Plant-based hydration monitoring for precision nitrogen and irrigation management of cotton under salinity stress

This study is part of a comprehensive research program examining the effects of nitrogen fertilization on cotton physiology and productivity under saline conditions, with parallel investigations focusing on plant growth, biomass accumulation, and yield components. This study investigates the combined effects of soil salinity and nitrogen fertilizer rates on the water-holding capacity of cotton (Gossypium spp.) leaves under soil salinity stress. Cotton, a key global crop, is affected by soil salinity and nitrogen imbalances, which hinder its growth and productivity. A precision agriculture framework was applied, treating each salinity-Nitrogen combination as a unique management zone. Water loss from cotton leaves was measured at three growth stages: the 3-4 true leaves stage, the budding stage, and the flowering stage. Results demonstrated that nitrogen application generally increased water loss from cotton leaves, with higher fertilizer rates leading to reduced water retention. At the flowering stage, water loss ranged from 22.0% to 35.6%, depending on the nitrogen rate and salinity level. Soil salinity significantly influenced leaf water retention, with cotton on strongly saline soils exhibiting lower water loss than plants on non-saline or weakly saline soils. These findings were used to develop a decision matrix linking real-time leaf hydration metrics (potential proxy for canopy temperature or spectral indices) with variable-rate nitrogen and irrigation prescriptions. The study validates the concept of using simple, plant-level physiological traits as inputs for sensor-driven precision management.

Authors

Publication Details

Journal
Springer Link (Chiba Institute of Technology)
Published
2026-04-10
DOI
https://doi.org/10.1051/bioconf/202623100016/pdf
Primary Topic
Irrigation Practices and Water Management
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Plant-based hydration monitoring for precision nitrogen and irrigation management of cotton under salinity stress

Nafisa Gaybullaeva, Shoxnazar To‘xtayev, Nigora Bazarova, Malokhat Jabborova
Springer Link (Chiba Institute of Technology)
Irrigation Practices and Water Management
article

Plant-based hydration monitoring for precision nitrogen and irrigation management of cotton under salinity stress

Nafisa Gaybullaeva, Shoxnazar To‘xtayev, Nigora Bazarova, Malokhat Jabborova
article en

Abstract

This study is part of a comprehensive research program examining the effects of nitrogen fertilization on cotton physiology and productivity under saline conditions, with parallel investigations focusing on plant growth, biomass accumulation, and yield components. This study investigates the combined effects of soil salinity and nitrogen fertilizer rates on the water-holding capacity of cotton (Gossypium spp.) leaves under soil salinity stress. Cotton, a key global crop, is affected by soil salinity and nitrogen imbalances, which hinder its growth and productivity. A precision agriculture framework was applied, treating each salinity-Nitrogen combination as a unique management zone. Water loss from cotton leaves was measured at three growth stages: the 3-4 true leaves stage, the budding stage, and the flowering stage. Results demonstrated that nitrogen application generally increased water loss from cotton leaves, with higher fertilizer rates leading to reduced water retention. At the flowering stage, water loss ranged from 22.0% to 35.6%, depending on the nitrogen rate and salinity level. Soil salinity significantly influenced leaf water retention, with cotton on strongly saline soils exhibiting lower water loss than plants on non-saline or weakly saline soils. These findings were used to develop a decision matrix linking real-time leaf hydration metrics (potential proxy for canopy temperature or spectral indices) with variable-rate nitrogen and irrigation prescriptions. The study validates the concept of using simple, plant-level physiological traits as inputs for sensor-driven precision management.

Springer Link (Chiba Institute of Technology)
Zero hunger
Openalex Percentile: Top 17%
Irrigation Practices and Water Management
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.