Advances in Agriculture

The tomato (Lycopersicon esculentum Mill) is an important vegetable crop in Ethiopia and is produced and eaten in large quantities throughout the nation. However, the tomato production is quite low (10 tons·ha⁻¹) compared to the global average yield of 34 tons·ha⁻¹ due to the repetitive use of chemical fertilizers alone, growing intensive crops that are absorbing significant amounts of the soil nutrients, and the lack of application of organic fertilizers. Therefore, it is crucial to take accurate measurements when using fertilizers in order to solve issues and boost crop yield. The study’s objective was to find out how NPSB and vermicompost fertilizers together influenced tomato growth, yield characteristics, and yield at the Wallaga University Research Site for two consecutive years (2021 and 2022). The experiment used a factorial randomized block design with two components: four levels of NPSB and four levels of vermicompost. The tomato fruit production and all of its components were strongly impacted by the primary and interaction effects of NPSB and vermicompost treatment rates. The highest fruit length was 6.26 cm, the largest fruit diameter was 5.94 cm, the shoot fresh weight was 48.25 g·plant⁻¹, the shoot dry weight was 4.50 g·plant⁻¹, the marketable fresh fruit per plant was 5.54 kg, and the fruit yield was 24.36 ton·ha⁻¹ after the application of 125 kg·ha⁻¹ NPSB plus 8 ton·ha⁻¹ vermicompost. Application of 125 kg·ha⁻¹ of NPSB fertilizer along with 8 tons·ha⁻¹ of vermicompost increases net benefits by 115922.5 ETB·ha⁻¹ as compared to a control. Therefore, in order to enhance tomato yield, it may be suggested that farmers utilize the combination of 125 kg·ha⁻¹ of NPSB and 8 tons·ha⁻¹ of vermicompost rather than applying any inorganic fertilizers alone.

One of the major limiting factors of livestock production in Ethiopia is the very low quantity and quality of livestock feeds supplied in the country. This calls for seeking forages that complement poor quality feeds in the country. Hence, the target of this article was to compare three types of grass agronomic performance, yield, and chemical composition under three different agroecologies and three harvesting dates (60, 90, and 120 days). The field experiment was carried out in selected three districts in 2017/2018 in the main cropping season. The treatments were laid out in a factorial RCBD (the randomized complete block design) arrangement with three replications. The treatments contained the combinations of three altitudes and three harvesting dates. Agronomic, yield, and chemical composition data were collected from the current study and subjected to analysis of variance procedures with a significance test. In most agronomical and chemical compositions, the interactions of altitudes and harvesting dates were significant for all tested grasses (Mulato II, Napier, and Rhodes grasses). The highest plant height (PH) and dry matter yield (DMY) by Napier and the number of tillers per plant (NTPP) by Mulato II were recorded. There were significant values () for DMY and CP for all grasses at the interactions of harvesting dates and altitudes. The significant difference in DMY was observed as the harvesting date advanced, but CP was contrariwise. Of all tested species, the highest crude protein value and the least value of NDF and ADF (best forage quality parameters) were recorded by Mulato II. Thus, the results of this study revealed that Brachiaria hybrid cv. Mulato II has great potential to fulfil the demands for quality feeds for livestock production, especially at low altitudes. Nevertheless, in areas where, Napier and Rhodes grass are available, they can be alternative forage for Mulato II grass. Generally, for effective utilization of the tested grasses, the comparative feed value for animals must be conducted.

Soybean (Glycine max) is an economically important crop, ranking first among the edible oilseed crops in the world due to its oil content and nutritional value. Besides, it is used as a dietary supplement and a source of pharmaceuticals. The recent rapid climate changes and increasing global population have led to increasing demand for vegetable oil. In the recent past, advances in the field of plant biotechnology have revolutionized agricultural practices at a global level to enhance the yield of crops. This technology not only makes an impact on the agricultural market but also opens up new corridors for agriculture-related industrial applications of this important crop. Therefore, in the last two decades, soybean has gained attention for genetic improvement with remarkable developments in the manipulations of genes for the induction of desired characteristics. In this review, we introduced the transgenic approach as a promising tool for the improvement of soybean oilseed quality and productivity. Then, the enhancement of nutritional and pharmaceutical value together with biotic and abiotic stress-resistant ability was summarized and compared. The methods and strategies for achieving soybean crops with improved abiotic stress tolerance, productivity, and pharmaceutics are categorized to help with future research.

Sustainable farm animal raising is dependent on the production of sufficient quantities and quality of forages and fodder, especially in dry regions. Improved forage and feed species are an option for these aspects because adequate feed resources enhance soil health and carbon, generate income, and reduce emissions. Therefore, the purpose of this review paper was to investigate the role of climate-smart forage production in sustaining farm animal production and maintaining the environment in arid and semiarid regions. Seasonal fluctuations in feed supply cause temporal scarcity in Ethiopia, with more acute gaps in dry periods, particularly in drought-prone regions. To address these problems in the country, improve forages to strengthen farm productivity, climate change resilience, and environmental sustainability, particularly in arid and semiarid areas. The country has a long history and is of some exemplary practices in indigenous improved forage production, but the input of improved forage to the total biomass production in feed resources is still low due to many factors like scarcity of land and water for irrigation, lack of awareness, forage seed, and policy recommendations. Despite the potential profits of feed and forage grasses and legumes, the availability of species adapted to a wide range of situations in actual use in the livestock sector has been insufficient. Therefore, it is strongly suggested that climate-resilient forage species be popularized to sustain livestock production and the environment, particularly in the country’s arid and semiarid regions.

The experiment was laid out in alpha-lattice design with two replicates of each genotype which comprised twenty-three heat-tolerant maize hybrids received from CIMMYT-Mexico and three check varieties. These treatment genotypes were evaluated at the Agronomy farm, Gokuleshwor College, Baitadi, Nepal, during the spring season of 2021. ZH191065 and ZH191158 were found to be the tallest (307.2 cm) and the shortest (227.6 cm) genotypes, respectively. High heritability (>60%) with high genetic advances in most traits, ensures the predominance difference of the genetic components observed among accessions. The presence of differences among genotypes showed that selection is possible by evaluating the days of 50% anthesis, days of 50% silking, anthesis-silking interval, number of ears per plant, number of grains per row, number of rows per cob, cob length, cob diameter, and grain yield; most of these evaluated morphological traits were found highly correlated with grain yield of varieties, suggesting that indirect selection achieves improvement for high yield. Based on yield ranks, ZH 19782, ZH 19961, and DKC 9108 could be promoted as potential higher-yielding heat-tolerant maize hybrids for Nepal.

This study addresses the underlying challenges of computer vision adoption in the Kenyan agricultural sector and how to solve these hurdles to commercialize this technology. Technological advancements have revolutionized the agriculture sector, where artificial intelligence enhances yields, mitigates losses, and manages natural resources, leading to increased productivity. Kenya is still lagging in the commercialization of computer vision to improve its agricultural sector, which is the largest source of GDP. Kenya has remarkable skills and expertise in artificial intelligence that can support artificial intelligence implementation; the government policies, data availability, and high cost incurred in starting a computer vision company are problematic. Through better government policies on subsidies and data, research and development investments, and AI forums, Kenya will solve the challenges of adopting computer vision. While computer vision has the potential to revolutionize the agricultural industry by improving crop yield, detecting diseases, and increasing efficiency, there are several barriers to its adoption, including inadequate infrastructure, lack of technical expertise, and limited funding. This study aims to identify the challenges hindering the implementation of computer vision technology in the Kenyan agricultural sector and propose potential solutions to address these challenges.