ArticleFrontiers in plant science2024
A growing degree day model determines the effect of temperature stress on diverse chickpea genotypes.
Article in Frontiers in plant science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Responses to Induced Passive Heat in Two Local Common Bean (Plants (Basel, Switzerland) · 2025Article
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4 authors.
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Abstract
Chickpeas are a globally crucial agricultural product, currently at risk due to human-induced climate change. There has been little research into the impact of heat stress on chickpea compared to other crops, but it is known that heat stress can cause up to 100% yield loss. This study measures Growing Degree Days (GDD) in chickpeas, utilizing an existing calculation. This formula has been expanded for heat stress, titled Stress Degree Days (SDD), to examine the effects of high temperature stress on commercially important traits such as yield and seed size. Using a multi-environment trial, traits such as time to flowering, and seed size were observed in 148 chickpea cultivars across two sowing times in two different Australian locations (Narrabri in New South Wales, and Kununurra in Western Australia). It was determined that there is a significant correlation between yield, GDD, and SDD at all locations, sowing times, and life stages of the crop. These metrics allowed greater differentiation between environments when compared to a count of the number of calendar days required for each cultivar to reach a set life stage (flowering and maturation), allowing more accurate investigation the impacts of high temperature stress. It was also determined that loss of yield and a decrease in seed size was significantly correlated with high GDD and SDD, though seed size had less environmental plasticity (variability) compared to yield, and therefore higher stability under stress. GDD and SDD were shown to be useful for predicting genotype adaptation to locations and seasons thus providing a basis for varietal recommendations. This information could also be used to breed environment specific cultivars and to understand trait plasticity.
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