Graphical This review summarized heat stress-mediated morphological and physiological changes in maize and elucidated the molecular mechanisms responsible for maize response to heat stress. Furthermore, plausible approaches to dissecting the regulatory network associated with heat stress response and improving maize adaptation to global warming have been discussed. This figure was made using BioRender.

Gene silencing is a negative feedback mechanism that regulates gene expression to define cell fate and also regulates metabolism and gene expression throughout the life of an organism. In plants, gene silencing occurs via transcriptional gene silencing (TGS) and post-transcriptional gene silencing (PTGS). TGS obscures transcription via the methylation of 5′ untranslated region (5′UTR), whereas PTGS causes the methylation of a coding region to result in transcript degradation. In this review, we summarized the history and molecular mechanisms of gene silencing and underlined its specific role in plant growth and crop production.

Cellulose synthase A genes (CesAs) are responsible for cellulose biosynthesis in plant cell walls. In this study, functions of secondary wall cellulose synthases PtrCesA4, PtrCesA7-A/B and PtrCesA8-A/B were characterized during wood formation in Populus trichocarpa (Torr. & Gray). CesA RNAi knockdown transgenic plants exhibited stunted growth, narrow leaves, early necrosis, reduced stature, collapsed vessels, thinner fiber cell walls and extended fiber lumen diameters. In the RNAi knockdown transgenics, stems exhibited reduced mechanical strength, with reduced modulus of rupture (MOR) and modulus of elasticity (MOE). The reduced mechanical strength may be due to thinner fiber cell walls. Vessels in the xylem of the transgenics were collapsed, indicating that water transport in xylem may be affected and thus causing early necrosis in leaves. A dramatic decrease in cellulose content was observed in the RNAi knockdown transgenics. Compared with wildtype, the cellulose content was significantly decreased in the PtrCesA4, PtrCesA7 and PtrCesA8 RNAi knockdown transgenics. As a result, lignin and xylem contents were proportionally increased. The wood composition changes were confirmed by solid-state NMR, two-dimensional solution-state NMR and sum-frequency-generation vibration (SFG) analyses. Both solid-state nuclear magnetic resonance (NMR) and SFG analyses demonstrated that knockdown of PtrCesAs did not affect cellulose crystallinity index. Our results provided the evidence for the involvement of PtrCesA4, PtrCesA7-A/B and PtrCesA8-A/B in secondary cell wall formation in wood and demonstrated the pleiotropic effects of their perturbations on wood formation.

The fungi present during pile-fermentation of Sichuan dark tea play a pivotal role in the development of its aroma and physical characteristics. Samples of tea leaves were collected on days 0 (YC-raw material), 8 (W1-first turn), 16 (W2-second turn), 24 (W3-third turn), and 32 (W4-out of pile) during pile-fermentation. High-throughput sequencing revealed seven phyla, 22 classes, 41 orders, 85 families, 128 genera, and 184 species of fungi. During fermentation, the fungal diversity index declined from the W1 to W3 stages and then increased exponentially at the W4 stage. A bar plot and heatmap revealed that Aspergillus, Thermomyces, Candida, Debaryomyces, Rasamsonia, Rhizomucor, and Thermoascus were abundant during piling, of which Aspergillus was the most abundant. Cluster analysis revealed that the W4 stage of fermentation is critical for fungal growth, diversity, and the community structure in Sichuan dark tea. This study revealed the role of fungi during pile-fermentation in the development of the essence and physical characteristics of Sichuan dark tea. This study comes under one of the Sustainable Development Goals of United Nations Organization (UNO) to “Establish Good Health and Well-Being.”

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.

Tomato yellow leaf curl virus (TYLCV) is one of the most harmful afflictions in the world that affects tomato growth and production. Six regular antagonistic genes (Ty-1, Ty-2, Ty-3, Ty-4, ty-5, and Ty-6) have been transferred from wild germplasms to commercial cultivars as TYLCV protections. With Ty-1 serving as an appropriate source of TYLCV resistance, only Ty-1, Ty-2, and Ty-3 displayed substantial levels of opposition in a few strains. It has been possible to clone three TYLCV opposition genes (Ty-1/Ty-3, Ty-2, and ty-5) that target three antiviral safety mechanisms. However, it significantly impacts obtaining permanent resistance to TYLCV, trying to maintain opposition whenever possible, and spreading opposition globally. Utilizing novel methods, such as using resistance genes and identifying new resistance resources, protects against TYLCV in tomato production. To facilitate the breeders make an informed decision and testing methods for TYLCV blockage, this study highlights the portrayal of typical obstruction genes, common opposition sources, and subatomic indicators. The main goal is to provide a fictitious starting point for the identification and application of resistance genes as well as the maturation of tomato varieties that are TYLCV-resistant.