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The effects of leaf dorsoventrality and its interaction with environmentally induced changes in the leaf spectral response are still poorly understood, particularly for isobilateral leaves. We investigated the spectral performance of 24 genotypes of field-grown durum wheat at two locations under both rainfed and irrigated conditions. Flag leaf reflectance spectra in the VIS-NIR-SWIR (visible–near-infrared–short-wave infrared) regions were recorded in the adaxial and abaxial leaf sides and at the canopy level, while traits providing information on water status and grain yield were evaluated. Moreover, leaf anatomical parameters were measured in a subset of five genotypes. The spectral traits studied were more affected by the leaf side than by the water regime. Leaf dorsoventral differences suggested higher accessory pigment content in the abaxial leaf side, while water regime differences were related to increased chlorophyll, nitrogen, and water contents in the leaves in the irrigated treatment. These variations were associated with anatomical changes. Additionally, leaf dorsoventral differences were less in the rainfed treatment, suggesting the existence of leaf-side-specific responses at the anatomical and biochemical level. Finally, the accuracy in yield pre- diction was enhanced when abaxial leaf spectra were employed. We concluded that the importance of dorsoventrality in spectral traits is paramount, even in isobilateral leaves. Keywords: Dorsoventral effect, leaf spectroscopy, nitrogen, pigment, side-specific responses, water stress, wheat. Introduction Spectroradiometry is a pivotal technique in the remote (Xue and Su, 2017). However, this information is usually pre- sensing evaluation of plant performance, used widely for dicted in an empirical manner without a clear understanding precision agriculture, high-throughput phenotyping, and of how a basic aspect such as leaf side (adaxial versus abax- ecosystem studies. Very diverse information is retrieved from ial) may affect the spectrum of the reflected radiation and the spectral signature of the light reflected by the canopy or the different categories of spectroradiometrical indices. This even by single leaves (Ustin et al., 2009), and to date a large is particularly relevant because canopy evaluations of spec- corpus of spectral reflectance indices has been formulated troradiometrical indices, at either the ground or aerial levels, © The Author(s) 2018. Published by Oxford University Press on behalf of the Society for Experimental Biology. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. Downloaded from https://academic.oup.com/jxb/article/69/12/3081/4957039 by DeepDyve user on 18 July 2022 3082 | Vergara-Díaz et al. are usually performed using the spectrum reflected from the chemical composition and the prevalence of structural sup- adaxial part of the leaves (Jacquemoud and Baret, 1990; Sims porting elements (Taylor et al., 1989). and Gamon, 2002; Lu and Lu, 2015). The aim of the present study was to investigate the effect For its part, water stress is known to trigger mechanisms of of water regime as well as leaf-side-specific responses on leaf acclimation in the leaf such as changes in gene expression and reflectance traits in field-grown durum wheat. Spectral reflect- modification of plant physiology, morphology, and anatomy, ance indices are discussed in the context of their relationship leading to homeostatic compensation (Flexas et al., 2006). At to different physiological, biochemical, and anatomical traits the leaf level, changes in morphology, anatomy, turgor status, of the leaf. The similarity and dissimilarities between both leaf and biochemical content can directly and/or indirectly impact spectra and of the spectrum of the canopy, and their implica- the reflected radiation. In fact, this is the basis for plant status tions for yield prediction were also addressed. The study was studies using a spectroscopic approach. Moreover, few stud- performed in the flag leaf because it has been reported to be ies have considered leaf-side-specific responses, and those the most isobilateral leaf in wheat (Araus et al., 1986). focusing on the leaf dorsoventral effect have usually been performed on plant species with a clear bifacial leaf anatomy (Evans, 1999; Lu et al., 2015). Materials and methods In contrast, monocots such as wheat have typical isobi- Plant material and experimental set up lateral leaves whereby dorsoventral differences tend to be Field trials were carried out during the 2014/15 growing season underestimated, considering the relative homogeneity in the at two locations: in central Spain at the experimental station of mesophyll anatomy (lack of a clear dorsoventral gradient in Colmenar de Oreja (Madrid), belonging to the Instituto Nacional de terms of palisade versus spongy cells) and even on the epi- Investigación y Tecnología Agraria y Alimentaria (INIA) of Spain, and in northern Spain at the experimental station of Zamadueñas dermal surface of these leaves (which are amphystomatous). (Valladolid), belonging to the Instituto Tecnológico Agrario de However, the abaxial epidermis is thinner and lacks bulliform Castilla y León (ITACyL). Geographic and agronomic informa- cells and furrows, while the usually relatively erect position tion together with weather, irrigation, and soil information are all of the flag leaf and the fact that it is placed in the uppermost detailed in Table 1. part of the canopy suggest that the light gradient through the Twenty-four durum wheat [Triticum turgidum L. subsp durum (Desf) Husn.] varieties released during the last 40 years in Spain leaf is not too strong. were grown at both experimental stations. Plots were sown in a ran- Recent studies in monocots have reported side-specific ana- domized blocks design with three replicates. A total of four growing tomical and physiological responses that are usually depend- conditions were considered: rainfed and supplemental irrigated con- ent on genotypic and environmental effects (Soares et al., ditions for each location. At harvest, grains were dried in an oven at 2008; Soares-Cordeiro et al., 2011; Jafarian et al., 2012). 60 °C for 48 h, and grain yield (GY) was determined. For instance, leaf side-specific responses of photosynthesis and stomatal closure to light intensity and CO enrichment, Spectral data collection and index calculation as well as to chilling and water stresses, have been reported The flag leaf spectral signature was measured with a Field-Spec4 in C and C species (Wang et al., 1998; Soares et al., 2008; 3 4 (ASD Inc. PANalytical Company, Boulder, CO, USA) full-range Soares-Cordeiro et al., 2011). Even so, there is a notable lack portable spectroradiometer, and spectra were acquired in the 350– of understanding of how and to what extent these leaf-side- 2500 nm range. The adaxial and abaxial leaf surfaces were meas- ured for each leaf with an ASD leaf clip accessory assembled to specific responses to environmental stress might affect the an ASD standard plant contact probe coupled with a fibre optic to reflected radiation at the leaf and plant canopy scales. To the the FieldSpec4 spectrometer. This probe is provided with a halo- best of our knowledge, this is the first study addressing side- gen bulb and has a spot size of 10 mm diameter. A total of 288 specific responses of wheat leaves to varying water conditions non-senescent leaves, one per plot and thus 144 from each location, using a spectroscopic approach. were measured at the mid grain-filling stage (25–27 May; 73 in the Zadoks scale), generating a total of 576 leaf spectra. Canopy spec- The spectral signatures in the range of visible (VIS; 400– tra were measured at midday (80 min before and after noon) with a 700 nm), near-infrared (NIR; 700–1400 nm), and short-wave pistol grip coupled with the fibre optic to the FieldSpec4 spectrom- infrared (SWIR, 1400–2500 nm) wavelengths were investi- eter. Measurements were made 1 m above the plot canopy in a zen- gated in the flag leaves of a set of 24 wheat genotypes grow- ithal plane, and the reflectance was calibrated every 15–20 min with ing under different water regimes in the field. Leaf reflectance a Spectralon white reference panel. A collection of 85 spectral reflectance indices (SRIs) was cal- spectra were recorded for the two leaf sides (adaxial and culated for each leaf spectrum (Supplementary Table S1 at JXB abaxial) and at the canopy level. Additionally, leaf size as well online). The broadband SRIs were calculated with reference to the as some specific morphological and anatomical traits (epider - Landsat Enhanced Thematic Mapper Plus (ETM+) sensor (Landsat mis, mesophyll, and xylem vessel metrics) were measured, 7, USGS) wavebands. and the stable carbon (δ C) isotope composition of the flag leaves and grains as well as the total carbon (%C) and nitro- Other spectroradiometrically derived leaf traits gen (%N) content of the flag leaves were further analysed. The leaf radiative transfer model, PROSPECT5 (Jacquemoud Although the δ C and total nitrogen content may provide and Baret, 1990), was used to estimate the equivalent water thick- information on the water and nitrogen status of the leaves ness (EWT) and the total chlorophyll (Chl) and carotenoid (Car) (Araus et al., 1997; Yousfi et al., 2012), the total carbon and contents from leaf reflectances using a numerical inversion of the PROSPECT 5 model via Matlab7. nitrogen and their ratio provide a broad indication of leaf Downloaded from https://academic.oup.com/jxb/article/69/12/3081/4957039 by DeepDyve user on 18 July 2022 Linking leaf spectroscopy and leaf traits in wheat | 3083 Table 1. Geographic, climatic, agronomic, and soil information for values were expressed in composition notation (δ) as follows: 13 13 12 13 12 δ C=[( C/ C) /( C/ C) ]–1, where ‘sample’ refers to each study site sample standard plant material and ‘standard’ to international secondary standards 13 12 of known C: C ratios (IAEA CH7 polyethylene foil, IAEA CH6 Zamadueñas Colmenar de Oreja sucrose, and USGS 40 l -glutamic acid) calibrated against Vienna experimental station experimental station Pee Dee Belemnite calcium carbonate with an analytical precision (standard deviation) of 0.15‰. Altitude (m asl) 700 590 In addition, a JEOL JSM-7100F scanning electron microscope Co-ordinates 41°42'N, 4°42'W 40°04'N, 3°31'W (JEOL, Akishima, Japan) in the Scientific and Technological Mean temp. (°C) 10.73 13.01 Facilities of the University of Barcelona was employed to observe Max. mea n temp. (°C) 17.45 21.45 the epicuticular wax structure of the adaxial and abaxial sides of Min. mean temp. (°C) 4.64 5.36 the flag leaf. Lyophilized leaves were gold-coated and subsequently Precipitation (mm) 258.4 206.8 observed operating at 10 kV. Sowing date 24 November 2014 21 November 2014 Finally, air (Testo 177-H1 Logger, Germany) and plot canopy Harvest date 22 July 2015 20 July 2015 temperature (PhotoTemp MXS, Raytek Corporation, CA, USA) were simultaneously recorded and the canopy temperature depres- Sowing density (seeds 250 250 −2 sion (CTD) was calculated as the difference between them. m ) Plot surface (m ) 10.5 (7 × 1.5) 10.5 (7 × 1.5) Irrigation provided (mm) 125 180 Statistical analysis Fertilization Multivariate ANOVAs were conducted using SPSS 21 (IBM SPSS −1 −1 First application 300 kg ha NPK 8:15:15 400 kg ha NPK 15:15:15 Statistics 21, Inc., Chicago, IL, USA). Principal component analysis −1 −1 Second application 300 kg ha CAN 27%N 150 kg ha Urea 46% (PCA) of reflectances was performed with CANOCO 4.5 software Soil texture Loam Clay-loam (Ter Braak and Smilauer, 2002). Figures were drawn with SigmaPlot Soil pH 8.44 8.1 10.0 (Systat Software Inc., San Jose, CA, USA). Finally, the clus- tered heatmap, the LASSO, and the backward stepwise regression analyses were performed with R 3.2.2 using the GPLOTS (Warnes During the growing season. In the irrigated treatments. et al., 2009), the GLMNET (Friedman et al., 2010), and the MASS (Ripley et al., 2013) packages, respectively. Total leaf Chl content on an area basis was also assessed with a portable Chl meter (Minolta SPAD-502, Spectrum Technologies Inc., Plainfield, IL, USA). Results GY was significantly affected by water regime (Table 2), Leaf morphological, anatomical, and physiological traits −1 decreasing by 47% in Zamadueñas (from 7.17 Mg ha to The leaf lamina length and width were measured in three flag leaves −1 −1 3.77 Mg ha ) and by 10% in Aranjuez (from 5.13 Mg ha to from each plot. Additionally, five genotypes representative of yield −1 4.65 Mg ha ) under rainfed compared with irrigated condi- variability (data not shown) were selected for the anatomical observa- tions. Flag leaf blade segments of 10 × 5 mm were sampled and sub- tions. Yield differences in Aranjuez were lower due to severe merged in Visikol clearing solution (Visikol Inc., New Brunswick, NJ, lodging during grain filling in the irrigated treatment. USA). The samples were incubated with 1% osmium tetroxide and The CTD and leaf blade size (length and width) were sig- 0.8% potassium ferrocyanide, washed with MiliQ water, dehydrated nificantly higher in irrigated conditions, whereas there was no with acetone at 4 °C, embedded in epoxy resin at room temperature, difference in leaf Chl content assessed by a SPAD meter due and blocks were left in the oven for 72 h at 80 °C. Cross-sections were obtained with an Ultracut E ultramicrotome (Reichert-Jung, to water regime. Regarding isotope composition, the δ C of Vienna, Austria) and stained with methylene blue and Van Gieson’s leaves and grains increased significantly in rainfed compared solution. Digital images were taken with an Olympus CX41 optical with irrigated conditions. Total leaf nitrogen content (%N) microscope at ×100 and ×200 magnifications. was significantly reduced in rainfed conditions, whereas the Images were scale-calibrated, and anatomical metrics were meas- C:N ratio was increased (Table 2). ured with Image J software. For the whole leaf cross-section, meas- urements were recorded of the leaf thickness, leaf sectional area, xylem vessel area and diameter, mesophyll cell sectional area and Leaf spectrum performance perimeter, epidermis cell sectional area and cell wall thickness, epi- dermis length, and areas of both the adaxial and the abaxial epi- Water regime significantly affected leaf reflectance in the NIR dermis. For the cross-sections, the following ratios were calculated: and SWIR regions (Fig. 1a). Regardless of the leaf side, leaf total epidermis length to leaf cross-section area, the epidermis area reflectance was significantly higher under irrigated conditions to epidermis length ratio for the adaxial and abaxial epidermises (hereafter considered as epidermis thickness), the epidermis area to in the NIR region (756–948 nm and 997–1000 nm), whereas leaf area ratio for both epidermises, and the mesophyll cell area to in rainfed conditions it was higher in the violet (350–375 nm) cell perimeter ratio. and SWIR regions (1289–1886 nm and 1988–2254 nm). 13 12 The stable carbon ( C: C) isotope ratio as well as the nitro- This performance changed when studying each leaf side gen (N) and carbon (C) concentrations (%) were measured in leaf separately (Fig. 1b, c). Differences in NIR reflectance between and grain dry matter using an elemental analyser (Flash 1112 EA; Thermo Finnigan, Bremen, Germany) coupled with an iso- water regimes were only detected in the abaxial leaf side (747– tope ratio mass spectrometer (Delta C IRMS, Thermo Finnigan) 1000 nm), whereas leaves belonging to the irrigated treatment operating in a continuous flow mode. Samples of 0.7–1 mg of leaf had higher reflectance. In contrast, in the second half of the dry matter from each plot, together with reference materials, were SWIR region, reflectance differences between water regimes weighed and sealed into tin capsules. Measurements were conducted were detected only in the adaxial leaf side (1988–2240 nm), at the Scientific Facilities of the University of Barcelona. Isotopic Downloaded from https://academic.oup.com/jxb/article/69/12/3081/4957039 by DeepDyve user on 18 July 2022 3084 | Vergara-Díaz et al. and were higher in the rainfed treatment. Finally, leaf reflect- On the other hand, and regardless of the water condi- ance from the end of the NIR region to the SWIR region tions during cultivation, the reflectances of the adaxial and (1300–1900 nm) was quite similar in both leaf sides, with the abaxial leaf surfaces were significantly different across sev- leaf reflectance being higher in the rainfed than in the irri- eral wavebands of the spectrum (Fig. 2a). In the violet region gated treatment. (350–425 nm), the abaxial reflectance was always significantly higher compared with the adaxial reflectance. In the red-edge region, abaxial reflectance was initially higher from 666 nm Table 2. Means and deviations of grain yield, leaf blade length to 702 nm and then decreased significantly from 719 nm to and width, leaf SPAD readings, leaf nitrogen and carbon 731 nm. Abaxial reflectance was always higher in the NIR concentration (%N and %C), and its ratio (C:N), grain and leaf plateau, and these differences were significant in the ranges of stable carbon isotope composition (δ C), and the canopy 752–850, 949–969, and 1035–1169 nm. Finally, in the SWIR temperature depression (CTD) for each water regime (R+, region, adaxial reflectance was significantly higher from irrigated; R–, rainfed) along with the significance level of the 1501 nm to 1739 nm and significantly lower from 1357 nm respective one-way ANOVA to 1437 nm, 1859 nm to 1994 nm, and 2377 nm to 2500 nm. Additionally, differences in reflectance between leaf sides Water regime ANOVA changed considerably within water regimes (Fig. 2b, c). The R+ R– P WR differences in the red-edge region between leaf sides were −1 evident only under rainfed conditions (676–699 nm; 721– Grain y ield (Mg ha ) 6.95 4.81 <0.001 733 nm). In contrast, reflectance differences between leaf 0.097 0.097 Leaf length (cm) 20.9 19.11 <0.001 sides throughout the NIR plateau were present only under 4.35 3.36 irrigated conditions (747–991 nm; 1000–1170 nm). Leaf width (cm) 1.679 1.547 0.038 Additionally, four contour maps were generated of reflect- 0.484 0.257 ance cross-correlations from across the spectrum (Fig. 3) with SPAD reading 55.467 55.692 0.699 the aim of further investigating the intrinsic relationships of 5.189 4.621 the waveband reflectances for each experimental condition. Plot CTD (°C) 4.89 0.63 <0.001 The following trends can be highlighted: cross-correlation 1.199 1.92 coefficients were always higher in the adaxial side of the leaf Leaf C (%) 40.13 40.42 0.486 than in the abaxial leaf side (i.e. wavebands were more closely 3.46 3.36 correlated in the spectrum of the adaxial leaf side). Similarly, Leaf N (%) 4.045 3.893 <0.001 0.362 0.385 when water regimes were compared, higher correlation coef- Leaf C:N ratio 9.95 10.46 <0.001 ficients were always obtained under rainfed conditions. 0.798 1.098 –28.1 –27.83 <0.001 Leaf δ C (‰) Principal component analysis of reflectance ranges 0.635 0.472 Grain δ C (‰) –26.16 –25.34 <0.001 To determine the most influential spectral ranges that 0.494 1.18 accounted for data variability, a PCA was performed and Fig. 1. Leaf reflectance spectra in irrigated (grey line) and rainfed (black line) water conditions for the entire set of records (A, n=576) and separated according to the leaf side measured, either in the adaxial (B, n=288) or in the abaxial (C) leaf side. Below: the respective P-value graphs for each of the one-way comparisons performed for the reflectance throughout the spectrum, where the reflectance in each wavelength is considered as a variable and the water regime as a factor. Spectral regions where differences are significant (1–P-value >0.95) are shaded in black. Downloaded from https://academic.oup.com/jxb/article/69/12/3081/4957039 by DeepDyve user on 18 July 2022 Linking leaf spectroscopy and leaf traits in wheat | 3085 Fig. 2. Leaf reflectance spectra in adaxial (grey line) and abaxial (black line) sides of the leaf for the entire set of records (A, n=576) and separating into the two water conditions, under either irrigated (B, n=288) or rainfed (C, n=288) conditions. Below: the respective P-value graphs for each one-way comparison performed for the reflectance across the spectrum, where the reflectance in each wavelength is considered as a variable and the leaf side as a factor. Spectral regions where differences are significant (1–P-value >0.95) are filled in black. Fig. 3. Contour maps of Pearson correlation coefficients between reflectances across the spectrum depending on water conditions (A) either in the irrigated (above the diagonal) or in the rainfed treatment (below the diagonal); and depending on leaf side (B), in the adaxial (above the diagonal) or the abaxial side of the leaf (below the diagonal). reflectances in 15 nm wavelength ranges were used as vari- analysis, but their relationships to the studied factors were ables (Fig. 4). The resulting PCA explained almost 83% of less evident. Interaction centroids in the PCA graph were very data variability (64.6% PC1 and 18.1% PC2). Variable fit- closely related in rainfed conditions (Ad*R- and Ab*R-), but ness was fixed at 57%, and 123 wavebands were selected by not in irrigated conditions where the interaction centroids the analysis. First, a cluster of variables grouped the wave- were placed far from the principal effect. bands in the NIR region from 740 nm to 1309 nm. This clus- ter was related to the leaf-side factor, and the reflectance of Performance of the spectroradiometrical parameters this region was higher in the abaxial leaf side. Secondly, the Factor clustering indicated that the overall differences in the reflectance within the SWIR region, in the 1400–1534 nm spectroradiometrical parameters (including SRIs and the and 1850–2500 nm wavebands, was moderately related to estimations obtained by the PROSPECT model) were greater the water regime effect, with the leaf reflectance being higher between leaf sides than between water conditions (Fig. 5). under rainfed conditions. The reflectance in the VIS region Water treatment differences were detected as significant (590–664 nm and 680–694 nm) had a similar trend to that by 25 of the SRIs (Supplementary Table S2), which were of the SWIR region, but it was a milder effect. Other wave- the most sensitive water indices, and in particular the MSI, bands in the NIR and SWIR regions were also selected by the Downloaded from https://academic.oup.com/jxb/article/69/12/3081/4957039 by DeepDyve user on 18 July 2022 3086 | Vergara-Díaz et al. of the subset of samples used in the anatomical study was assessed by the respective performance of the SRIs. As in the main analysis presented here, water, nitrogen, and some pigment-related SRIs detected water regime differences for this subset of plots, while evidence for leaf side differences was mainly derived from pigment- and structure-related SRIs (Supplementary Table S3). Water stress induced significant decreases in xylem vessel cross-sectional area and diam- eter, and mesophyll cell cross-sectional area and perimeter, whereas the mesophyll cell cross-sectional area to perimeter ratio increased (Fig. 6; Table 3). All the epidermal traits measured were significantly differ - ent between leaf sides, including the area of the epidermis cell section, the epidermis thickness, and the ratio of the epider- mis sectional area to the total leaf sectional area, which were higher in the adaxial epidermis, whereas the epidermis cell wall thickness was higher in the abaxial epidermis. Additionally, a wide range of SRIs (water-, biochemical-, and structure-related indices) significantly correlated with Fig. 4. Principal component analysis of reflectances introduced as several anatomical traits (Fig. 7). Mesophyll cell-sectional variables. Light green arrows correspond to wavebands belonging to the area and the mesophyll cell area to cell perimeter ratio cor- visible region, violet arrows correspond to wavebands in the NIR region, related positively with the water-related indices, NDWI and while dark green arrows correspond to wavebands in the SWIR region. NDII, respectively (Fig. 7a, b). Meanwhile, the mesophyll cell Main levels of the factors (R+, irrigated; R–, rainfed; AD, adaxial side; AB, sectional perimeter correlated positively with the N-related abaxial side) are represented as filled rhomboids, and interactions (Ad*R+; Ad*R–; Ab*R+; Ab*R–) are shown as empty triangles. The variables index, NDNI (Fig. 7c), and with the Chl-related index, shown in the graph were those selected by fixing the fitness at 57%. R RENDVI (Fig. 7d), whereas the ratio between the epidermis corresponds to the reflectance at λ band. sectional area and the leaf sectional area correlated nega- tively with the Chl index, NPQI (Fig. 7e), and positively with NDII, NDWI, NMDI, and SWWI (P<0.001). Many other the flavonol-related index, FRI, and with the lignin-related biochemical and structurally related indices (pigment, lignin, index, NDLI (Fig. 7f, h). Finally, the epidermis cell cross- and nitrogen) such as ARI , ARI , NDNI, mDATT, NDLI, 1 2 sectional area correlated negatively with the Anth index, FRI (P<0.001), mCARI , and MRCI (P<0.05) also varied mARI (Fig. 6g). significantly between water conditions. Finally, some red- edge indices including VREI , VREI (P<0.01), and NDRE 1 2 (P<0.05) were also shown to be sensitive to the water treat- Relationship between leaf and canopy spectra and ment factor. their relationship to GY Regarding the dorsoventral effect, 42 of the SRIs tested The similarities between adaxial, abaxial, and canopy reflect- were sensitive to this factor. These SRIs mainly corresponded ance spectra were assessed with a PCA, setting the reflect- to biochemical, structural, and water indices, but also to some ance spectra as variables. The resulting two-component PCA narrow and broadband greenness indices. The most robust (Supplementary Fig. S1) explained 94% of the variability differences between leaf sides were found by pigment-sensi- (82.1% PC1 and 12.7% PC2). Measurements were distrib- tive indices [Chl, Car, and anthocyanin (Anth)], and struc- uted in two parallel dot clouds, where the two leaf spectra tural and water-related indices (P<0.001). were overlapping and parallel to that of the canopy. Leaf and The interaction between leaf side and water regime was sig- canopy dot clouds were mainly separated by PC1, which was nificant for some indices (ARI, mARI, GATB, SIPI, NPCI, mostly dependent on R . In addition, from the collection SRPI, and PSRI) whose formulation included a red-edge 1900 of indices calculated, 74% of adaxial SRIs correlated signifi- alongside a blue or green wavelength. In such cases, the vari- cantly with the respective indices at the canopy level, whereas ation in these SRIs in response to water regime was clearly only 52% of abaxial SRIs correlated significantly with the dependent on the side of the leaf. respective canopy indices (data not shown). Regarding the PROSPECT estimated leaf traits, only the In order to test the leaf-side effect on the ability for yield EWT varied significantly between water regimes, and it was prediction, two multiple regression models were performed: higher in the irrigated treatment. a LASSO analysis using the full-range reflectance spectrum and a backward multiple regression using the SRIs (Table 4). Leaf anatomy In both analyses, the explained variability was always higher when using canopy spectral data, followed by the abaxial Leaf anatomy was studied in a subset of five genotypes with models and lastly the adaxial models, all of them being sig- the aim of gaining insights into the relationship between nificant (P<0.001). leaf anatomy and spectral signature. The representativeness Downloaded from https://academic.oup.com/jxb/article/69/12/3081/4957039 by DeepDyve user on 18 July 2022 Linking leaf spectroscopy and leaf traits in wheat | 3087 Fig. 5. Clustered heatmap of the spectroradiometer parameters (on the right) grouped by its trait targeted as water-related SRIs (Water), anthocyanin- related SRIs (Anth), carotenoid-related SRIs (Car), chlorophyll-related SRIs (Chl), carotenoid to chlorophyll ratio-related SRIs (Car/Chl), narrowband greenness indices (NBG), broadband greenness indices (BBG); other SRIs including nitrogen- and structural-related indices and estimates from the PROSPECT model (PROSPECT). At the top, a dendrogram resulting from the clustering analysis, with labels in bold indicating the main levels of the factors (R+, irrigated; R–, rainfed; AD, adaxial side; AB, abaxial side) and the interactions (Ad*R+; Ad*R–; Ab*R+; Ab*R–). The red–blue colour scale was obtained by Z-score transformation of the actual values. revealed that the spectral parameters were more influenced by Discussion the side of the leaf measured than by the water regime. In this study, the decrease in GY, CTD, and leaf elongation Leaf reflectance was sensitive to leaf side in several wave- (i.e. flag leaf blade length and width) in rainfed conditions bands of the spectrum (Fig. 2) that were beyond the expected compared with the support irrigation trial was associated structurally related wavebands (i.e. not only in the NIR with water stress as shown by the increase in leaf δ C and an but also in the red-edge and SWIR regions). Even so, PCA even larger increase in grain δ C (Table 2) from irrigated to (Fig. 4) revealed the leaf-side factor to be strongly associated rainfed conditions (Araus et al., 2003; Araus et al. 2013; Bort with leaf reflectance spectrum variability in the NIR region, et al., 2014). and was positively related to the abaxial side of the leaf. The magnitude of reflectance in the NIR region is largely governed by structural discontinuities in the leaf (i.e. cell layers and Leaf anatomy-related spectral signal interfaces) and leaf dry matter content (Peñuelas and Filella, A wide range of spectral traits was affected substantially by 1998; Ceccato et al., 2001; Homolova et al., 2013). In particu- the leaf-side factor. In particular, clustering analysis (Fig. 5) lar, previous studies have reported that leaf NIR reflectance Downloaded from https://academic.oup.com/jxb/article/69/12/3081/4957039 by DeepDyve user on 18 July 2022 3088 | Vergara-Díaz et al. Similarly, the reported leaf anatomical differences between water regimes, such as the larger size of the mesophyll cell cross-sectional area and perimeter and a lower cell packing level (higher cell area to perimeter ratio) in the irrigated treat- ment (Table 3), led to an increase in NIR reflectance (Knapp and Carter, 1998; Johnson et al., 2005; Ollinger, 2011) in irri- gated compared with rainfed leaves (Fig. 1). The observed trends of increasing leaf thickness and decreasing epidermis sectional area relative to the total leaf sectional area in irri- gated compared with trials might also contribute to a higher NIR reflectance of the former. PCA (Fig. 4) revealed that adaxial and abaxial reflect- ance properties were closely related in rainfed conditions but were markedly differentiated in irrigated conditions. In other words, water stress caused changes in the leaf that tended to reduce dorsoventral differences in the spectrum. For instance, overall reflectance differences between leaf sides were detected in the NIR region in the irrigated treatment but not in rainfed conditions (Fig. 2b, c). This trend is further supported by the contour maps of correlations between wave- band reflectance for the four main effects (rainfed and irri- gated conditions, adaxial and abaxial leaf sides) (Fig. 3). In these analyses, higher correlation coefficients for the adaxial side compared with the abaxial side (Fig. 3a) can be explained by lower variation (i.e. greater similarity) of the adaxial spec- tral traits between water regimes. Meanwhile, reflectance dif- ferences between leaf sides were lower in rainfed conditions, which explains the higher correlation coefficients in rainfed compared with irrigated conditions (Fig. 3b). It must be noted that leaf anatomical and biochem- ical characteristics can be affected by the gradient of light exposure during growth. Thus, while more erect leaves are characterized by an isobilateral anatomy, more horizontal leaves may exhibit increased dorsoventrality. In the case of wheat, an insertion gradient exists, with the flag leaf exhibit- ing more isobilateral characteristics than the basal (tillering) leaves (Araus et al., 1986), which is probably associated with a progressive increase in verticality of the successive leaves. However, environmental conditions other than the light gra- dient cannot be discarded. Thus an increase in the level of atmospheric drought and the intensity of solar radiation during growth seems to affect the degree of isobilaterality of the flag wheat leaf laminas growing in the field (Araus et al., 1989). Fig. 6. Flag leaf transverse section images of two durum wheat In fact, as previously mentioned in this study, the leaf genotypes; (A, C) var. Tussur; (B, D) var. Avispa; grown under irrigated (A, dorsoventral gradient was less pronounced in rainfed condi- B) and rainfed (C, D) conditions. tions. Nevertheless, despite there being no clear differences is increased in flat and thick leaves possessing thin epidermal among the genotypes in the angle of the laminas for given and epicuticular layers and long palisade cells (Knapp and growing conditions (i.e. site and water regime) (data not Carter, 1998; Johnson et al., 2005; Ollinger, 2011; Kozhoridze shown), it should be noted that during stem elongation the et al., 2016). In concordance, the increased NIR reflectance laminas usually extrude vertically and the final position of in the abaxial compared with the adaxial leaf side (Fig. 2) each lamina is only achieved when it is fully expanded. can be consistently associated with a thinner and flatter epi- In agreement with previous observations in cereals, the dermis in the abaxial surface (Table 3). Thus, the existence of wax cover was uniform and denser on the adaxial leaf side anatomical differences between the adaxial and abaxial leaf (Supplementary Fig. S2a, c) (Araus et al., 1991). As described sides, particularly in the epidermis, greatly impacts on leaf by Willick et al. (2018), the filament size of the epicuticu- reflectance in the NIR region, even in an isobilateral leaf. lar waxes was larger and longer in the abaxial leaf side Downloaded from https://academic.oup.com/jxb/article/69/12/3081/4957039 by DeepDyve user on 18 July 2022 Linking leaf spectroscopy and leaf traits in wheat | 3089 Table 3. Means of the leaf section anatomical metrics for each water regime (R+, irrigated; R–, rainfed) and leaf side along with the significance levels of the respective two-way ANOVA Water regime Leaf side Adaxial Abaxial Significance R+ R- Adaxial Abaxial R+ R- R+ R- P P P WR LS WR*LS Leaf Thickness (µm) 199.98 176.23 - - - - - - .065 - - -1 0.112 0.118 - - - - - - .350 - - Perimeter/area (µm ) Epidermis area/Leaf area 0.177 0.185 - - - - - - .249 - - Mesophyll - - - - - - - - 577.17 407.89 - - - - - - .001 - - Cell area (µm ) Cell perimeter (µm) 111.47 88.80 - - - - - - .000 - - 5.04 4.42 - - - - - - .006 - - Cell area/Cell perimeter (µm) Xylem vessels Major diameter (µm) 32.50 23.28 - - - - - - .011 - - 544.34 281.69 - - - - - - .008 - - Vessels area (µm ) Epidermis Thickness (µm) 15.91 15.72 17.06 14.57 17.35 16.77 14.46 14.67 .740 .000 .477 Area/leaf area .089 .092 .100 .081 .099 .102 .078 .083 .192 .000 .784 220.9 237.5 294.7 163.7 278.3 311.2 163.5 163.9 .385 .000 .398 Cell area (µm ) Wall thickness (µm) 3.988 4.066 3.581 4.473 3.621 3.541 4.355 4.592 .643 .000 .352 (Supplementary Fig. S2b, d), whereas water stress seemed to In particular, the performance of several spectral traits induce an increase in wax density (Supplementary Fig. S2c, d). revealed differences in leaf N-protein and lignin content in Previous studies have reported that the presence of waxes (glau- response to water stress. The moderate relationship between cousness) is important for reflecting UV–VIS light with respect the water regime effect and the second half of the SWIR to non-waxy leaves, with the UV–blue regions being particu- region (Fig. 4) was coincident with the absorption bands larly affected (Clark and Lister, 1975; Reicosky and Hanover, of these compounds (Kokaly 2001; Ustin et al., 2009). 1978; Febrero and Araus, 1994). Thus, reflectance differences Additionally, the SRIs related to N-protein and lignin con- between leaf sides and water regimes in the violet region could tent (NDNI and NDLI, respectively) varied in response to the be associated with the observed structural differences in the low water regime, showing decreasing and increasing trends, wax cover density and size. In comparison with the waveband respectively (Supplementary Table S2). The analytical meas- range of this study, changes in biochemical composition of the urements of leaf N concentration that indicated a decrease epicuticular waxes between leaf sides and water regimes have under rainfed conditions (Table 2) further confirmed this been reported for longer wavebands (Mid-IR) (Willick et al., trend. Additionally, the reported positive correlation between 2018), whereas wax determination has been addressed with the mesophyll cell section perimeter and the N-related index shorter wavebands (UV) (Bianchi and Figini, 1986). NDNI (Serrano et al., 2002) (Fig. 7c) showed the relationship between composition and anatomical changes, which were both caused by water-limited conditions. Leaf water- and composition-related spectral signals On the other hand, increasing the leaf C:N ratio (Table 2) Leaf reflectance in the SWIR region has been related to water in rainfed conditions could indicate the prevalence of sup- and N-protein absorption as well as to other biochemical con- porting elements (i.e. cell wall materials) enriched in N-free stituents such as lignin, cellulose, and starch (Peñuelas and compounds such as lignin. Moreover, the described epidermal Filella, 1998; Ustin et al., 2009; Homolova et al., 2013). Even leaf side differences (Table 3; Fig. 6) (i.e. greater epidermis so, the amount of water available in the internal leaf struc- thickness and cell section area, and the increased percentage ture largely controls SWIR reflectance (Ceccato et al., 2001; of epidermis area relative to the total leaf sectional area in Ollinger, 2011). Thus, the increase in leaf reflectance in the the adaxial leaf side) and their relationship to the lignin spec- SWIR region under rainfed conditions (Fig. 1) consistently tral signal (Fig.7h) further support this suggestion. indicates lower leaf water content. At wavelengths beyond Regarding the leaf water signal, the water-related SRIs 1400 nm, water absorption partially overshadows the absorp- derived from the SWIR bands (e.g. MSI, NDII, NMDI, tion features of other biochemical compounds (Ollinger, SWWI, and NDryMI) were the most sensitive to changing 2011). Nevertheless, the reported relationship between SWIR water conditions, indicating a decrease in water content con- reflectance and the water regime effect (Fig. 4), as well as the ditions as well as an increase in leaf dry matter content in performance of several SRIs, suggest that the water regime response to rainfed conditions (Supplementary Table S2). may affect leaf biochemistry in addition to the direct effect This superior performance of SWIR-based SRIs has been on leaf water status. noted previously (Carter, 1991) following the high sensitivity Downloaded from https://academic.oup.com/jxb/article/69/12/3081/4957039 by DeepDyve user on 18 July 2022 3090 | Vergara-Díaz et al. Fig. 7. Scatter plot graphs showing correlations between anatomical leaf section traits (EaLar, epidermis sectional area to leaf sectional area ratio; ECa, epidermis cell sectional area; MCa, mesophyll cell sectional area; MCp, mesophyll cell sectional perimeter; Mcapr, mesophyll cell sectional area to perimeter ratio) and spectral reflectance indices (the water-related indices NDWI and NDII; the nitrogen-related index NDNI; the chlorophyll-related indices RENDVI and NPQI; the flavonol-related index FRI; the anthocyanin-related index mARI, and the lignin-related index NDLI) for the subset of plots selected. of reflectance to leaf water content in the water-absorbing In turn, for the subset of genotypes where leaf anatomy 1300–2500 nm range. In contrast, the use of the 970 nm sec- was studied, the observed variability in water-related indices, ondary water absorption band (which is included in indices such as NDWI and NDII (Hardisky et al., 1983; Gao 1996), such as WBI and NWI) was ineffective at the scale of the was strongly and positively correlated with the increase in current work, although it has been reported as effective at the mesophyll cell size and the decrease in the mesophyll cell the whole-plant and canopy scales (Peñuelas et al., 1997; packing (i.e. mesophyll cell area to perimeter ratio) from the Gutierrez et al., 2010). The PROSPECT EWT parameter rainfed to the irrigated treatment (Fig. 7a, b). These results proved to be robust, showing differences between water show that the variation in anatomical traits (in turn caused by regimes. Downloaded from https://academic.oup.com/jxb/article/69/12/3081/4957039 by DeepDyve user on 18 July 2022 Linking leaf spectroscopy and leaf traits in wheat | 3091 Table 4. Multiple regression analyses for grain yield prediction dorsoventral effect by improving the accuracy of water con- employing the adaxial, abaxial, or canopy reflectances tent retrieval. st 1 Approach - Backward stepwise Chlorophyll-related spectral signal Adaxial Abaxial Canopy Regarding the dorsoventral effect on the Chl spectral sig- SRIs SRIs SRIs nal, the observed significant changes in red-edge reflectance R 0.732 0.795 0.925 between leaf sides (Fig. 2) were largely related to absorption adjusted R 0.637 0.713 0.903 by Chl (Ustin et al., 2009; Ollinger, 2011). Unlike other spec- p-value < 0.001 < 0.001 < 0.001 troscopic studies using species with bifacial leaves (Knapp error of prediction 0.963 0.858 0.499 et al., 1988; Vogelmann and Evans, 2002; Johnson et al., nd 2 Approach - LASSO regression 2005), we detected an apparently higher Chl content in the Adaxial Abaxial Canopy abaxial side of the leaf from assessments with all of the Chl- spectrum spectrum spectrum sensitive spectral indices (Supplementary Table S2). The cor- relation between the Chl-related index, NPQI (Barnes et al., R actual vs estimated 0.384 0.552 0.747 p-value < 0.001 < 0.001 < 0.001 1992), and the ratio of the epidermis sectional area to the leaf sectional area (Fig. 7e) (which increased in the adaxial leaf For the first approach, the spectral reflectance indices (SRIs) side) revealed a dorsoventral gradient in the Chl spectral sig- calculated at the three levels (from adaxial, abaxial, and canopy nal. The higher sun irradiance reaching the upper side of the measurements) were set as variables in a backward stepwise analysis. leaf may involve a chloroplast acclimation process (i.e. lower For the second approach, three LASSO regression models were performed with the whole spectrum at the three mentioned levels. Chl content) (Terashima et al., 1986), which may support the Each model was obtained using a training set (75% of data), and its existence of a leaf dorsoventral gradient in Chl. robustness was assessed by its respective accuracy in predicting yield Different responses of leaf Chl content to water stress have (R ) for the test set (25% of data). been reported in the literature (Loggini et al., 1999; Carter and Knapp, 2001; Izanloo et al., 2008; Valifard et al., 2012), and the water conditions during growth) affected the leaf spectral can be highly dependent on genotypic variability and pheno- performance. logical stage. In this study, the total leaf Chl content per unit The consistent dorsoventral differences in SWIR reflect- area (measured with a portable SPAD meter) was unaffected ance (centred on 1600, 1400, and 1900 nm) found under both by water conditions. SPAD readings are exponentially corre- water conditions (Fig. 2) suggest the existence of constitutive lated with leaf Chl content (Uddling et al., 2007), so for high differences in biochemistry and/or water content between values of SPAD (as they occur in our study) the variation in leaf sides that are independent of the water conditions dur- the actual Chl content could be high, and the accuracy of the ing growth. The adaxial epidermis of wheat is character- readings can also be affected by leaf water content (Martínez ized by the presence of bubble-shaped bulliform cells whose and Guiamet, 2004). Instead, many of the Chl-related SRIs changes in turgidity control leaf straightening. Accordingly, (e.g. RECI, mSR , mSR , mDATT, VREI MRCI, and we hypothesized that a higher water content signal would be 1 2 1 NDRE) showed interesting trends. Indices based solely on red- expected in the adaxial epidermis. The reported decrease in edge wavebands were more sensitive to the water regime and adaxial reflectance (Fig. 2) in the SWIR that was coincident apparently indicated a decrease in Chl content under rainfed with strong absorption by water (centred on 1430 nm and conditions, whereas SRIs including blue or green wavebands 1950 nm) may support this hypothesis as a direct response in their formulation (e.g. ChlNDI, TCI, and TCARI) were to water changes. However, the response in the NIR region insensitive. The interference of other pigments such as Car and has previously been reported rather as an indirect effect via Anth, which have absorption wavebands in the blue and green changes in leaf structure and scattering (Ollinger, 2011). regions, might affect the Chl retrieval of some of the SRIs Some of the water SRIs tested, particularly those using the tested. As additional evidence, the reflectance in the red region waveband centred on 1600 nm, detected apparently higher was shown to be positively related to rainfed conditions in the water content in the abaxial side of the leaf. This waveband PCA (Fig. 4). Although the estimated Chl content from the has been reported to be indirectly sensitive to leaf and canopy PROSPECT model did not vary significantly between water water content (Ceccato et al., 2001; Jackson et al., 2004), but conditions, it followed the same decreasing trend in rainfed it is also related to leaf structure and biochemical character- conditions. Additional evidence for this is the positive corre- istics (Ceccato et al., 2001; Serrano et al., 2002). Therefore, lation between the Chl-related SRI, RENDVI (Gitelson and the possible existence of biochemical and/or structural dif- Merzlyak, 1994), and the mesophyll cell perimeter (Fig. 7d), ferences between the two sides of the leaf could affect the whereby a higher mesophyll cell size under irrigation com- reflectance in this waveband and thus interfere with leaf water pared with rainfed conditions matches the increase in the Chl content retrieval. Nevertheless, some other water-related SRIs spectral signal. Previous studies have shown that indices using (NDMI and NDMI ) combining NIR and SWIR bands as 1 2 off-chlorophyll absorption wavebands (i.e. 690–730 nm) are well as the EWT were insensitive to leaf side but were effect- the best Chl predictors because they have greater sensitivity to ive at detecting water regime differences. Thus, combin- subtle changes in Chl content than the maximum absorption ing NIR and SWIR bands may remove variations induced wavebands (i.e. 660–665 nm for Chl a) (Zarco-Tejada et al., by mesophyll structure (Ceccato et al., 2001) and avoid the Downloaded from https://academic.oup.com/jxb/article/69/12/3081/4957039 by DeepDyve user on 18 July 2022 3092 | Vergara-Díaz et al. 2003; Main et al., 2011). Altogether these results suggest a 2014). In addition to the photoprotective function mentioned decreasing trend in leaf Chl content under rainfed conditions, before, previous studies have suggested that flavonols act as with its level of significance depending on the sensitivity of the antioxidants in plants (Hernández et al., 2009), accumulating detection of the spectral parameter (i.e. SPAD meter, SRIs, in different compartments such as the leaf epidermis (Tevini PROSPECT model). et al., 1991). In this context, the increase in the ratio of the epidermis section area to the leaf section area (in the adax- ial compared with the abaxial leaf side and in rainfed com- Photoprotection-related spectral signal pared with irrigation conditions), which correlated positively Besides leaf Chl, the leaf Car and Anth contents are also usu- with FRI (Fig. 7f), suggested an anatomy-mediated increase ally targeted because of their ecophysiological significance in leaf flavonols in response to water stress and to high sun- (Close and Beadle, 2003; Ustin et al., 2009). Under stress light levels. These results support the implementation of SRIs conditions, Cars function to prevent photooxidation of the related to drought tolerance metabolites for plant stress stud- reaction centres (Ustin et al., 2009), while Anths have an anti- ies and breeding purposes. oxidant and photoprotective role, besides acting as osmoreg- ulators in plant cells (Chalker-Scott, 1999; Steyn et al., 2002; Main ideas and some insights into the scaling effect Gould et al., 2002). and yield prediction Regarding dorsoventrality effects, all Car- and Anth-related SRIs, as well as those related to the Car:Chl ratio, indicated a Overall, the detailed study of leaf reflectance and several higher Car and Anth content and Car:Chl ratio in the abax- spectral-derived parameters revealed significant differences ial leaf side (Supplementary Table S2), suggesting a prevail- between the two sides of the leaf, which in turn are highly ing photoprotective role for the abaxial side of the leaf. The dependent on water regime, particularly under irrigated condi- reported negative correlation between the Anth-related index, tions. For instance, the significant interactions between dorso- mARI (Gitelson et al., 2001), and the epidermis cell sectional ventral and water regime effects in some of the Car:Chl- and area (Fig. 7g) suggests the existence of an anatomy-driven Anth-related indices (Fig. 5; Supplementary Table S2) sug- dorsoventral gradient in Anth content. In agreement with gest possible side-specific photochemical changes in response this, Cartelat et al. (2005) reported higher leaf phenolic con- to water regime. Previous studies in monocots (Soares et al., tent, which includes Anth, in the abaxial side of wheat leaves 2008; Soares-Cordeiro et al., 2011) have reported that side- measured with a portable device (Dualex meter). As reported specific physiological responses are involved in leaf acclima- by Shi et al. (2014), this might indicate that the upper part tion to environmental stresses. In our study, the following of wheat leaves exhibits greater light use efficiency via lower tentative trend is hypothesized: in well-watered conditions, energy dissipation and photoinhibition. Although the Car the two sides of the leaf are more differentiated, with the estimation by PROSPECT performed similarly to the Car- adaxial part of the leaf being photosynthetically more effi- related SRIs, the differences were not significant. This robust cient (having a lower Car:Chl and Anth), larger epidermal but conservative performance of the PROSPECT parameters and mesophyll cells, and a thicker epidermis. However, water may be explained by the large range of leaf pigment con- stress induces alterations in structural, pigment, and photo- centrations (i.e. wide range of species and conditions) used protective compounds that tend to reduce dorsoventral dif- for the development of the PROSPECT model (Feret et al., ferences (functioning) of both leaf sides and consequently the 2008). Finally, the results in the flavonol-related index (FRI) spectroradiometrical response of reflected light. To the best (Merzlyak et al., 2005) suggested a possible higher flavonol of our knowledge, this is the first study describing a leaf-side- content in the adaxial leaf side (Supplementary Table S2). It specific response to water regime in wheat using a spectro- is worth pointing out that this index was originally developed scopic approach. for apple fruit, where Car and Chl contents do not interfere The classical approaches for multispectral remote sensing as much as in leaves. Flavonols are considered to have a pho- evaluation of leaf and vegetation traits have usually been toprotective role as UV-absorbing compounds (Mazza et al., developed using the reflectance spectrum from the adaxial 2000), so a possible higher concentration in the upper side of side of the leaves (Jacquemoud and Baret, 1990; Sims and the leaf (i.e. the more exposed to sunlight) (Fig. 7f) may indi- Gamon, 2002; Lu and Lu, 2015). Although the adaxial leaf cate an ecophysiological relevance for them as photoprotec- spectrum appeared to be more representative of the canopy- tors instead of Anth. level data, the prediction of grain yield was clearly enhanced Regarding the water regime effect on photoprotective when abaxial rather than adaxial reflectance is employed, and compounds, Car-related indices were unaffected, and Anth- this was irrespective of whether the full-range spectra or sin- related indices decreased under rainfed conditions, whereas gle SRIs were used (Table 4). Therefore, this study reveals that the flavonol-related SRI increased (Supplementary Table S2). even for a species, such as wheat, with isobilateral leaves, spec- The performance of leaf Cars and Anths in response to water tra are different, and this may affect the assessment of yield. stress is quite variable according to the literature (Alexieva Apart from constitutive differences, some anatomical traits et al., 2001; Chakraborty and Pradhan, 2012; Valifard et al., of the abaxial leaf side (the epidermis thickness and the 2012; Hammad and Ali, 2014). Accumulation of flavonols in epidermis cell area) seemed to be less affected by changing the leaves has been reported in wheat in response to water water conditions than the adaxial side. This greater struc- stress and especially in drought-tolerant varieties (Ma et al., tural homogeneity across the abaxial leaf blade surface may Downloaded from https://academic.oup.com/jxb/article/69/12/3081/4957039 by DeepDyve user on 18 July 2022 Linking leaf spectroscopy and leaf traits in wheat | 3093 oxygen in assessing early vigour and grain yield in durum wheat. Journal of provide a less noisy spectral signal and better suitability for Agricultural Science 152, 408–426. the prediction of yield from spectroscopy compared with the Broge NH, Leblanc E. 2001. Comparing prediction power and stability adaxial leaf side. of broadband and hyperspectral vegetation indices for estimation of green leaf area index and canopy chlorophyll density. Remote Sensing of Environment 76, 156–172. Supplementary data Cartelat A, Cerovic ZG, Goulas Y, et al. 2005. 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Journal of Experimental Botany – Oxford University Press
Published: May 25, 2018
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