The study investigated the green and chemical approaches for the preparation of Zn nanoparticles and their effect on the growth of okra plants under saline conditions. The leaf extract of Sorghum bicolor L. was used for the green synthesis of zinc nanoparticles (Zn-GNPs). Zinc nanoparticles (Zn-NPs) were also produced by the co-precipitation method (Zn-CNPs). The synthesized NPs were characterized by UV-visible spectroscopy, X-ray diffraction (XRD) and Fourier-transform infrared spectroscopy (FTIR) and were applied foliarly in the range of 0.1%, 0.2%, 0.3% on okra plants. A marked increase in the shoot and root fresh and dry weight (g) and chlorophyll contents were observed under normal and saline conditions. An increase in antioxidant activity was observed under saline conditions. However, the foliar application of 0.3% Zn-GNPs was helpful in the regulation of the antioxidant defense system under a saline environment. Based on the results, it can be concluded that the use of Zn-GNPs is the most promising eco-friendly approach in mitigating salinity stress.

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.

Nanomaterials (NMs) are the leading edge as an amazing class of materials that consists of at least one dimension in the range of 1–100 nm. NMs can be made with exceptional magnetic, electrical, and catalytic properties different from their bulk counterparts. We summarized unique features of NMs, their synthesis, and advances in agri-nanotechnology and cutting-edge nanobionics. The review describes advances in NMs including their applications, dosimetry to ensure biosafety, remote sensing of agro-forestry fields, nanofertilizers, and nanopesticides, and avoid post-harvest losses, gene delivery, and nanobionics. Tree nanobionics has enabled the synthesis and delivery of nanosensors, which enhance the rate of photosynthesis, detection of pathogens, and poisonous residues to ensure biosafety and biomass accumulation. Finally, we conclude by discussing challenges, future perspectives, and agro-ecological risks of using NMs.