Machine and Deep Learning: Artificial Intelligence Application in Biotic and Abiotic Stress Management in Plants.

Biotic and abiotic stresses significantly affect plant fitness, resulting in a serious loss in food production. Biotic and abiotic stresses predominantly affect metabolite biosynthesis, gene and protein expression, and genome variations. However, light doses of stress result in the production of positive attributes in crops, like tolerance to stress and biosynthesis of metabolites, called hormesis. Advancement in artificial intelligence (AI) has enabled the development of high-throughput gadgets such as high-resolution imagery sensors and robotic aerial vehicles, i.e., satellites and unmanned aerial vehicles (UAV), to overcome biotic and abiotic stresses. These High throughput (HTP) gadgets produce accurate but big amounts of data. Significant datasets such as transportable array for remotely sensed agriculture and phenotyping reference platform (TERRA-REF) have been developed to forecast abiotic stresses and early detection of biotic stresses. For accurately measuring the model plant stress, tools like Deep Learning (DL) and Machine Learning (ML) have enabled early detection of desirable traits in a large population of breeding material and mitigate plant stresses. In this review, advanced applications of ML and DL in plant biotic and abiotic stress management have been summarized.

Integrative application of silicon and/or proline improves Sweet corn (Zea mays L. saccharata) production and antioxidant defense system under salt stress condition.

Silicon (Si) and/or proline (Pro) are natural supplements that are considered to induce plants' stress tolerance against various abiotic stresses. Sweet corn (Zea mays L. saccharata) production is severely afflicted by salinity stress. Therefore, two field tests were conducted to evaluate the potential effects of Si and/or Pro (6mM) used as seed soaking (SS) and/or foliar spray (FS) on Sweet corn plant growth and yield, physio-biochemical attributes, and antioxidant defense systems grown in a saline (EC = 7.14dS m-1) soil. The Si and/or Pro significantly increased growth and yield, photosynthetic pigments, free proline, total soluble sugars (TSS), K+/Na+ratios, relative water content (RWC), membrane stability index (MSI), α-Tocopherol (α-TOC), Ascorbate (AsA), glutathione (GSH), enzymatic antioxidants activities and other anatomical features as compared to controls. In contrast, electrolytes, such as SS and/or FS under salt stress compared to controls (SS and FS using tap water) were significantly decreased. The best results were obtained when SS was combined with FS via Si or Pro. These alterations are brought about by the exogenous application of Si and/or Pro rendering these elements potentially useful in aiding sweet corn plants to acclimate successfully to saline soil.