Stress breeding is an innovative branch of plant science that has gained significant attention in recent years. This specialized field of plant breeding focuses on developing crop varieties with enhanced resilience to diverse environmental stressors. The primary objective of stress breeding is to address the challenges posed by climate change through the creation and introduction of adaptive crop varieties. By doing so, it aims to ensure food security and maintain agricultural productivity in the face of increasingly unpredictable and extreme weather conditions. This approach represents a proactive strategy to safeguard global food production systems against the backdrop of a rapidly changing climate.

Drought Stress and High-Throughput Analysis for Sorghum

Chinese researchers have developed a high-throughput method for non-destructive estimation of leaf chlorophyll content in sorghum. This method combines RGB, hyperspectral, and fluorescence imaging with sensor fusion and data analysis techniques.

Flowchart showing the steps in hyperspectral image analysis to obtain apparent reflectance spectra. Source: Zhang et al. Source: Zhang et al., 2022

Key findings:

• Multiple linear regression and partial least squares regression (PLSR) models were created to predict chlorophyll content based on image-derived features.
• The PLSR model incorporating all imaging features achieved the highest prediction accuracy (R² of 0.90).
• Including specific leaf weight (SLW) further improved the model’s accuracy.

Multiple linear regression and partial least squares regression - PLSR models were created to predict chlorophyll content based on image-derived features. Source: Zhang et al., 2022

This research demonstrates the potential of high-throughput imaging as a reliable, non-destructive method for real-time chlorophyll content estimation, which can be instrumental in plant phenotyping and precision agriculture.

The sequential steps in segmentation of plant pixels from the background. Source: Zhang et al., 2022

Ten different binary images converted from RGB from 0 to 360 degree. Source: Zhang et al. Source: Zhang et al., 2022

Process flow of image processing steps used in the extraction of plant’s projected chlorophyll content from the fluorescence images. Source: Zhang et al., 2022

Heat Stress Tolerance in Soybean

Another study by Chinese researchers explored enhancing heat stress tolerance in soybean (Glycine max L.) using both conventional and molecular tools.

Areas with extreme heatwaves in China. As global warming in rising, the heat waves in these areas continue to increase, which will have devastating effects on crop production in the coming time. Source: Jianing et al., 2022

Methodologies employed:

• Classical breeding techniques: mass selection, hybridization, and backcrossing
• Molecular techniques: QTL mapping, genetic engineering, CRISPR/Cas9 gene editing, and transcriptome analysis
• Application of phytohormones: ethylene, cytokinin, and melatonin

Effects of heat stress on morphological, physiological, biochemical, and molecular level of soybean. Source: Jianing et al., 2022

Key outcomes:

• Integration of conventional breeding with molecular techniques significantly enhanced soybean’s heat tolerance.
• CRISPR/Cas9 successfully edited key genes like GmHsp90A2 and GmTIP2;6, improving oxidative stress resistance and chlorophyll content under heat stress.
• QTL mapping identified critical genomic regions associated with heat tolerance.
• Phytohormone treatments increased seed germination rates by 15% and enhanced photosynthetic pigment levels by 10% under heat conditions.

Conventional breeding methods for the development of heat-tolerant soybean cultivars. Source: Jianing et al., 2022

These results highlight the potential for developing robust heat-tolerant soybean cultivars to maintain stable yields amid rising global temperatures.

Role of phytohormones in heat tolerance in soybean. Hormones enhance seed germination, stem elongation, and enhanced photosynthetic pigments. Source: Jianing et al., 2022

Role of different genes/proteins in heat tolerance in soybean. Source: Jianing et al., 2022

Salt Stress Tolerance in Chickpea

A research team from Turkey explored the use of artificial neural network (ANN) modelling to understand in vitro induced salt stress tolerance in chickpea (Cicer arietinum L).

Methodology:

• Exposure of chickpea seeds to various NaCl concentrations (6.25 to 125 mM) in Murashige and Skoog (MS) medium
• Recording of germination and growth indices
• Data analysis using multilayer perceptron (MLP) models

Genotypic variation for salinity tolerance in the chickpea Reference Set. Varying levels of salinity tolerance exhibited by different chickpea genotypes. Photo credit: Atieno et al., 2023

Key findings:

• Salt stress negatively impacts all growth indices, with higher NaCl concentrations resulting in more severe reductions.
• Mean germination times for roots and shoots increased significantly under high salt conditions, while mean germination rates decreased.
• MLP models successfully predicted outcomes with high R² values (0.575 to 0.927 for various parameters).
• Elemental analysis showed increased Na and Cl accumulation in plant tissues correlating with higher NaCl levels.

An overview of the impact of different NaCl concentrations on in vitro germination indices of chickpea. Photo credit: Atieno et al., 2023

These findings can be applied to enhance the breeding of salt-tolerant chickpea varieties using AI-based models to predict and validate stress responses.

Impact of different NaCl concentrations on element analysis of chickpea. Photo credit: Atieno et al., 2023

Distribution of predicted values of different growth parameters of chickpea. Photo credit: Atieno et al., 2023

In conclusion, these studies demonstrate the significant progress being made in stress breeding across various crops. By combining traditional breeding techniques with cutting-edge technologies and data analysis, researchers are paving the way for more resilient and productive crops in the face of climate change.