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      Combining biophysical parameters, spectral indices and multivariate hyperspectral models for estimating yield and water productivity of spring wheat across different agronomic practices

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          Abstract

          Manipulating plant densities under different irrigation rates can have a significant impact on grain yield and water use efficiency by exerting positive or negative effects on ET. Whereas traditional spectral reflectance indices (SRIs) have been used to assess biophysical parameters and yield, the potential of multivariate models has little been investigated to estimate these parameters under multiple agronomic practices. Therefore, both simple indices and multivariate models (partial least square regression (PLSR) and support vector machines (SVR)) obtained from hyperspectral reflectance data were compared for their applicability for assessing the biophysical parameters in a field experiment involving different combinations of three irrigation rates (1.00, 0.75, and 0.50 ET) and five plant densities (D 1: 150, D 2: 250, D 3: 350, D 4: 450, and D 5: 550 seeds m -2) in order to improve productivity and water use efficiency of wheat. Results show that the highest values for green leaf area, aboveground biomass, and grain yield were obtained from the combination of D 3 or D 4 with 1.00 ET, while the combination of 0.75 ET and D 3 was the best treatment for achieving the highest values for water use efficiency. Wheat yield response factor (ky) was acceptable when the 0.75 ET was combined with D 2, D 3, or D 4 or when the 0.50 ET was combined with D 2 or D 3, as the ky values of these combinations were less than or around one. The production function indicated that about 75% grain yield variation could be attributed to the variation in seasonal ET. Results also show that the performance of the SRIs fluctuated when regressions were analyzed for each irrigation rate or plant density specifically, or when the data of all irrigation rates or plant densities were combined. Most of the SRIs failed to assess biophysical parameters under specific irrigation rates and some specific plant densities, but performance improved substantially for combined data of irrigation rates and some specific plant densities. PLSR and SVR produced more accurate estimations of biophysical parameters than SRIs under specific irrigation rates and plant densities. In conclusion, hyperspectral data are useful for predicting and monitoring yield and water productivity of spring wheat across multiple agronomic practices.

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          Most cited references 54

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          Crop Production under Drought and Heat Stress: Plant Responses and Management Options

          Abiotic stresses are one of the major constraints to crop production and food security worldwide. The situation has aggravated due to the drastic and rapid changes in global climate. Heat and drought are undoubtedly the two most important stresses having huge impact on growth and productivity of the crops. It is very important to understand the physiological, biochemical, and ecological interventions related to these stresses for better management. A wide range of plant responses to these stresses could be generalized into morphological, physiological, and biochemical responses. Interestingly, this review provides a detailed account of plant responses to heat and drought stresses with special focus on highlighting the commonalities and differences. Crop growth and yields are negatively affected by sub-optimal water supply and abnormal temperatures due to physical damages, physiological disruptions, and biochemical changes. Both these stresses have multi-lateral impacts and therefore, complex in mechanistic action. A better understanding of plant responses to these stresses has pragmatic implication for remedies and management. A comprehensive account of conventional as well as modern approaches to deal with heat and drought stresses have also been presented here. A side-by-side critical discussion on salient responses and management strategies for these two important abiotic stresses provides a unique insight into the phenomena. A holistic approach taking into account the different management options to deal with heat and drought stress simultaneously could be a win-win approach in future.
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            Hyperspectral Vegetation Indices and Their Relationships with Agricultural Crop Characteristics

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              Sources of variability in canopy reflectance and the convergent properties of plants.

              How plants interact with sunlight is central to the existence of life and provides a window to the functioning of ecosystems. Although the basic properties of leaf spectra have been known for decades, interpreting canopy-level spectra is more challenging because leaf-level effects are complicated by a host of stem- and canopy-level traits. Progress has been made through empirical analyses and models, although both methods have been hampered by a series of persistent challenges. Here, I review current understanding of plant spectral properties with respect to sources of uncertainty at leaf to canopy scales. I also discuss the role of evolutionary convergence in plant functioning and the difficulty of identifying individual properties among a suite of interrelated traits. A pattern that emerges suggests a synergy among the scattering effects of leaf-, stem- and canopy-level traits that becomes most apparent in the near-infrared (NIR) region. This explains the widespread and well-known importance of the NIR region in vegetation remote sensing, but presents an interesting paradox that has yet to be fully explored: that we can often gain more insight about the functioning of plants by examining wavelengths that are not used in photosynthesis than by examining those that are. © 2010 The Author. New Phytologist © 2010 New Phytologist Trust.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Formal analysisRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SoftwareRole: SupervisionRole: ValidationRole: Writing – original draftRole: Writing – review & editing
                Role: Data curationRole: Formal analysisRole: MethodologyRole: Resources
                Role: Formal analysisRole: InvestigationRole: SoftwareRole: VisualizationRole: Writing – original draft
                Role: Data curationRole: Formal analysisRole: Funding acquisitionRole: MethodologyRole: Resources
                Role: Data curationRole: Funding acquisitionRole: MethodologyRole: Resources
                Role: Data curationRole: Funding acquisitionRole: MethodologyRole: ResourcesRole: Visualization
                Role: Data curationRole: Formal analysisRole: Funding acquisitionRole: MethodologyRole: SoftwareRole: Validation
                Role: ConceptualizationRole: Formal analysisRole: MethodologyRole: SoftwareRole: SupervisionRole: Visualization
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                6 March 2019
                2019
                : 14
                : 3
                Affiliations
                [1 ] Department of Plant Production, College of Food and Agriculture Sciences, King Saud University, Riyadh, Saudi Arabia
                [2 ] Department of Agronomy, Faculty of Agriculture, Suez Canal University, Ismailia, Egypt
                [3 ] Evaluation of Natural Resources Department, Environmental Studies and Research Institute, Sadat City University, Menoufia, Egypt
                [4 ] Department of Horticulture, Faculty of Agriculture, Kafrelsheikh University, Kafr El Sheikh, Egypt
                [5 ] Department of Biology, College of Science and Humanities at Quwayiah, Shaqra University, Riyadh, Saudi Arabia
                [6 ] Department of Agricultural Botany, Faculty of Agriculture, Suez Canal University, Ismailia, Egypt
                [7 ] Chair of Plant Nutrition, Department of Plant Sciences, Technical University of Munich, Freising-Weihenstephan, Freising, Germany
                Potsdam Institute for Climate Impact Research, GERMANY
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Article
                PONE-D-18-32847
                10.1371/journal.pone.0212294
                6402754
                30840631
                b6701269-373c-493e-8b13-917c9fa1e536
                © 2019 El-Hendawy et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                Page count
                Figures: 6, Tables: 8, Pages: 26
                Product
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100011665, Deanship of Scientific Research, King Saud University;
                Award ID: RG-1435-032
                Award Recipient :
                The authors extend their appreciation to the Deanship of Scientific Research at King Saud University for funding this work through Research Group No. (RG-1435-032), and the Researchers Support & Services Unit (RSSU) for their technical support.
                Categories
                Research Article
                Biology and Life Sciences
                Agriculture
                Agronomy
                Biology and Life Sciences
                Organisms
                Eukaryota
                Plants
                Grasses
                Wheat
                Biology and Life Sciences
                Plant Science
                Plant Anatomy
                Leaves
                Biology and Life Sciences
                Agriculture
                Crop Science
                Crops
                Cereal Crops
                Ecology and Environmental Sciences
                Natural Resources
                Water Resources
                Biology and Life Sciences
                Agriculture
                Agricultural Methods
                Agricultural Irrigation
                Biology and Life Sciences
                Plant Science
                Plant Anatomy
                Seeds
                Biology and Life Sciences
                Agriculture
                Crop Science
                Crops
                Custom metadata
                All relevant data are within the manuscript and its Supporting Information files.

                Uncategorized

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