The world’s food and agricultural programs have gradually declined into an unsustainable situation due to challenges such as increase in world population, varied agro-climatic regions, increase temperature, extreme sole-culture growing techniques, and water shortage. A considerable emphasis has been put on few staple food crops coupled with repeated dieting, food scarcity, and essential mineral deficits, frequently inducing dietary disorders. Because relying on staple crops may lead to serious food shortages in the future, we must adjust our dietary habits to include a diverse range of non-staple foods and maximize their use in order to achieve food security and reduce the nutritional gap. To assure healthy meals around the world, an authentic and reasonable strategy is presented to draw additional awareness towards variations in agricultural production techniques and dietary preferences. The EAT-Lancet declaration highlighted the importance of increasing agri-based foods to achieve sustainable health. Expanding overlooked crops with abundant genetic stocks and possibly beneficial characteristics is an approach that might meet food and nutritional security challenges. Although undervalued, pumpkin is a valuable vegetable herbaceous plant that contributes to global food and nutritional security. This crop has already been identified as a revolutionary age crop, balanced food, and more adapted to low soil and atmospheric circumstances than other major crops. This review paper focuses on the potential uses of pumpkin as an underutilized crop; diversification and development of hybrids, particularly hybridization breeding through diallel mating design; and how implementation of this “modern” technology would contribute to the breeding of the neglected pumpkin vegetable and stimulate productivity and nourish the world’s largest malnourished, deprived, and starved populations.

Brown planthopper (BPH; Nilaparvata lugens Stal) is considered the main rice insect pest in Asia. Several BPH-resistant varieties of rice have been bred previously and released for large-scale production in various rice-growing regions. However, the frequent surfacing of new BPH biotypes necessitates the evolution of new rice varieties that have a wide genetic base to overcome BPH attacks. Nowadays, with the introduction of molecular approaches in varietal development, it is possible to combine multiple genes from diverse sources into a single genetic background for durable resistance. At present, above 37 BPH-resistant genes/polygenes have been detected from wild species and indica varieties, which are situated on chromosomes 1, 3, 4, 6, 7, 8, 9, 10, 11 and 12. Five BPH gene clusters have been identified from chromosomes 3, 4, 6, and 12. In addition, eight BPH-resistant genes have been successfully cloned. It is hoped that many more resistance genes will be explored through screening of additional domesticated and undomesticated species in due course.

Many insect pests, including the brown planthopper (BPH), undergo windborne migration that is challenging to observe and track. It remains controversial about their migration patterns and largely unknown regarding the underlying genetic basis. By analyzing 360 whole genomes from around the globe, we clarify the genetic sources of worldwide BPHs and illuminate a landscape of BPH migration showing that East Asian populations perform closed-circuit journeys between Indochina and the Far East, while populations of Malay Archipelago and South Asia undergo one-way migration to Indochina. We further find round-trip migration accelerates population differentiation, with highly diverged regions enriching in a gene desert chromosome that is simultaneously the speciation hotspot between BPH and related species. This study not only shows the power of applying genomic approaches to demystify the migration in windborne migrants but also enhances our understanding of how seasonal movements affect speciation and evolution in insects.

A full diallel mating design was used to hybridize seven pumpkin inbred parental lines, yielding 42 F₁ hybrids, including reciprocals. The generated F₁ hybrids, parental lines and commercial check hybrid were evaluated in two environments to investigate the per se performances, combining ability effects and magnitude of heterosis over mid-parent, better-parent and commercial check hybrids for yield, yield attributed, sweetness, total carotenoid and antioxidant traits, using a randomized complete block design with three replications. The analysis of variance for most of the examined traits revealed highly significant differences (p ≤ 0.01) for GCA, SCA, reciprocal, maternal and non-maternal variances and their interaction with the environment. Since the inheritance of yield and its contributing fruit quality, and antioxidant traits is governed by non-additive gene action, it suggests heterosis breeding would be useful in obtaining further improvements in pumpkin. From the experiment, it was found that the paternal lines P1 (Gold Butter 315) for dry matter content and DPPH (%), P4 (Asian pumpkin) for total carotenoid content, P6 (Sarawak) for fruit number per plant and P7 (Australia-1) for single fruit weight, fruit flesh thickness, yield per plant and total soluble solid were shown to be good general combiners. In respect to per se performance, combining ability effects and magnitude of heterosis over mid-parent, better-parent and commercial check, the cross P2 (928 Fuxiang) × P1 (Gold Butter 315) and P4 (Asian pumpkin) × P5 (Sarawak) for single fruit weight and yield per plant, the cross P5 (Sarawak) × P2 (928 Fuxiang) for fruits number per plant, P1 (Gold Butter 315) × P7 (Australia-1) and P1 (Gold Butter 315) × P6 (Sarawak) for total soluble solid and dry matter content, P7 (Australia-1) × P2 (928 Fuxiang) for total carotenoid content and P3 (Ser Bajadi) × P1 (Gold Butter 315) for DPPH (antioxidant) were identified to be highly significant positive specific combiners and the highest performers, and these crosses may be exploited as commercial hybrids.

MODIS land surface temperature data (MODIS T_s) products are quantified from the earth surface’s reflected thermal infrared signal via sensors onboard the Terra and Aqua satellites. MODIS T_s products are a great value to many environmental applications but often subject to discrepancies when compared to the air temperature (T_a) data that represent the temperature measured at 2 m above the ground surface. Although they are different in their nature, the relationship between T_s and T_a has been established by many researchers. Further validation and correction on the relationship between these two has enabled the estimation of T_a from MODIS T_s products in order to overcome the limitation of T_a that can only provide data in a point form with a very limited area coverage. Therefore, this study was conducted with the objective to assess the accuracy of MODIS T_s products, i.e., MOD11A1, MOD11A2, MYD11A1, and MYD11A2 against T_a and to identify the performance of a modified Linear Scaling using a constant and monthly correction factor (LS-MBC), and Quantile Mapping Mean Bias Correction (QM-MBC) methods for lowland area of Peninsular Malaysia. Furthermore, the correction factor (CF) values for each MBC were adjusted according to the condition set depending on the different bias levels. Then, the performance of the pre- and post-MBC correction for by stations and regions analysis were evaluated through root mean square error (RMSE), percentage bias (PBIAS), mean absolute error (MAE), and correlation coefficient (r). The region dataset is obtained by stacking the air temperature (T_{a_r}) and surface temperature (T_{s_r}) data corresponding to the number of stations within the identified regions. The assessment of pre-MBC data for both 36 stations and 5 regions demonstrated poor correspondence with high average errors and percentage biases, i.e., RMSE = 3.33–5.42 °C, PBIAS = 1.36–12.07%, MAE = 2.88–4.89 °C, and r = 0.16–0.29. The application of the MBCs has successfully reduced the errors and bias percentages, and slightly increased the r values for all MODIS T_s products. All post-MBC depicted good average accuracies (RMSE and MAE < 3 °C and PBIAS between ±5%) and r between 0.18 and 0.31. In detail, for the station analysis, the LS-MBC using monthly CF recorded better performance than the LS-MBC using constant CF or the QM-MBC. For the regional study, the QM-MBC outperformed the others. This study illustrated that the proposed LS-MBC, in spite of its simplicity, managed to perform well in reducing the error and bias terms of MODIS T_s as much as the performance of the more complex QM-MBC method.

The development of a decision support system (DSS) called the IRice Risk Management System aims to empower farmers in making well-informed decisions, ultimately enhancing rice field production. This system focuses on providing a monitoring mechanism that optimizes monitoring and control efforts in paddy plantations. By employing predictive modeling, integrated pest monitoring, and decision support systems for pests, weeds, abiotic variables, and rainfall patterns, it predicts the likelihood and consequences of potential weed infestations, pest outbreaks, and changes in weather patterns like temperature and rainfall. By leveraging precision agriculture technologies and data-driven insights, the Risk Management System keeps a vigilant watch on disease and pest presence in paddy fields. It promptly alerts farmers when specific thresholds are surpassed, enabling them to take immediate action. The system facilitates effective data analysis for extension officers, enabling them to swiftly respond to emergency situations. Overall, this method offers a practical and efficient response to the challenges faced by paddy farmers. It equips them with the ability to make informed decisions, increase production, and effectively manage diseases and pests, ultimately leading to improved agricultural outcomes.