Optimizing Nutrient Use Efficiency and Chlorophyll Fluorescence Metrics in Maize Under Variable Water Availability Using Remote Sensing and Genotype-by-Environment Interaction Analysis

Project Abstract

Optimizing nutrient use efficiency (NUE) and chlorophyll fluorescence metrics in maize under variable water availability will be advanced through an integrative framework that combines high-throughput remote sensing, physiological phenotyping, and genotype-by-environment interaction (GxE) analysis. This study aims to quantify how water stress modulates NUE components, including uptake efficiency, utilization efficiency, and internal translocation efficiency, and to relate these to non-destructive chlorophyll fluorescence indices (e.g., Fv/Fm, NPQ, qP) as proxy indicators of photosystem II efficiency and photoprotective responses. By deploying proximal and aerial hyperspectral imaging alongside conventional agronomic measurements across a diverse panel of maize genotypes subjected to gradient irrigation regimes in multiple environments, we will establish robust trait associations and temporal dynamics of NUE under drought and intermittent rainfall patterns. A key objective is to develop predictive models that integrate remote sensing-derived vegetation indices, pigment composition proxies, and fluorescence-derived stress signatures to classify tolerant versus sensitive genotypes and to forecast grain yield potential under future climate scenarios. The research will implement a nested experimental design with replicated genotypes across factorial water treatments, enabling precise partitioning of genetic, environmental, and GxE components. Advanced statistical methods, including mixed models, multi-trait genomic selection frameworks, and reaction norm analysis, will be used to identify stable NUE-associated traits and their fluorescence correlates across environments. We will investigate the mechanistic links between nitrogen assimilation pathways and photosynthetic regulation under water limitation, examining gene expression patterns of key NUE and chlorophyll fluorescence-related genes through targeted transcriptomics in a subset of lines. The sustainability dimension will be addressed by evaluating water-use efficiency (WUE) and nitrogen-use efficiency under deficit irrigation, with economic thresholds established for potential adoption by breeding programs and farmers. Expected outcomes include (i) a set of high-confidence phenotypic and spectral biomarkers for NUE under drought, (ii) validated models predicting maize yield and NUE under variable hydric regimes, (iii) identification of genotypes with favorable GxE profiles that combine high NUE with resilient photosynthetic performance, and (iv) actionable guidelines for integrating remote sensing tools into breeding pipelines for climate-resilient maize. The study will contribute to a deeper understanding of how water stress interacts with nitrogen dynamics to shape photosynthetic efficiency, enabling targeted selection strategies that balance nutrient stewardship and resource conservation. By bridging physiological insights with scalable sensing technologies, the project aspires to accelerate the development of maize cultivars capable of maintaining productivity with reduced fertilizer inputs in water-limited ecosystems.

Project Overview

What This Project Is About

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A simple, real-world look at how maize plants use nutrients efficiently under different water conditions, using everyday tools like photos and simple measurements to see how plants stay healthy.

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The Problem It Addresses

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A common farming challenge is keeping maize healthy when water is scarce or inconsistent. Traditional methods may waste fertilizer or miss early stress signals. This project seeks practical ways to combine easy plant health checks with basic technology to guide better watering and fertilization decisions.

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Objectives of the Project

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1. Identify simple indicators that show when maize plants are efficiently using nutrients.
2. Explore how varying water affects these indicators.
3. Introduce a user-friendly approach to monitor plant health over time.
4. Provide guidelines for better nutrient and water management in maize farming.

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What You Will Do Step by Step

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1. Review basic literature on plant health signals and nutrient use in maize.
2. Collect soil and plant health data under different water levels on a small farm or experimental plot.
3. Use simple tools (photos, basic sensors) to measure plant responses.
4. Analyze trends to see which signals best reflect nutrient use under water stress.
5. Summarize findings into practical recommendations for growers.

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Expected Outcome

Clear, easy-to-use insights on how to monitor maize nutrition and water status, with practical steps for farmers to optimize inputs and reduce waste.