Use of Phenomics for Differentiation of Mungbean (Vigna radiata L. Wilczek) Genotypes Varying in Growth Rates Per Unit of Water

Use of low cost near-infrared spectroscopy, to predict pasting properties of high quality cassava flour

Determination of pasting properties of high quality cassava flour using rapid visco analyzer is expensive and time consuming. The use of mobile near infrared spectroscopy (SCiO™) is an alternative high throughput phenotyping technology for predicting pasting properties of high quality cassava flour traits. However, model development and validation are necessary to verify that reasonable expectations are established for the accuracy of a prediction model. In the context of an ongoing breeding effort, we investigated the use of an inexpensive, portable spectrometer that only records a portion (740-1070 nm) of the whole NIR spectrum to predict cassava pasting properties. Three machine-learning models, namely glmnet, lm, and gbm, implemented in the Caret package in R statistical program, were solely evaluated. Based on calibration statistics (R2, RMSE and MAE), we found that model calibrations using glmnet provided the best model for breakdown viscosity, peak viscosity and pasting temperature. The glmnet model using the first derivative, peak viscosity had calibration and validation accuracy of R2 = 0.56 and R2 = 0.51 respectively while breakdown had calibration and validation accuracy of R2 = 0.66 and R2 = 0.66 respectively. We also found out that stacking of pre-treatments with Moving Average, Savitzky Golay, First Derivative, Second derivative and Standard Normal variate using glmnet model resulted in calibration and validation accuracy of R2 = 0.65 and R2 = 0.64 respectively for pasting temperature. The developed calibration model predicted the pasting properties of HQCF with sufficient accuracy for screening purposes. Therefore, SCiO™ can be reliably deployed in screening early-generation breeding materials for pasting properties.

Capturing crop adaptation to abiotic stress using image-based technologies

Farmers and breeders aim to improve crop responses to abiotic stresses and secure yield under adverse environmental conditions. To achieve this goal and select the most resilient genotypes, plant breeders and researchers rely on phenotyping to quantify crop responses to abiotic stress. Recent advances in imaging technologies allow researchers to collect physiological data non-destructively and throughout time, making it possible to dissect complex plant responses into quantifiable traits. The use of image-based technologies enables the quantification of crop responses to stress in both controlled environmental conditions and field trials. This paper summarizes phenotyping imaging technologies (RGB, multispectral and hyperspectral sensors, among others) that have been used to assess different abiotic stresses including salinity, drought and nitrogen deficiency, while discussing their advantages and drawbacks. We present a detailed review of traits involved in abiotic tolerance, which have been quantified by a range of imaging sensors under high-throughput phenotyping facilities or using unmanned aerial vehicles in the field. We also provide an up-to-date compilation of spectral tolerance indices and discuss the progress and challenges in machine learning, including supervised and unsupervised models as well as deep learning.

The Response of Cowpea (Vigna unguiculata) Plants to Three Abiotic Stresses Applied with Increasing Intensity: Hypoxia, Salinity, and Water Deficit

Exposing plants to gradually increasing stress and to abiotic shock represents two different phenomena. The knowledge on plants’ responses following gradually increasing stress is limited, as many of the studies are focused on abiotic shock responses. We aimed to investigate how cowpea (Vigna unguiculata (L.) Walp.) plants respond to three common agricultural abiotic stresses: hypoxia (applied with the increasing time of exposure to nitrogen gas), salinity (gradually increasing NaCl concentration), and water deficit (gradual decrease in water supply). We hypothesized that the cowpea plants would increase in tolerance to these three abiotic stresses when their intensities rose in a stepwise manner. Following two weeks of treatments, leaf and whole-plant fresh weights declined, soluble sugar levels in leaves decreased, and lipid peroxidation of leaves and roots and the levels of leaf electrolyte leakage increased. Polyphenol oxidase activity in both roots and leaves exhibited a marked increase as compared to catalase and peroxidase. Leaf flavonoid content decreased considerably after hypoxia, while it increased under water deficit treatment. NO emission rates after 3 h in the hypoxically treated plants were similar to the controls, while the other two treatments resulted in lower values of NO production, and these levels further decreased with time. The degree of these changes was dependent on the type of treatment, and the observed effects were more substantial in leaves than in roots. In summary, the responses of cowpea plants to abiotic stress depend on the type and the degree of stress applied and the plant organs.

The Adaptation and Tolerance of Major Cereals and Legumes to Important Abiotic Stresses

Abiotic stresses, including drought, extreme temperatures, salinity, and waterlogging, are the major constraints in crop production. These abiotic stresses are likely to be amplified by climate change with varying temporal and spatial dimensions across the globe. The knowledge about the effects of abiotic stressors on major cereal and legume crops is essential for effective management in unfavorable agro-ecologies. These crops are critical components of cropping systems and the daily diets of millions across the globe. Major cereals like rice, wheat, and maize are highly vulnerable to abiotic stresses, while many grain legumes are grown in abiotic stress-prone areas. Despite extensive investigations, abiotic stress tolerance in crop plants is not fully understood. Current insights into the abiotic stress responses of plants have shown the potential to improve crop tolerance to abiotic stresses. Studies aimed at stress tolerance mechanisms have resulted in the elucidation of traits associated with tolerance in plants, in addition to the molecular control of stress-responsive genes. Some of these studies have paved the way for new opportunities to address the molecular basis of stress responses in plants and identify novel traits and associated genes for the genetic improvement of crop plants. The present review examines the responses of crops under abiotic stresses in terms of changes in morphology, physiology, and biochemistry, focusing on major cereals and legume crops. It also explores emerging opportunities to accelerate our efforts to identify desired traits and genes associated with stress tolerance.