Comparative Yield Response of Cereal Crops to Water Stress Timing

Thesis Abstract

In the context of increasing rainfall variability and the rising frequency of terminal droughts, cereal crop production faces significant yield losses due to water stress at critical growth stages; understanding species- and cultivar-specific responses to stress timing is essential for developing resilient cropping systems. This study addresses the gap in cross-species comparability of yield outcomes under defined irrigation withdrawal schedules by examining how timing of water limitation influences yield components across major cereal crops. The aim is to quantify and compare yield responses to water stress timing among wheat (Triticum aestivum), maize (Zea mays), and barley (Hordeum vulgare), and to identify physiological and phenological traits that mediate differential sensitivity. Specific objectives are to (i) characterize growth-stage-specific yield losses associated with early-vegetative, booting, anthesis, and grain-filling drought stress; (ii) compare stomatal conductance, leaf water potential, and non-structural carbohydrate dynamics as mechanistic indicators of stress timing effects; (iii) evaluate genotype-by-environment interactions using multiple commercial cultivars per species; and (iv) develop a predictive hierarchy model for yield under intermittent drought scenarios. The methodology employs a controlled field experiment in a randomized complete block design with split-plot arrangements replicated thrice across two locations representing distinct soil textures and rainfall regimes. A total of 9 cultivars per species (27 treatments) are subjected to four irrigation regimes well-watered (control), and stress imposed at early vegetative, booting, anthesis, or grain-filling stages, each maintained for 10 days or until the onset of irreversible senescence depending on crop. The population comprises commercially important cultivars grown under standard agronomic practices. Data collection instruments include soil moisture sensors (TDR and capacitance probes), portable sap flow meters, chlorophyll fluorescence meters, portable photosynthemeters to measure net photosynthesis, and lysimeters for precise evapotranspiration estimates. Harvest measurements target yield and yield components grain weight, 1000-kernel weight, kernel number, aboveground biomass, harvest index, and post-anthesis carbohydrate partitioning. Physiological sampling collects leaf water potential, stomatal conductance, and non-structural carbohydrate concentrations at key growth stages. Data analysis uses mixed-effects models to partition fixed effects of stress timing and cultivar, with random effects for location and block, supplemented by regression analyses to link physiological indicators to yield components. ANOVA is applied to test treatment differences, with post hoc Tukey tests for pairwise comparisons. A structural equation modeling approach may be used to elucidate causal pathways from stress timing through physiological responses to yield. Model diagnostics will include residual analysis, Akaike information criterion, and cross-location validation. Theoretical grounding draws on the source-sink theory and the stress timing framework, integrating traits from the drought tolerance paradigm and the boundary layer theory to interpret stomatal and photosynthetic responses under transient drought. Expected findings anticipate that late-season stress (grain-filling) will cause the largest yield penalties in maize, while wheat and barley may show comparatively greater resilience during early-vegetative stress due to more effective carbohydrate remobilization and stay-green traits. Distinct cultivar-level differences are expected, with some genotypes demonstrating reduced stomatal aperture and maintained photosynthesis under early stress, contributing to smaller yield losses. The study will identify physiological indicators most predictive of yield decline under each stress timing, enabling development of a predictive model for yield under variable irrigation regimes. This research contributes to knowledge by providing a cross-species, timing-focused comparative lens on drought sensitivity that informs breeding strategies and irrigation scheduling for cereals under climate variability. It offers a parsimonious predictive framework linking stress timing to yield via measurable physiological traits, enabling agronomic decision-support tools for farmers and policy-relevant recommendations for water-limited environments. Practical recommendations include selecting stress-tolerant cultivars with favorable phenology for specific regions, optimizing irrigation timing to mitigate grain-fill losses, and integrating stay-green and carbohydrate remobilization traits into breeding programs to enhance resilience to asynchronous rainfall patterns.