Unlocking chickpea flour potential: AI-powered prediction for quality assessment and compositional characterisation.

The growing demand for sustainable, nutritious, and environmentally friendly food sources has placed chickpea flour as a vital component in the global shift to plant-based diets. However, the inherent variability in the composition of chickpea flour, influenced by genetic diversity, environmental conditions, and processing techniques, poses significant challenges to standardisation and quality control. This study explores the integration of deep learning models with near-infrared (NIR) spectroscopy to improve the accuracy and efficiency of chickpea flour quality assessment.

High-throughput chlorophyll fluorescence screening of Setaria viridis for mutants with altered CO compensation points.

To assist with efforts to engineer a C4 photosynthetic pathway into rice, forward-genetic approaches are being used to identify the genes modulating key C4 traits. Currently, a major challenge is how to screen for a variety of different traits in a high-throughput manner. Here we describe a method for identifying C4 mutant plants with increased CO2 compensation points.

High Throughput Determination of Plant Height, Ground Cover, and Above-Ground Biomass in Wheat with LiDAR.

Crop improvement efforts are targeting increased above-ground biomass and radiation-use efficiency as drivers for greater yield. Early ground cover and canopy height contribute to biomass production, but manual measurements of these traits, and in particular above-ground biomass, are slow and labor-intensive, more so when made at multiple developmental stages. These constraints limit the ability to capture these data in a temporal fashion, hampering insights that could be gained from multi-dimensional data.

Leaf Photosynthetic Parameters Related to Biomass Accumulation in a Global Rice Diversity Survey.

Mining natural variations is a major approach to identify new options to improve crop light use efficiency. So far, successes in identifying photosynthetic parameters positively related to crop biomass accumulation through this approach are scarce, possibly due to the earlier emphasis on properties related to leaf instead of canopy photosynthetic efficiency. This study aims to uncover rice () natural variations to identify leaf physiological parameters that are highly correlated with biomass accumulation, a surrogate of canopy photosynthesis.

Diurnal Solar Energy Conversion and Photoprotection in Rice Canopies.

Genetic improvement of photosynthetic performance of cereal crops and increasing the efficiency with which solar radiation is converted into biomass has recently become a major focus for crop physiologists and breeders. The pulse amplitude modulated chlorophyll fluorescence technique (PAM) allows quantitative leaf level monitoring of the utilization of energy for photochemical light conversion and photoprotection in natural environments, potentially over the entire crop lifecycle. Here, the diurnal relationship between electron transport rate (ETR) and irradiance was measured in five cultivars of rice (Oryza sativa) in canopy conditions with PAM fluorescence under natural solar radiation.

Using Phenomic Analysis of Photosynthetic Function for Abiotic Stress Response Gene Discovery.

Monitoring the photosynthetic performance of plants is a major key to understanding how plants adapt to their growth conditions. Stress tolerance traits have a high genetic complexity as plants are constantly, and unavoidably, exposed to numerous stress factors, which limits their growth rates in the natural environment. , with its broad genetic diversity and wide climatic range, has been shown to successfully adapt to stressful conditions to ensure the completion of its life cycle.

Phenomic Approaches and Tools for Phytopathologists.

Plant phenomics approaches aim to measure traits such as growth, performance, and composition of plants using a suite of noninvasive technologies. The goal is to link phenotypic traits to the genetic information for particular genotypes, thus creating the bridge between the phenome and genome. Application of sensing technologies for detecting specific phenotypic reactions occurring during plant-pathogen interaction offers new opportunities for elucidating the physiological mechanisms that link pathogen infection and disease symptoms in the host, and also provides a faster approach in the selection of genetic material that is resistant to specific pathogens or strains.

Digital imaging approaches for phenotyping whole plant nitrogen and phosphorus response in Brachypodium distachyon.

This work evaluates the phenotypic response of the model grass (Brachypodium distachyon (L.) P. Beauv.

TraitCapture: genomic and environment modelling of plant phenomic data.

Agriculture requires a second green revolution to provide increased food, fodder, fiber, fuel and soil fertility for a growing population while being more resilient to extreme weather on finite land, water, and nutrient resources. Advances in phenomics, genomics and environmental control/sensing can now be used to directly select yield and resilience traits from large collections of germplasm if software can integrate among the technologies. Traits could be Captured throughout development and across environments from multi-dimensional phenotypes, by applying Genome Wide Association Studies (GWAS) to identify causal genes and background variation and functional structural plant models (FSPMs) to predict plant growth and reproduction in target environments.

Infrared thermography in plant phenotyping for salinity tolerance.

The recent advances made in the use of infrared thermal imaging (thermography) as a non-invasive, high-throughput technique for the screening of salinity tolerance in plants is reviewed. Taking wheat seedlings as an example, the methods and protocols used to impose a homogeneous salt stress to a large number of genotypes, as well as capturing infrared images of these genotypes and automatically processing the images are described in detail in this chapter. We also present the source code of the Matlab program applied to automatically identify plants and batch process IR images.

Down-regulation of Glucan, Water-Dikinase activity in wheat endosperm increases vegetative biomass and yield.

A novel mechanism for increasing vegetative biomass and grain yield has been identified in wheat (Triticum aestivum). RNAi-mediated down-regulation of Glucan, Water-Dikinase (GWD), the primary enzyme required for starch phosphorylation, under the control of an endosperm-specific promoter, resulted in a decrease in starch phosphate content and an increase in grain size. Unexpectedly, consistent increases in vegetative biomass and grain yield were observed in subsequent generations.

A novel mesh processing based technique for 3D plant analysis.

Background: In recent years, imaging based, automated, non-invasive, and non-destructive high-throughput plant phenotyping platforms have become popular tools for plant biology, underpinning the field of plant phenomics. Such platforms acquire and record large amounts of raw data that must be accurately and robustly calibrated, reconstructed, and analysed, requiring the development of sophisticated image understanding and quantification algorithms. The raw data can be processed in different ways, and the past few years have seen the emergence of two main approaches: 2D image processing and 3D mesh processing algorithms.

Growth of the C4 dicot Flaveria bidentis: photosynthetic acclimation to low light through shifts in leaf anatomy and biochemistry.

In C(4) plants, acclimation to growth at low irradiance by means of anatomical and biochemical changes to leaf tissue is considered to be limited by the need for a close interaction and coordination between bundle sheath and mesophyll cells. Here differences in relative growth rate (RGR), gas exchange, carbon isotope discrimination, photosynthetic enzyme activity, and leaf anatomy in the C(4) dicot Flaveria bidentis grown at a low (LI; 150 micromol quanta m(2) s(-1)) and medium (MI; 500 micromol quanta m(2) s(-1)) irradiance and with a 12 h photoperiod over 36 d were examined. RGRs measured using a 3D non-destructive imaging technique were consistently higher in MI plants.

New phenotyping methods for screening wheat and barley for beneficial responses to water deficit.

This review considers stomatal conductance as an indicator of genotypic differences in the growth response to water stress. The benefits of using stomatal conductance are compared with photosynthetic rate and other indicators of genetic variation in water stress tolerance, along with the use of modern phenomics technologies. Various treatments for screening for genetic diversity in response to water deficit in controlled environments are considered.

A new screening method for osmotic component of salinity tolerance in cereals using infrared thermography.

A high-throughput, automated image analysis protocol for the capture, identification and analysis of thermal images acquired with a long-wave infrared (IR) camera was developed to quantify the osmotic stress response of wheat and barley to salinity. There was a strong curvilinear relationship between direct measurements of stomatal conductance and leaf temperature of barley grown in a range of salt concentrations. This indicated that thermography accurately reflected the physiological status of salt-stressed barley seedlings.