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The current management of whiteflies is largely dependent on insecticides. However, pesticides are costly and do not provide effective control of whitefly-transmitted viruses (WTVs). However, breeding for resistant cultivars can provide a more effective and sustainable solution. Twenty-one Citrullus genotypes, including 10 C. lanatus, four C. mucosospermus, six C. amarus, and one C. ecirrhosus, were evaluated to determine their resistance to three WTVs common in Georgia in field trials for 2 years. Phenotypic data were collected weekly to determine viral disease severity, and the cumulative season data were calculated as the area under the disease progress curve. Leaves were collected 5 weeks after transplanting (WAT) in 2022 and at 7 WAT in 2023 to determine the viral loads of Cucurbit leaf crumple virus (CuLCrV), Cucurbit yellow stunting disorder virus (CYSDV), and Cucurbit chlorotic yellows virus (CCYV) via a quantitative polymerase chain reaction. The CuLCrV and CYSDV viral loads were higher in 2022 than those in 2023, whereas the CCYV load was higher in 2023. Three accessions (PI 494528, PI 595203, and Grif 16444) outperformed the cultivars for viral disease resistance and CuLCrV load (2022). In 2022, there was a significant difference among cultivars regarding the CYSDV load, with ‘AU-Producer’, ‘Crimson Sweet’, and ‘Estrella’ having lower loads than those of ‘Charleston Gray’ and ‘Sugar Baby’. There were no statistical differences in CCYV loads between the best-performing accessions and ‘Charleston Gray’. Grif 16444 is a C. ecirrhosus accession, and this species has resistance to whiteflies. The two C. mucosospermus accessions (PI 494528 and PI 595203) provide a valuable resource for breeders to develop CuLCrV resistance in watermelon (C. lanatus) because there is no reproductive barrier between the two species.

Peanut is a vital source of protein, particularly in the tropical regions of Asian and African countries. About three-quarters of peanut production occurs worldwide in arid and semi-arid regions, making drought an important concern in peanut production. In the US about two-thirds of peanuts are grown in non-irrigated lands, where drought accounts for 50 million USD loss each year. The looming threat of climate change exacerbates this situation by increasing erratic rainfall. Drought not only reduces yield but also degrades product quality. Peanuts under drought stress exhibit higher levels of pre-harvest aflatoxin contamination, a toxic fungal metabolite detrimental to both humans and animals. One way to sustain peanut production in drought-prone regions and address pre-harvest aflatoxin contamination is by developing drought-tolerant peanut cultivars, a process that can be accelerated by understanding the underlying physiological and genetic mechanisms for tolerance to drought stress. Different physiological attributes and genetic regions have been identified in drought-tolerant cultivars that help them cope with drought stress. The advent of precise genetic studies, artificial intelligence, high-throughput phenotyping, bioinformatics, and data science have significantly improved drought studies in peanuts. Yet, breeding peanuts for drought tolerance is often a challenge as it is a complex trait significantly affected by environmental conditions. Besides technological advancements, the success of drought-tolerant cultivar development also relies on the identification of suitable germplasm and the conservation of peanut genetic variation.

Biodiversity is an essential attribute of sustainable agroecosystems. Diverse arthropod communities deliver multiple ecosystem services, such as biological control, which are the core of integrated pest management programs. The molecular analysis of arthropod diets has emerged as a new tool to monitor and help predict the outcomes of management on the functioning of arthropod communities. Here, we briefly review the recent molecular analysis of predators and parasitoids in agricultural environments. We focus on the developments of molecular gut content analysis (MGCA) implemented to unravel the function of community members, and their roles in biological control. We examine the agricultural systems in which this tool has been applied, and at what ecological scales. Additionally, we review the use of MGCA to uncover vertebrate roles in pest management, which commonly receives less attention. Applying MGCA to understand agricultural food webs is likely to provide an indicator of how management strategies either improve food web properties (i.e., enhanced biological control), or adversely impact them.