The Fall armyworm (FAW), Spodoptera frugiperda (J. E. Smith), is a highly destructive lepidopteran pest known for its extensive feeding on maize (Zea mays L.) and other crops, resulting in a substantial reduction in crop yields. Understanding the metabolic response of maize to FAW infestation is essential for effective pest management and crop protection. Metabolomics, a powerful analytical tool, provides insights into the dynamic changes in maize’s metabolic profile in response to FAW infestation. This review synthesizes recent advancements in metabolomics research focused on elucidating maize’s metabolic responses to FAW and other lepidopteran pests. It discusses the methodologies used in metabolomics studies and highlights significant findings related to the identification of specific metabolites involved in FAW defense mechanisms. Additionally, it explores the roles of various metabolites, including phytohormones, secondary metabolites, and signaling molecules, in mediating plant–FAW interactions. The review also examines potential applications of metabolomics data in developing innovative strategies for integrated pest management and breeding maize cultivars resistant to FAW by identifying key metabolites and associated metabolic pathways involved in plant–FAW interactions. To ensure global food security and maximize the potential of using metabolomics in enhancing maize resistance to FAW infestation, further research integrating metabolomics with other omics techniques and field studies is necessary.

Mungbean (Vigna radiata) is an important short-season legume widely cultivated in Asia, particularly India. It is highly susceptible to bruchids and developing bruchid resistance is an important goal in mungbean breeding programs. In the present study, 52 mungbean genotypes were evaluated for bruchid resistance based on the “no-choice test” and identified two highly resistant genotypes (V2802BG and V2709) with no adult emergence and seed damage. Further, these two resistant genotypes were crossed with six high-yielding bruchid susceptible cultivars (CO 5, CO 6, CO 7, CO 8, VBN 2, and VBN 3), and 12 independent F₁ populations were generated. Of these, one population derived from CO 6 × V2802BG was selected (based on the good combining ability of the parents) and forwarded to later generations to trace the bruchid-resistant lines. A total of 159 F_2:3 families were screened for bruchid resistance, and the results showed that seven families were highly resistant, whereas the remainder were resistant to highly susceptible. Further, those seven families were evaluated in F₄ and F₅ generations. As a result, five highly resistant lines (BSR-GG-1-49-3-1, BSR-GG-1-56-2-2, BSR-GG-1-160-5-3, BSR-GG-1-170-2-4, and BSR-GG-1-198-1-4) with good agronomic performances were identified. The newly developed lines could be tested in multi-location trials and then be utilized as a potential source of genetic material for improving the bruchid resistance in mungbean breeding programs.

Mycotoxins are secondary metabolites produced by fungi, primarily from the genera Aspergillus, Fusarium, Penicillium and Alternaria. The attention is on the existence of mycotoxin compounds in food substances that jeopardize public health and it is directed to systematic regulation to overcome these issues. Pathogenic fungi, including Aspergillus, Penicillium and Fusarium species, infiltrate spice crops during the pre-harvest, postharvest and storage stages. These fungi create toxic secondary metabolites called mycotoxin. The reviews' intend to examine the prevalence, types and levels of mycotoxins commonly found in spices, including aflatoxins, ochratoxin A and fumonisins. The study highlights the factors that influence mycotoxin contamination, such as environmental conditions, agricultural practices and storage methods. Analytical techniques for detecting mycotoxins, including chromatography and immunoassays, are evaluated for efficacy and sensitivity. It also discusses the regulatory frameworks and safety standards established by international bodies like the Codex Alimentarius Commission to mitigate mycotoxin risks. In addition to these regulatory measures, mycotoxin detection needs to be addressed before framing the standards. The preventive strategies and mitigation measures, including good agricultural practices (GAP), proper drying, storage conditions and biocontrol agents, were explored based on previous research conducted earlier. This comprehensive review underscores the critical importance of implementing integrated approaches combining advanced detection methods, harmonized regulatory standards and preventive strategies to ensure the safety and quality of spices in the global food supply chain.

The present study was carried out in the backcross population of groundnut involving TMV 7 and ICG 15419. Allele-specific primers were used to screen the population for high oleic acid and a total of 11 yield-contributing traits were included in this study. The number of primary and secondary branches had higher estimates of PCV and GCV whereas pod yield per plant had moderate PCV but low GCV. Along with the variability parameters, plant height, number of primary and secondary branches, pod width, 100 pod weight, oleic acid content and linoleic acid content had good estimates of heritability and genetic advance as a percent of the mean, whereas pod yield per plant had moderate and low, heritability and GAM respectively, with a negatively significant skewed distribution. Association analysis exhibited a positive correlation between the number of primary branches, number of secondary branches, pod length and 100 pod weight with pod yield per plant and it was evident that oleic acid was indirectly proportional to linoleic acid content. Hundred pod weights had the highest direct effect on pod yield per plant. Selection based on traits with a better relationship with pod yield per plant and moderate to high estimates of PCV, GCV, heritability and genetic advancement would help in accelerating the groundnut improvement program. High oleic, low linolenic lines of BC2F2 with better pod yield would be forwarded to the next generation.

The present investigation was carried out at the Department of Vegetable Crops, Horticultural College and Research Institute (HC&RI), Tamil Nadu Agricultural University, Periyakulam during 2016 -2017. Twenty genotypes used to study the genetic diversity for different yield attributing characters of moringa by principal component analysis. In this study, out of twelve principal components, five components exhibited eigen value and revealed about 99.54% variability among the traits. The PC1 accounted for the highest variability (62.20%), followed by PC5 (28.86%) , PC (10 6.25%), PC7 (1.01%) and PC4 (0.75%). The results of the Principal Component Analysis revealed that wide genetic variability exists in these moringa genotypes.