The Agricultural and Food Research Council (AFRC) was a British Research Council responsible for funding and managing scientific and technological developments in farming and horticulture.
Abstract Cassava (Manihot esculenta) is an important staple food in sub–Saharan Africa. Over 60% of the global cassava production occurs in Africa, with the southern African region contributing approximately 15% to this total. Compared to west and central Africa, the southern Africa region has not fully realised its potential for cassava production. This study examines cassava-related research in southern Africa focusing on current trends, challenges, and contributions of cassava to food security, economic development, and climate resilience. It also explores industrial applications, the implications for sustainable agriculture, and identifies critical policy and research gaps through a bibliographic network analysis. One hundred and ninety-two eligible research manuscripts published between 2000 and 2024 were retrieved from the Scopus and Web of Science databases. Most cassava research has been conducted in South Africa, followed by Zambia, Mozambique and Malawi. Cassava pests and diseases, crop management, yield and food security were the most researched themes. The region’s average actual yield (9.5 t/ha) compared with the potential yield (75–80 t/ha) highlights the untapped potential in cassava production. Findings from climatic studies predict a substantial increase in the area suitable for cassava production in the region. Some studies have highlighted the potential of cassava as a raw material for biofuel and industrial starch. This study highlights the current body of knowledge and identifies research gaps concerning cassava, which various stakeholders can explore to achieve significant advancements in promoting cassava cultivation in the region.
The Northern Mountainous Region (NMR) is one of the poorest areas in Vietnam. In rural communities, ethnic minority people tend to subsist on livestock and crops grown locally on a smaller scale. The raising of heritage breeds of chicken for eggs and meat according to sustainable agriculture by women, for example, is a common way of securing a vital source of nutrition and income. It also contributes to the maintenance of genetic diversity and indigenous knowledge systems of production. As more industrial production systems of chicken are rapidly being developed across Vietnam, and in the NMR in particular, rural livelihoods are being considerably affected. This study explores the results of these changes in four districts of Thai Nguyen and Bac Giang Provinces where ethnic minorities dominate the population. Overall, this article provides a realistic view of the impact of industrial chicken production on small-scale female ethnic minority farmers and their communities. Innovative solutions in support of these communities in Vietnam are posited with application to other rural populations in developing countries undergoing a rapid commodification of animal husbandry and the countryside.
In African countries and many developing countries, communal farmers rely on livestock such as cattle, goats, and sheep to support food security, income, and agricultural activities. Fertility in these animals is often limited by poor semen quality, which reduces sperm concentration, total motility, and morphology. Assisted reproductive biotechnologies, including semen cryopreservation and artificial insemination, are increasingly essential to enhance reproductive efficiency and productivity. Although cryopreservation preserves valuable genetic material, it can damage sperm cells, making high-quality extenders critical for protection. Common extenders, such as Tris-egg yolk glucose, citrate-sugar-based, and skimmed milk solutions, supply nutrients and protect sperm membranes. To further minimize oxidative stress, antioxidants are incorporated, with growing interest in plant-derived compounds. Many plants contain bioactive substances, including antioxidants and phytomelatonin, which can enhance sperm quality safely and effectively. This review examines the use of plant-based antioxidants during semen cryopreservation and highlights their potential to improve fertility in mammalian livestock.
Abstract Rapid, accurate and cost-effective identification of Apis mellifera subspecies is needed for subspecies of regulatory concern. We designed and validated subspecies markers based on single nucleotide polymorphisms (SNP) on mitochondrial cytochrome b ( Cytb ) and NADH dehydrogenase 4 ( ND4 ) genes. We used a combination of established and novel real-time qPCRs in a stepwise series, with increasing discrimination power, to (1) differentiate honey bees of African (A-lineage) ancestry from those of other lineages ( Cytb SNP #1), (2) identify African-derived honey bees (AHBs) ( Cytb SNP #2), and (3) detect A. m. capensis exclusively in the bee’s indigenous region of South Africa ( ND4 SNP). We also developed a restriction fragment length polymorphism assay targeting a SNP on the NADH dehydrogenase 2 ( ND2 RFLP) gene to detect the specific mitochondrial A-lineage clade. These assays allow for reliable time- and cost-effective results that provide increased accuracy on subspecies assignation.
In populations with limited genotyping, single-step genomic best linear unbiased predictions (ssGBLUP) can produce biased or less accurate genomic predictions due to incompatibilities between genomic and pedigree relationship matrices. The study evaluated the impact of five alternative ssGBLUP models for genomic predictions of milk, fat, and protein yield production traits in South African Holstein cattle. The dataset included 696,413 milk production records and pedigrees of 541,325 animals. Production traits were 305-day lactation yields for milk, protein, and fat. Genotype data were based on the Illumina 50K chip v3, with 53,218 SNPs. A total of 1221 animals with genotypes and 41,407 SNP markers were in the final dataset. The five models used to estimate genomic estimated breeding values (GEBVs) were the single-step method (ssGBLUP), ssGBLUP accounting for inbreeding (ssGBLUP_Fx), ssGBLUP with unknown parent groups (ssGBLUP_upg), and two ssGBLUP models with blending, tuning, and scaling parameters set to optimum values in constructing the inverse of the unified relationship matrix (ssGBLUP_adjusted). Realized prediction accuracies were highest for ssGBLUP_adjusted models (6-7% improvements compared to ssGBLUP). Accuracy of GEBVs for milk, protein, and fat yields ranged from 0.23, 0.29, and 0.30 for both ssGBLUP and ssGBLUP_Fx, 0.26, 0.32, and 0.34 for ssGBLUP_upg, and 0.29, 0.35, and 0.37 for ssGBLUP_adjusted models, respectively. Corresponding bias, expressed as regression coefficients, ranged from 0.30, 0.31, and 0.36 for ssGBLUP; 0.31, 0.32, and 0.37 for ssGBLUP_Fx; 0.41, 0.44, and 0.49 for ssGBLUP_upg; and 0.44, 0.47, and 0.53 for ssGBLUP_adjusted models, respectively. The improved accuracy and reduced bias observed with the ssGBLUP_adjusted underscores the importance of optimizing the blending of pedigree- and genome-based relationships to achieve more reliable GEBVs, thereby improving selection decisions in Holstein dairy cattle.
