Soil salinity is one of the most serious environmental challenges, posing a growing threat to agriculture across the world. Soil salinity has a significant impact on rice growth, development, and production. Hence, improving rice varieties’ resistance to salt stress is a viable solution for meeting global food demand. Adaptation to salt stress is a multifaceted process that involves interacting physiological traits, biochemical or metabolic pathways, and molecular mechanisms. The integration of multi-omics approaches contributes to a better understanding of molecular mechanisms as well as the improvement of salt-resistant and tolerant rice varieties. Firstly, we present a thorough review of current knowledge about salt stress effects on rice and mechanisms behind rice salt tolerance and salt stress signalling. This review focuses on the use of multi-omics approaches to improve next-generation rice breeding for salinity resistance and tolerance, including genomics, transcriptomics, proteomics, metabolomics and phenomics. Integrating multi-omics data effectively is critical to gaining a more comprehensive and in-depth understanding of the molecular pathways, enzyme activity and interacting networks of genes controlling salinity tolerance in rice. The key data mining strategies within the artificial intelligence to analyse big and complex data sets that will allow more accurate prediction of outcomes and modernise traditional breeding programmes and also expedite precision rice breeding such as genetic engineering and genome editing.

Rice is frequently subjected to various environmental stresses, resulting in significant production losses, with drought and salinity are the leading causes of plant damage globally. This study aims to characterize and understand the function of rice high-affinity potassium transporters ( HKTs ) genes in response to salinity stress. Initially, the genome-wide analysis was undertaken to reveal the evolutionarily conserved function of the OsHKT in higher plants. To investigate the transcription level of OsHKT during the vegetative and reproductive stages, two microarray datasets (GSE19024 and GSE3053) were analyzed, and salt-treated samples were subsequently evaluated using real-time PCR. Differentially expressed genes ( DEGs ) were identified from microarray datasets (GSE41650 and GSE14403), followed by constructing a DEG network that highlighted interaction partners of the OsHKTs . Genome mining of rice revealed 9 HKT genes, namely OsHKT1;1–1;5 and OsHKT2;1–2;4 . These genes exhibited a well-conserved domain structure called TrkH . Comprehensive phylogenetic and motif analyses clustered genes encoding HKT proteins into seven monophyletic groups, and the motifs were relatively conserved. Ka/Ks ratios indicated a high degree of purifying selection during evolutionary time. Gene ontology findings suggested the involvement of OsHKT in stress response. Besides, several CRE motifs in the promoter regions of OsHKT have demonstrated their potential roles in abiotic stress responses. Furthermore, we analyzed the top 250 significant DEGs from the two datasets (p-value < 0.05; fold two change ≥ 1 or ≤ − 1) to evaluate the relationship among the DEGs and HKTs . Three co-expressed OsHKT genes were discovered to be upregulated in seedlings under salinity treatment, including OsP5CS2 , OsHAK1 , and OsNHX2 , whereas OsP5CS1 and OsHAK27 were downregulated. The transcripts of OsHKT were found to be differentially expressed in a tissue-specific manner. Analysis of microarray datasets validated by real-time PCR shows that OsHKT1;5 had a higher expression level, followed by OsHKT1;1 , OsHKT1;3 , and OsHKT2;1 after salinity treatment. In addition, several micro-RNA targets in rice HKT genes regulate their expression in response to stress. This study paves the way for future investigation on genes and miRNA-target interaction in plants under environmental stresses, offering potential strategies to enhance stress tolerance in crops via targeted ion transport modification.

A field experiment was carried out at the farmers' field in the Kaliganj upazila for two consecutive years (2021-22, 2022-23). The experiment carried out in a multi-location testing site in the Jhenaidah district, under the Jashore region. The objective of the experiment was to enhance cropping intensity and productivity by incorporating T. Aus into the existing cropping pattern. The current cropping sequence consisted of T. Aman-Mustard-Mungbean, while the suggested cropping sequence included T. Aman- Mustard-Mungbean-T. Aus. The research findings showed that the rice equivalent yield (REY) in the suggested cropping pattern was 21 t ha-1, representing a 31.25% increased over the yield of existing pattern (16 t ha-1). The greater gross return (Tk. ha-1), gross margin (Tk. ha-1), and slightly higher marginal benefit cost ratio obtained from this four-crop-based cropping pattern suggest that the proposed pattern could be recommended for higher productivity and economic benefit in other parts of the Jashore region. Bangladesh J. Nuclear Agric, 38(1): 93-100, 2024

Determining the optimal radiation dose according to its impacts on crop growth characteristics is vital for effective mutation breeding. This study aimed to determine the lethal dose 50 (LD₅₀) and assess the growth performance of gamma-irradiated rice mutants of the Nepali Swarna variety. Rice seeds were exposed to gamma irradiation using Cobalt-60 (⁶⁰Co) at eleven dose levels, ranging from 100 to 600 Grays (Gy) in increments of 50 Gy, along with a non-irradiated control (T0). Germination percentage was assessed after 7 days, while 14 days provided to evaluate shoot length, root length, fresh weight and dry weight of both the shoots and roots, and at 21 days the survival percentage was evaluated. The results showed that gamma irradiation significantly influenced all growth parameters compared to the control. The LD₅₀, based on survival percentage, was determined to be 513 Gy. Growth parameter values exhibited a linear decline with increasing radiation doses, with the most pronounced effects observed at 600 Gy. The findings suggest that 513 Gy can be considered an effective dose for inducing genetic variability in Nepali Swarna, balancing mutation induction with minimal lethal effects for subsequent generations.