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Water Stress Alters Morphophysiological, Grain Quality and Vegetation Indices of Soybean Cultivars.

Cássio Jardim TavaresWalter Quadros Ribeiro JuniorMaria Lucrecia Gerosa RamosLucas Felisberto PereiraRaphael Augusto das Chagas Noqueli CasariAndré Ferreira PereiraCarlos Antonio Ferreira de SousaAnderson Rodrigo da SilvaSebastião Pedro da Silva NetoLiliane Marcia Mertz Henning
Published in: Plants (Basel, Switzerland) (2022)
Rainfall is among the climatic factors that most affect production, as in the Brazilian Cerrado. Non-destructive and automated phenotyping methods are fast and efficient for genotype selection. The objective of this work was to evaluate, under field conditions, the morphophysiological changes, yield, and grain quality of soybean ( Glycine max L. Merrill) under water stress in the Brazilian Cerrado. The plots comprised six soybean cultivars and the subplots of four water regimes, corresponding to 31, 44, 64 and 100% of crop evapotranspiration replacement. The experiments were conducted from May to September 2018 and 2019. An irrigation system with a bar of sprinklers with different flow rates was used. Gas exchange, vegetation indices (measured using a hyperspectral sensor embedded in a drone), yield and grain quality were evaluated. Water stress had different effects on gas exchange, vegetation indices, grain yield and chemical composition among the cultivars. Embrapa cultivar BRS 7280 Roundup ready (RR) and Nidera cultivar NA 5909 RG (glyphosate resistant) are yield stable and have a greater tolerance to drought. BRS 7280RR showed a higher tolerance to drought and higher water use efficiency (WUE) than all other tested cultivars. Vegetation indices, such as the NDVI (Normalized Difference Vegetation Index), correlated with the morphophysiological traits, such as plant height, were the most responsive variables to water stress. The NDVI can be used to predict soybean yield as a tool in a selection program under drought.
Keyphrases
  • climate change
  • quality improvement
  • heat stress
  • high throughput
  • machine learning
  • stress induced
  • gene expression
  • deep learning
  • genome wide
  • room temperature
  • physical activity
  • carbon dioxide