Abstract
Detection of senescence’s dynamics in crop breeding is time consuming and needs considerable details regarding its rate of progression and intensity. Normalized difference red-edge index (NDREI) along with four other spectral vegetative indices (SVIs) derived from unmanned aerial vehicle (UAV) based spatial imagery, were evaluated for rapid and accurate prediction of senescence. For this, 32 selected winter wheat genotypes were planted under full and limited irrigation treatments. Significant variations for all five SVIs: green normalize difference vegetation index (GNDVI), simple ratio (SR), green chlorophyll index (GCI), red-edge chlorophyll index (RECI), and normalized difference red-edge index (NDREI) among genotypes and between treatments, were observed from heading to late grain filling stages. The SVIs showed strong relationship (R2 = 0.69 to 0.78) with handheld measurements of chlorophyll and leaf area index (LAI), while negatively correlated (R2 = 0.75 to 0.77) with canopy temperature (CT) across the treatments. NDREI as a new SVI showed higher correlations with ground data under both treatments, similarly as exhibited by other four SVIs. There were medium to strong correlations (r = 0.23–0.63) among SVIs, thousand grain weight (TGW) and grain yield (GY) under both treatments. Senescence rate was calculated by decreasing values of SVIs from their peak values at heading stage, while variance for senescence rate among genotypes and between treatments could be explained by SVIs variations. Under limited irrigation, 10% to 15% higher senescence rate was detected as compared with full irrigation. Principle component analysis corroborated the negative association of high senescence rate with TGW and GY. Some genotypes, such as Beijing 0045, Nongda 5181, and Zhongmai 175, were selected with low senescence rate, stable TGW and GY in both full and limited irrigation treatments, nearly in accordance with the actual performance of these cultivars in field. Thus, SVIs derived from UAV appeared as a promising tool for rapid and precise estimation of senescence rate at maturation stages.
Highlights
Bread wheat is a major staple crop and provides the calorie needs of one-third of the global population [1]
Correlations were high (R2 = 0.69 to 0.76) between spectral vegetative indices (SVIs) and leaf area index detected from the light ceptometer during the mid and late grain filling stages
Lower correlations under limited irrigation indicated that hand-held data were collected from healthy representative parts, whereas SVIs were derived from whole experimental unit (Figures 4 and 5). These results showed that SVIs derived from the unmanned aerial vehicle (UAV) provided more accurate phenotypic values with much lower cost and less time, compared to data collected by hand-held devices
Summary
Bread wheat is a major staple crop and provides the calorie needs of one-third of the global population [1]. The rate of senescence caused by disintegration of these traits is an important selection criterion that can be used to improve crop adaptability under drought and heat conditions [5]. Senescence is an important time-point which utilizes available resources of the plants for remobilization of nutrients to the sink. It is not a chaotic breakdown, but rather, a complex, dynamic process, generally programmed and driven by genetic and environmental factors [6]. Early senescence caused by maturation due to rapid breakdown of plant tissues and macromolecules, for example chlorophyll, results in significant yield penalties [7,8]. Wheat genotypes with improved stay-green traits have delayed senescence [8,14], and selection for low senescence could improve cultivar’s performance under stressed condition [9,14]
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