0.00035 0.00030 0.00025 0.00020 Esting of pixels 0.00015 5 lg intervl 0.00010 6 lg intervl 7 lg intervl 0.00005 8 lg intervl 9 lg intervl 0.00000 0 2 4 6 8 Lg distnce between pixels Lg distnce between pixels A very importnt spect of regression fits to vriogrm dt is the decision on how mny lg distnce intervls to use when fitting Equtions (1) or (2) to the dt in Figure 1(b). All regression fits with Eqution (2) to semi-vrince dt when 5 9 lg distnce intervls were included (excluding the lst 4) provided highly significnt regression fits (P < 0.001), but it ws seen tht rnge estimtes incresed with number of lg distnce intervls included in the regression fit (Figure 1(d)). In fct, the rnge estimte with nine lg distnce intervls (7.9) ws lmost twice the rnge estimte with five lg distnce intervls (4.3), nd the nugget vlue ws 1.8 times higher when bsed on 9 lg distnce intervls compred to 5. This simple exmple illustrtes how firly subjective decisions bout regression fit settings cn mrkedly ffect the outcome of given vriogrm nlysis. Thus, despite the widespred cceptnce of geosttistics being BLUE (best liner unbised estimte) [18,22], it is lso sometimes cknowledged tht different pplictors of this pproch my develop highly different sptil structure nlyses of the sme dt set, nd significnt portion of this subjectivity is ssocited with decisions mde regrding vriogrm nlyses [18,21]. However, recent nlysis of
Remote Sens. 2012, 4 185 wide rnge of vriogrm settings demonstrted tht this nlyticl pproch hd higher robustness (rdiometric repetbility) thn 3 stndrd vegettion indices (NDVI, SI, nd PRI) [16]. 3. Mterils nd Methods 3.1. Greenhouse Plnt Mteril The greenhouse mize plnts hve been described elsewhere [3,16]. In brief, we plnted 2 mize hybrids (Hybrid 1: Triumph 1416, 2004 nd Hybrid 2: Pioneer 3223, 2006) October 2007 (dt set 1) nd Februry 2008 (dt set 2) in individul 11L plstic pots, nd ech plnt ws mintined under 1 of 3 wter regimes. Spider mite infesttion consisted of plcing hevily infested lef piece on ech mize plnt. Mize plnts in dt set 1 were infested 4 December 2007, while mize plnts in dt set 2 were infested 25 Mrch 2008. Tble 1. Dt sets (totl of 229 hyperspectrl imges) included in this study. Non-Infested Infested DAI None Moderte High None Moderte High 8 Dec 3.00 6 6 6 6 6 6 Dt set 1 12 Dec 7.00 6 6 6 6 6 6 14 Dec 9.00 6 6 6 6 6 6 28 Mr 3.00 5 5 6 4 5 6 Dt set 2 31 Mr 6.00 5 5 6 4 5 6 2 Apr 8.00 5 5 6 4 5 5 5 Apr 10.00 5 5 6 4 4 5 DAI denotes dys fter infesttion of mize plnts with spider mites, nd non-infested/infested refers to whether the mize plnts were infested with spider mites. 3.2. Hyperspectrl Imging A push broom line-scnning hyperspectrl cmer with 640 sensors in liner rry (PIKA II, www.resonon.com) ws used. This hyperspectrl cmer cquires reflectnce dt in 160 spectrl bnds in wvelengths from 405 to 907 nm. Drk clibrtion ws conducted t the beginning of the dt cquisition. White Teflon ws used for white clibrtion immeditely before ech imge cquisition to ccount for subtle chnges in light conditions. Ech hyperspectrl imge ws 6 cm long nd 2.5 cm wide (15 cm 2 ) from mid portion of 7th or 8th lef without dmging the mize plnt (lef not excised). A hyperspectrl imge consisted of 160,000 reflectnce profiles (640 sensors 250 frmes) or pixels. The imging device ws mounted bout 45 cm from imged leves nd the reflectnce dt were cquired t sptil resolution of 106 hyperspectrl profiles or pixels per mm 2 inside greenhouse with sunlight s the only light source. Similr to [16], PC-ENVI 4.7 (www.ittvis.com) ws used to conduct 4 4 sptil verging so tht ech hyperspectrl imge from greenhouse plnts ws reduced to 10,080 (160 63) pixels. Thus, fter sptil verging of hyperspectrl imging dt from greenhouse plnts, the sptil resolution ws equivlent to 6.7 hyperspectrl profiles (pixels) per mm 2.
Remote Sens. 2012, 4 186 3.3. Vriogrm Settings All hyperspectrl imge files were imported into PC-SAS 9.2 (Cry, NC, USA) for dt processing nd sttisticl nlyses. Vriogrm nlyses (PROC VARIOGRAM) were conducted of ll combintions of spectrl bnds (160) nd hyperspectrl imges (229) (totl = 36,640 vriogrm nlyses). Bsed on previous study [4], the following vriogrm settings were used: semi-vrince dt with lg distnce of 2 nd 15 lg distnce intervls. Non-liner regression (PROC NLIN) ws used to conduct sphericl regression (Eqution (2)) of semi-vrince dt nd to estimte the 3 vriogrm prmeters, nugget, sill, nd rnge. Vriogrm prmeter estimtes from hyperspectrl imge file were discrded if the regression fits filed to converge or the predicted rnge vlue exceeded 63. This threshold of 63 ws chosen s it represented the width of the imging dt cube nd rnge vlue higher thn 63 ment tht the sill ws reched t lg distnce tht ws longer thn the width of dt set. Due to the rnge vlue threshold, there ws slight vrition in the number of vriogrm dt observtions used in sttisticl nlyses of ech of the spectrl bnds. Ech of the 3 vriogrm prmeters, nugget, sill, nd rnge, were exmined individully in n nlysis of vrince (PROC MIXED) with 4 tretment effects (dt set, hybrid, biotic, nd biotic stressors) nd dy fter infesttion s rndom vrible. Abiotic stress ws ssigned vlue from 1 to 3 with: no drought stress (biotic stress = 1), moderte (biotic stress = 2), or high (biotic stress = 3). These wter regimes were imposed by wtering highly drought stressed plnts one-third s much s the no drought stressed plnts, nd modertely drought stressed plnts received two-thirds of the wter given to no drought stressed plnts. Spider mite infesttions were grouped into the following 3 clsses: (1) biotic stress = 1 (0 10 spider mites per plnt) (50% of dt), (2) biotic stress = 2 (10 480 spider mites per plnt) (25% of dt), nd (3) biotic stress = 3 (>480 spider mites per plnt) (25% of dt). These rnges were chosen to obtin similr numbers of observtions in the 2 clsses with spider mite induced stress. For ech nlysis of vriogrm prmeter, F-vlues ssocited with ech of the tretment fctors were used s indictors of how well given combintion of spectrl bnd nd vriogrm prmeter responded to the exmined stress fctors. 4. Results nd Discussion 4.1. Dul Stress Detection For ech of the 480 combintions of spectrl bnds nd vriogrm prmeters (160 spectrl bnds 3 vriogrm prmeters), the reltive effects of dt set, mize hybrid, biotic stress (irrigtion regime), nd biotic stress (spider mite infesttion) were exmined. The min purpose ws to identify combintions of spectrl bnds nd vriogrm prmeters tht could be considered relible/unique stress indictors without showing significnt response to difference between mize hybrids nd/or between the 2 dt sets. Severl importnt observtions could be mde from this initil nlysis (Figure 2): (1) most of the combintions of spectrl bnds nd vriogrm prmeters were found unsuitble s stress indictors minly becuse of significnt difference between the 2 dt sets, especilly in nlyses of sill vlues, (2) nugget vlues (Figure 2()) from 645 675 nm nd 766 826 nm (multiple spectrl bnds in ech spectrl rnge) responded significntly to biotic stress without responding significntly to other tretment fctors, (3) sill vlues (Figure 2(b)) showed highly
Remote Sens. 2012, 4 187 consistent response to biotic stress in spectrl bnds from 592 to 668 nm, but the sme spectrl bnds lso responded significntly to difference between dt sets, so they were not considered further, (4) rnge vlues (Figure 2(c)) from 579 to 661 nm (multiple spectrl bnds) responded significntly to biotic stress without responding significntly to other tretment fctors, nd (5) rnge vlues t 715 nm responded significntly to biotic stress without responding significntly to other tretment fctors. Thus, it ws demonstrted tht there is considerble vrition in the stress response by vriogrm prmeters derived from different spectrl bnds, nd tht unique responses to biotic nd biotic stressors could be detected. It is suspected tht more spectrl bnds responding significntly to biotic stress thn to biotic stress becuse the rnge of biotic stress ws likely wider thn tht of biotic stress. Vriogrm prmeters derived from severl of spectrl bnds ner 700 nm responded significntly to the imposed stressors, so the dt nlysis presented here corroborte findings published elsewhere [4,8]. Bsed on results presented in Figure 2 nd identifiction of highest F-vlues from ll 480 nlyses of vrince, 4 spectrl bnds, (683 nd 775 nm s biotic stress indictors nd 715 nd 731 nm s biotic stress indictors) were selected for further nlyses (Figure 3). It ws seen tht there ws n increse in both nugget nd sill vlues t 683 nm (Figure 3()) nd 775 (Figure 3(b)) nd tht rnge vlues t 683 nm decresed in response to biotic stress. Regrding vriogrms t 731 nm (Figure 3(c)) nd 715 nm (Figure 3(d)), it ws seen tht rnge vlues incresed in response to biotic stress, nd sill vlues t 731 nm incresed considerbly. Anlysis of vrince ws used to identify sttisticl differences in vriogrm prmeters in response to the imposed stressors (Figure 4). Figures 4 nd b suggested tht nugget vlues t 683 nm (Figure 4()) nd 775 nm (Figure 4(b)) incresed significntly when mize plnts re subjected to severe drought stress compred to mize plnts without drought stress. Regrding detection of biotic stress, nugget vlues t 731 nm (Figure 4(c)) nd rnge vlues t 715 nm (Figure 4(d)) lso showed significnt responses. Figure 2. Anlysis of vrince of nugget (), sill (b) nd rnge (c) vlues in 160 spectrl bnds between 405 nd 907 nm in response to 4 tretment fctors: (1) difference between dt set 1 nd 2 (Tble 1), (2) difference between hybrid 1 nd 2, (3) response to biotic stress, nd (4) response to biotic stress. Horizontl brs represent spectrl regions with significnt response to either biotic (dshed) or biotic (non-dshed) stressor t the 0.05-level. Biotic b c Fctor Abiotic Hybrid Dt sets 500 600 700 800 900 Wvelength (nm) 500 600 700 800 900 Wvelength (nm) 500 600 700 800 900 Wvelength (nm)
Remote Sens. 2012, 4 188 Figure 3. Vriogrms of reflectnce dt t 683 nm () nd 775 (b) in response to biotic stress, nd t 731 nm (c) nd 715 nm (d) in response to biotic stress. Semi-vrince 0.0006 0.0005 0.0004 0.0003 0.0002 0.0001 None Moderte Severe 0.008 0.006 0.004 0.002 b None Moderte Severe 0.0000 0 10 20 30 40 Lg distnce 0.0025 0.0020 c 0.000 0 10 20 30 40 50 Lg distnce 0.005 0.004 d Semi-vrince 0.0015 0.0010 0.0005 None Few Moderte 0.003 0.002 0.001 None Few Moderte 0.0000 0 10 20 30 40 50 Lg distnce 0.000 0 10 20 30 40 50 Lg distnce Figure 4. Nugget vlues t 683 nm () nd 775 (b) in response to biotic stress, nd nugget vlues t 731 nm (c) nd rnge vlues t 715 nm (d) in response to biotic stress. Different letters denote sttisticl difference t the 0.05-level. Nugget vlue 0.00016 0.00014 0.00012 0.00010 0.00008 0.00006 0.00004 0.00002 b b Nugget vlue 0.0005 0.0004 0.0003 0.0002 0.0001 c b b 0.00000 None Moderte Severe None Few Moderte Nugget vlue 0.0004 0.0003 0.0002 0.0001 0.0000-0.0001-0.0002-0.0003-0.0004 b b b None Moderte Severe Rnge vlue 38 36 34 32 30 28 26 d b None Few Moderte Abiotic stress Biotic stress
Remote Sens. 2012, 4 189 4.2. Reltionship between Reflectnce Dt nd Vriogrm Prmeters Tble 2 shows tht none of the exmined descriptive sttistics reveled trends consistent with the identified vriogrm prmeter responses, nd tht none of them could be considered relible stress indictors. Thus, the findings in this study re not in greement with Crter nd Knpp [8], who, bsed on n extensive review, concluded tht most plnt stressors induce n increse in reflectnce, especilly in spectrl bnds ner 700 nm. One possible explntion for the discrepncy between the results presented in this study nd those by Crter nd Knpp [8] is tht this study ws bsed on heterogeneous composite of 2 dt sets nd 4 tretment fctors (dt set, mize hybrids, biotic nd biotic stressors). Furthermore, it is importnt to mention tht spider mite infesttion levels were generlly low with highest count on single mize plnt equl to bout 700 spider mites. Bsed on smpling of spider mite infested mize plnts from greenhouse cultures nd field plots, over 300 spider mites my be found on single mize leves [23], which my mount to severl thousnd spider mites on single plnt ( fully developed mize plnt typiclly hs 15 20 leves). Thus even though biotic stress ws referred to s rnging from none to severe, nd biotic stress rnged from none to moderte, the imposed stress levels were quite subtle. Tble 2. Descriptive sttistics of verge reflectnce vlues t 683, 715, 731, nd 775 nm. Stndrd Confidence Limits Averge Medin Error Lower Upper Width Response to biotic stress t 683 nm None 0.091b 0.087b 0.000030 0.090 0.091 0.000118 Moderte 0.089 0.083 0.000034 0.089 0.089 0.000132 High 0.093b 0.088b 0.000035 0.093 0.093 0.000136 Response to biotic stress t 775 nm None 0.836b 0.840b 0.000121 0.836 0.836 0.000474 Moderte 0.823 0.825 0.000137 0.823 0.824 0.000539 High 0.856b 0.859b 0.000132 0.856 0.856 0.000519 Response to biotic stress t 715 nm None 0.370 0.366 0.000084 0.370 0.370 0.000331 Few 0.372 0.371 0.000087 0.372 0.373 0.000341 Moderte 0.389 0.386 0.000129 0.389 0.389 0.000504 Response to biotic stress t 731 nm None 0.638b 0.640b 0.000088 0.638 0.638 0.000345 Few 0.633 0.639 0.000098 0.633 0.634 0.000385 Moderte 0.66b4 0.663b 0.000148 0.664 0.664 0.000581 Different letters cross stress levels (verticl comprison) denote difference t the 0.05-level. This low spider mite infesttion level ws intentionl, s the objective ws to test vriogrm bsed nlysis on chllenging model system, nd vriogrm prmeters did respond significntly despite the fct tht nlysis of verge reflectnce vlues in the sme spectrl bnds yielded no consistent trends. A recent study involving experimentl mnipultion of reflectnce dt (dding 2.5% or 5.0% to reflectnce vlues in ll or rndom subsets of pixels) showed tht increse in reflectnce especilly
Remote Sens. 2012, 4 190 ffected sill vlues nd to some extent lso effected nugget vlues but hd negligible effect on rnge vlues [24]. Thus, if minly sill vlues respond to increses in reflectnce vlues, it is not surprising tht this study showed negligible increse in verge reflectnce nd non-consistent response by sill vlues to the 2 stressors. Without significnt increse in verge reflectnce nd/or width of 95% confidence limits, remining objective ws to chrcterize the sptil distribution (scttering) of reflectnce responses to imposed stressors. In this context, it is very importnt to mention tht crop leves re never clen tht dust, pollen, nd discolortions will invribly be present, nd they cn obviously compromise clssifiction ccurcy of reflectnce bsed pproches. Figure 5 shows typicl mize lef imge nd 4 hyperspectrl imge files, which were selected bsed on their nugget nd rnge vlues derived from the spectrl bnd t 683 nm. Averge reflectnce vlues vried within 10% (0.82 0.91) with the vst mjority of pixels hving reflectnce vlues between 0.05 nd 0.10, nd ll 4 imges were cquired ner the lef mid rib (white line of excluded pixels in the middle of ech imge). Compring imges nd b, it is seen tht minly due to single lrge spots of incresed reflectnce in the top right corner cused 4-fold increse in nugget vlues, while sill nd rnge vlues remined firly constnt. Compring imges c nd d, it is seen tht few scttered spots of incresed reflectnce cused 2-fold increse in rnge vlues, while these scttered spots hd negligible effect on nugget nd sill vlues. The subtle vrition in reflectnce vlues mong these 4 imges emphsize the mrked sensitivity of vriogrm nlysis nd how it my be used to mplify vritions in dt sptilly orgnized dt sets, which otherwise could not be differentited. Figure 5. Mize lef imges: n ctul RGB imge nd 4 imges bsed on reflectnce vlues t 683 nm with ech imge representing 10,000 pixels. Actul mize lef Imge Nugget = 0.000041 Sill = 0.000254 Rnge = 21.01 Imge b Nugget = 0.000166 Sill = 0.000231 Rnge = 21.75 Imge c Nugget = 0.000115 Sill = 0.000117 Rnge = 22.25 Imge d Nugget = 0.000140 Sill = 0.000177 Rnge = 46.08 Averge = 0.082 Medin = 0.079 Averge = 0.090 Medin = 0.087 Averge = 0.085 Medin = 0.083 Averge = 0.091 Medin = 0.088 0.05-0.10 0.10-0.15 0.15-0.20 0.20-0.25 Bsed on the findings in this study nd results published elsewhere, it is hypothesized tht if n imposed stress level is sufficiently high, it will led to significnt increse in verge reflectnce, especilly ner 700 nm, nd especilly sill vlues will respond to such n increse [4,8]. However, even before significnt increse in verge reflectnce, stress expression in crop leves my
Remote Sens. 2012, 4 191 predominntly consist of scttered increses in reflectnce within given lef, nd tht my led to significnt increses in both nugget nd rnge vlues. In theoreticl model nlysis of the reltionship between chlorophyll distribution nd lef reflectnce, Brton [25] concluded tht: (1) Even smll nd subtle stress signs of chlorosis cn significntly influence the reflectnce of lef nd tht sensitivity of reflectnce to chlorosis vries with wvelength. (2) Within-lef vrition in chlorophyll concentrtion due to stressors my mrkedly increse lef reflectnce nd led to underestimtion of chlorophyll concentrtion. In ddition, Brton [25] highlighted the importnce of studying plnt stress response bsed on individul leves nd lso to incorporte sptil distribution informtion into the nlysis. 5. Conclusions This study confirmed results from previously published studies [4,8], tht nlysis of reflectnce dt ner 700 nm show strong stress response, but it ws lso shown tht this spectrl region my not be suitble for stress detection, when crop plnts re subjected to more thn 1 stressor nd when other tretment fctors re included in the nlysis. With focus on vriogrm prmeters, it ws shown tht especilly nugget nd rnge vlues incresed significntly in response to the imposed stressors. Nugget vlues t 683 nd 775 nm responded significntly to biotic stress, nd nugget vlues t 731 nm nd rnge vlues t 715 nm responded significntly to biotic stress. Bsed on qulittive chrcteriztion of ctul imges, it ws seen tht even subtle chnges in sptil ptterns of reflectnce vlues cn elicit severl-fold chnges in vriogrm prmeters despite non-significnt chnges in verge nd medin reflectnce vlues nd in width of 95% confidence limits. Furthermore, it ws hypothesized tht, rther thn cusing grdul increse in reflectnce in ll pixels, emerging plnt stress expression predominntly elicit increses in reflectnce in scttered pixels within crop lef. Such scttered stress expression is in ccordnce with documented within-lef vrition in both minerl content nd chlorophyll concentrtion nd therefore supports the need for reflectnce-bsed stress detection t high sptil resolution (mny hyperspectrl reflectnce profiles cquired from single lef) nd my be used to explin or chrcterize within-lef forging ptterns of herbivorous rthropods. Acknowledgements This study ws prtilly funded by the Texs Corn Producers Bord. References 1. Reisig, D.; Godfrey, L. Spectrl response of cotton phid- (Homopter: Aphidide) nd spider mite- (Acri: Tetrnychide) infested cotton: Controlled studies. Environ. Entomol. 2007, 36, 1466-1474. 2. Dellieux, S.; Auwerkerken, A.; Verstreten, W.W.; Ben Somers, B.; Vlcke, R.; Lhermitte, S.; Keulemns J.; Coppin, P. Hyperspectrl reflectnce nd fluorescence imging to detect scb induced stress in pple leves. Remote Sens. 2009, 1, 858-874. 3. Nnsen, C.; Sidumo, A.J.; Cpred, S. Vriogrm nlysis of hyperspectrl dt nlysis to chrcterize impct of biotic nd biotic stress of mize plnts nd to estimte biofuel potentil. Appl. Spect. 2010, 64, 627-636.
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