Leveraging machine learning to unravel the impact of cadmium stress on goji berry micropropagation.

This study investigates the influence of cadmium (Cd) stress on the micropropagation of Goji Berry (Lycium barbarum L.) across three distinct genotypes (ERU, NQ1, NQ7), employing an array of machine learning (ML) algorithms, including Multilayer Perceptron (MLP), Support Vector Machines (SVM), Random Forest (RF), Gaussian Process (GP), and Extreme Gradient Boosting (XGBoost). The primary motivation is to elucidate genotype-specific responses to Cd stress, which poses significant challenges to agricultural productivity and food safety due to its toxicity.

Advanced Biotechnological Interventions in Mitigating Drought Stress in Plants.

This comprehensive article critically analyzes the advanced biotechnological strategies to mitigate plant drought stress. It encompasses an in-depth exploration of the latest developments in plant genomics, proteomics, and metabolomics, shedding light on the complex molecular mechanisms that plants employ to combat drought stress. The study also emphasizes the significant advancements in genetic engineering techniques, particularly CRISPR-Cas9 genome editing, which have revolutionized the creation of drought-resistant crop varieties.