Climate change is shifting agricultural production, which could impact the economic and cultural contexts of the oilseed industry, including sesame. Environmental threats (biotic and abiotic stresses) affect sesame production and thus yield (especially oil content). However, few studies have investigated the genetic enhancement, quality improvement, or the underlying mechanisms of stress tolerance in sesame. This study reveals the challenges faced by farmers/researchers growing sesame crops and the potential genetic and genomic resources for addressing the threats, including: (1) developing sesame varieties that tolerate phyllody, root rot disease, and waterlogging; (2) investigating beneficial agro-morphological traits, such as determinate growth, prostrate habit, and delayed response to seed shattering; (3) using wild relatives of sesame for wide hybridization; and (4) advancing existing strategies to maintain sesame production under changing climatic conditions. Future research programs need to add technologies and develop the best research strategies for economic and sustainable development.

Mainstreaming biodiversity in production landscapes ensures conservation and sustainable use of agricultural biodiversity, the key objectives of the Convention on Biological Diversity (CBD) and the projects supported by the United Nations Environment Program (UNEP) Global Environment Facility (GEF). Mainstreaming integrates biodiversity in existing or new programs and policies, both cross-sectoral and sector-specific. The conventional model of agricultural production with limited diversity in production systems and use of high chemical input has taught us a valuable lesson as it is adversely impacting the environment, the essential ecosystem services, the soil health and the long term sustainability of our food systems. Using a qualitative participant observation approach, our study investigated four distinct traditional Indian production landscapes to gage (i) the farming communities’ response to institutional policies, programs and agricultural biodiversity-related activities in traditional Indian production landscapes and (ii) opportunities and challenges for sustainable development in smallholder traditional Indian farming systems. Results indicate that the top-down decision-making regime is the least effective towards achieving sustainable development in traditional Indian farming landscapes and that farmers’ experiential knowledge on participatory biodiversity management, maintenance and use for sustainable development are of critical importance to India’s agriculture and economy. Reclaiming agriculture’s spiritual roots through organic farming and locally grown food emerged as key, including the need for designing and implementing a more sovereign food system. Revisiting traditional smallholder farming under the COVID-19 pandemic and lessons learned for repurposing India’s agricultural policy are also highlighted.

Amaranth and buckwheat are two pseudo-cereals preferred for their high nutritional value, are gluten free and carry religious importance as fasting food. Germplasm resources are the reservoir of diversity for different traits, including nutritional characteristics. These resources must be evaluated to utilize their potential in crop improvement programs. However, conventional methods are labor-, cost- and time-intensive and prone to handling errors when applied to large samples. NIRS-based machine learning to predict different nutritional traits is applied in different food crops for multiple traits. NIRS prediction models are developed in this study using the mPLS regression technique for oil, protein, fatty acids and essential amino acid estimation in amaranth and buckwheat. Good RSQ external (power of determination) values were obtained for the above traits ranging from 0.72 to 0.929. Ratio performance deviation (RPD) value for most of the traits ranged between 2 and 3, except for valine (1.88) and methionine (3.55), indicating good prediction capabilities in the developed model. These prediction models were utilized in screening the germplasm of amaranth and buckwheat; the results obtained were in good agreement and confirmed the applicability of developed models. It will enable the identification of a trait-specific germplasm as a potential gene source and aid in crop improvement programs.

Sesame, one of the ancient oil crops, is an important oilseed due to its nutritionally rich seeds with high protein content. Genomic scale information for sesame has become available in the public databases in recent years. The genes and their families involved in oil biosynthesis in sesame are less studied than in other oilseed crops. Therefore, we retrieved a total of 69 genes and their translated amino acid sequences, associated with gene families linked to the oil biosynthetic pathway. Genome-wide in silico mining helped identify key regulatory genes for oil biosynthesis, though the findings require functional validation. Comparing sequences of the SiSAD (stearoyl-acyl carrier protein (ACP)-desaturase) coding genes with known SADs helped identify two SiSAD family members that may be palmitoyl-ACP-specific. Based on homology with lysophosphatidic acid acyltransferase (LPAAT) sequences, an uncharacterized gene has been identified as SiLPAAT1. Identified key regulatory genes associated with high oil content were also validated using publicly available transcriptome datasets of genotypes contrasting for oil content at different developmental stages. Our study provides evidence that a longer duration of active oil biosynthesis is crucial for high oil accumulation during seed development. This underscores the importance of early onset of oil biosynthesis in developing seeds. Up-regulating, identified key regulatory genes of oil biosynthesis during early onset of seed development, should help increase oil yields.

Sesame (Sesamum indicum L.) is a globally cultivated oilseed crop renowned for its historical significance and widespread growth in tropical and subtropical regions. With notable nutritional and medicinal attributes, sesame has shown promising effects in combating malnutrition cancer, diabetes, and other diseases like cardiovascular problems. However, sesame production faces significant challenges from environmental threats such as charcoal rot, drought, salinity, and waterlogging stress, resulting in economic losses for farmers. The scarcity of information on stress-resistance genes and pathways exacerbates these challenges. Despite its immense importance, there is currently no platform available to provide comprehensive information on sesame, which significantly hinders the mining of various stress-associated genes and the molecular breeding of sesame. To address this gap, here a free, web-accessible, and user-friendly genomic web resource (SesameGWR, http://backlin.cabgrid.res.in/sesameGWR/) has been developed This platform provides key insights into differentially expressed genes, transcription factors, miRNAs, and molecular markers like simple sequence repeats, single nucleotide polymorphisms, and insertions and deletions associated with both biotic and abiotic stresses.. The functional genomics information and annotations embedded in this web resource were predicted through RNA-seq data analysis. Considering the impact of climate change and the nutritional and medicinal importance of sesame, this study is of utmost importance in understanding stress responses. SesameGWR will serve as a valuable tool for developing climate-resilient sesame varieties, thereby enhancing the productivity of this ancient oilseed crop.

A field experiment was undertaken during the Rabi seasons of 2019-20 and 2021-22 at organic farm of Amity Institute of Organic Agriculture, Amity University, Noida, Uttar Pradesh, India, for the optimization of the sowing time period to reduce the effect of heat stress on Indian mustard (Brassica juncea L.) for increasing productivity. 32 Indian mustard germplasms were sown at three different time periods viz., the last week of September, the last fortnight of October, and the second week of November. Our results revealed that the mustard crop showed a substantial increase in yield supporting characters such as the number of siliqua and seeds per siliqua when sown at last week of September as compared to the second week of October, whereas the late sown crop resulted in less yield due to the heat stress faced by crop during the anthesis stage as compared to early and optimum sowing. The mean seed yield per plant showed a positive correlation with mean test weight. We established the positive effect of early sowing over optimal and late sowing in Indian mustard; further, we found a few mustard accessions were able to resist different climatic conditions. The mustard germplasm accessions IC296688, IC296703, IC296732, IC305130, IC401575, IC426385, and IC589669 were high yielding among all the accessions and can be considered as heat stress tolerant.