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article · Cogent Food & Agriculture

Leaf reflectance and physiological attributes monitoring differentiate rice cultivars under drought-stress and non-stress conditions

20253 citationsOpen accessUniversity of Lomé

Abstract

Rice production in Africa is unambiguously hampered by drought. This study aimed to monitor the efficiency of physiological traits (stomatal conductance (gsw), transpiration rate (E)), and leaf-reflectance (NDVI and RDVI) at vegetative (VS) and reproductive (RS) stages for selection of drought-tolerant genotypes. To achieve these objectives, we screened 14 rice genotypes under drought-stress and non-stress conditions in the greenhouse. At VS-drought-stress, the relative-gsw and relative-E consistently showed efficiency in differentiating drought-tolerant genotypes APO and UPLR-17 from the drought-sensitive ones at 11-, 18- and 27-days during VS-drought-stress, while NDVI, CRI1 and CRI2 at 18- and 27-days. At RS-drought-stress, genotypes APO and UPLR-17 were selected as drought-tolerant genotypes based on the multi-trait-genotype-ideotype-distance-index (MGIDI) confirming the selection at 11-, 18- and 27-days during VS-drought-stress. This consistency in selecting APO and UPLR-17 as drought-tolerant genotypes at both VS and RS proved the efficiency of gsw, E, NDVI, RDVI, CRI1 and CRI2 in selecting for drought-tolerant varieties at VS. Genotypes UPLR-17 and APO consistently showed homozygosity status for the favorable alleles G, A, G and C for drought-tolerant QTLs DTY1.1 (snpOS00400), DTY1.1 (snpOS00402), DTY1.1 (snpOS00408) and DTY12.1 (snpOS00483), respectively, confirming their drought tolerance status. At RS, with GYP recorded positive and significant correlation with RDVI, while regression analysis revealed that 34% of the variability in GYP is explained by RDVI. The regression analysis coupled with correlation analysis between LDS, DTF, RDVI and GYP implied that these traits can be used as predictors of GYP at RS-drought-stress. While gsw, E and NDVI are recommended for monitoring during VS-drought-stress screening.

Research topics

  • Leaf Properties and Growth Measurement
  • Remote Sensing in Agriculture
  • Rice Cultivation and Yield Improvement

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DOI: 10.1080/23311932.2025.2453086

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