The Asian corn borer, Ostrinia furnacalis (Guenée), emerges as a significant threat to maize cultivation, inflicting substantial damage upon the crops. Particularly, its larval stage represents a critical point characterised by significant economic consequences on maize yield. To manage the infestation of this pest effectively, timely and precise identification of its larval stages is required. Currently, the absence of techniques capable of addressing this urgent need poses a formidable challenge to agricultural practitioners. To mitigate this issue, the current study aims to establish models conducive to the identification of larval stages. Furthermore, this study aims to devise predictive models for estimating larval weights, thereby enhancing the precision and efficacy of pest management strategies. For this, 9 classification and 11 regression models were established using four feature datasets based on the following features geometry, colour, and texture. Effectiveness of the models was determined by comparing metrics such as accuracy, precision, recall, F1-score, coefficient of determination, root mean squared error, mean absolute error, and mean absolute percentage error. Furthermore, Shapley Additive exPlanations analysis was employed to analyse the importance of features. Our results revealed that for instar identification, the DecisionTreeClassifier model exhibited the best performance with an accuracy of 84%. For larval weight, the SupportVectorRegressor model performed best with R2 of 0.9742. Overall, these findings present a novel and accurate approach to identify instar and predict the weight of O. furnacalis larvae, offering valuable insights for the implementation of management strategies against this key pest.

The Asian corn borer (ACB), Ostrinia furnacalis (Guenée, 1854), is a serious pest of several crops, particularly a destructive pest of maize and other cereals throughout most of Asia, including China, the Philippines, Indonesia, Malaysia, Thailand, Sri Lanka, India, Bangladesh, Japan, Korea, Vietnam, Laos, Myanmar, Afghanistan, Pakistan and Cambodia. It has long been known as a pest in South-east Asia and has invaded other parts of Asia, Solomon Islands, parts of Africa and certain regions of Australia and Russia. Consequently, worldwide efforts have been increased to ensure new control strategies for O. furnacalis management. In this article, we provide a comprehensive review of the ACB covering its (i) distribution (geographic range and seasonal variations), (ii) morphology and ecology (taxonomy, life-history, host plants and economic importance) and (iii) management strategies (which include agroecological approaches, mating disruption, integrated genetic approaches, chemical as well as biological control). Furthermore, we conclude this review with recommendations to provide some suggestions for improving eco-friendly pest management strategies to enhance the sustainable management of ACB in infested areas.

The desert locust (Schistocerca gregaria) is a destructive migratory pest, posing great threat to over 60 countries globally. In the backdrop of climate change, the habitat suitability of desert locusts is poised to undergo alterations. Hence, investigating the shifting dynamics of desert locust habitats holds profound significance in ensuring global agricultural resilience and food security. In this study, we combined the maximum entropy modelling and geographic information system technology to conduct a comprehensive analysis of the impact of climate change on the distribution patterns and habitat adaptability of desert locusts. The results indicate that the suitable areas for desert locusts (0.2976 × 108 km2) are concentrated in northern Africa and southwestern Asia, accounting for 19.97% of the total global land area. Key environmental variables affecting the desert locust distribution include temperature annual range, mean temperature of the coldest quarter, average temperature of February, and precipitation of the driest month. Under the SSP1–2.6 and SSP5–8.5 climate scenarios, potential suitable areas for desert locusts are estimated to increase from 2030 (2021–2040) to 2090 (2081–2100). By 2090, highly suitable areas for SSP1–2.6 and SSP5–8.5 are projected to be 0.0606 × 108 and 0.0891 × 108 km2, respectively, reflecting an expansion of 1.84 and 2.77% compared to existing ones. These research findings provide a theoretical basis for adopting prevention and control strategies for desert locusts.

As heatwaves increase and intensify worldwide, so has the research aimed at outlining strategies to protect individuals from their impact. Interventions that promote adaptive measures to heatwaves are encouraged, but evidence on how to develop such interventions is still scarce. Although the Health Belief Model is one of the leading frameworks guiding behavioral change interventions, the evidence of its use in heatwave research is limited. This rapid review aims to identify and describe the main themes and key findings in the literature regarding the use of the Health Belief Model in heatwaves research. It also highlights important research gaps and future research priorities. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, 10 articles were included, with a geographic distribution as follows: United States (n = 1), Australia (n = 1), Pakistan (n = 1), and China (n = 1), as well as Malaysia (n = 2), Germany (n = 1), and Austria (n = 1). Results showed a lack of research using the Health Belief Model to study heatwaves induced by climate change. Half of the studies assessed heatwave risk perception, with the 2 most frequently used constructs being Perceived Susceptibility and Perceived Severity. The Self-efficacy construct was instead used less often. Most of the research was conducted in urban communities. This review underscores the need for further research using the Health Belief Model.

In this research communication we describe the DGAT1 sequence and promoter region in dairy cows and buffalo and compare the activities of DGAT1 between the two species in order to increase knowledge of the cause of milk fat variation. pGL-3 basic vectors were used to construct the reporter gene. Based on the predicted promoter region, 4 truncated plasmid vectors were constructed in cow-DGAT1 and 3 plasmid vectors in buffalo-DGAT1. Each reporter plasmid was transfected into the bovine mammary epithelial cell (BMEC), 293T cell, and CHO cells to analyze the activity using Dual-Luciferase Reporter Assay System. The results show that the region between −93 to −556 bp was essential for cow promoter activity while −84 to −590 bp was essential for buffalo promoter activity revealing these regions contain core promoter. The buffalo has higher promoter activity than cow yet it was not statistically significant. Comparison of candidate mutation K232A between cow and buffalo population revealed the presence of both the allelic population in dairy cows (lysine and alanine) however, only K (lysine) allelic amino acid was found in buffalo population. The absence of the alanine allelic population from buffalo explains the higher fat content of buffalo milk.

The objective of the studies presented in this Research Communication was to investigate the association of single nucleotide polymorphisms present in the MAP4K4 gene with different milk traits in dairy cows. Based on previous QTL fine mapping results on bovine chromosome 11, the MAP4K4 gene was selected as a candidate gene to evaluate its effect on somatic cell count and milk traits in ChineseHolstein cows. Milk production traits including milk yield, fat percentage, and protein percentage of each cow were collected using 305 d lactation records. Association between MAP4K4 genotype and different traits and Somatic Cell Score (SCS) was performed using General Linear Regression Model of R. Two SNPs at exon 18 (c.2061T > G and c.2196T > C) with genotype TT in both SNPs were found significantly higher for somatic SCS. We found the significant effect of exon 18 (c.2061T > G) on protein percentage, milk yield and SCS. We identified SNPs at different location of MAP4K4 gene of the cattle and several of them were significantly associated with the somatic cell score and other different milk traits. Thus, MAP4K4 gene could be a useful candidate gene for selection of dairy cattle against mastitis and the identified polymorphisms might potentially be strong genetic markers.