Smallholder farmers are the mainstay of the agricultural economies of sub-Saharan Africa (SSA), where they produce several crops, predominantly centered on maize. Smallholder productivity remains limited resulting from a range of confounding factors, but a primary cause is loss from pests and diseases, particularly insects. To improve productivity, recommendations for the mitigation of crop loss globally include early-warning and management systems for in-season indigenous pests. There are many early-warning systems in temperate regions; however, such systems are poorly established in Africa. This is in part due to the need for a combination of pest modeling, data handling and dissemination infrastructure, capacity, and resource provision. While each of these components is progressing in Africa, the means to successfully deploy such systems remain limited. To bridge this, the development of the Pest Risk Information Service (PRISE) began in 2017 for farmers in SSA. Implemented in Kenya, Ghana, Malawi, and Zambia, PRISE developed temperature-driven phenology models for major maize, bean, and tomato pests. Using downscaled and processed Earth Observation data to drive the models, PRISE partnered with African national agencies to communicate pre- and in-season pest alerts that forecast the time to act against key insect pests. Alerts were designed to be integrated into country-specific Good Agricultural Practice (GAP) recommendations to provide a complementary package to agricultural stakeholders. End line studies with farmers showed that those who received information about the target crops including PRISE pest forecasts, generally reported better outcomes in terms of reduced losses and increased incomes compared with farmers who did not.

The main challenges facing rain-fed rice farming in Kilifi County at the Kenyan coast are inadequate and erratic rainfall, inadequate skills, and poorly developed infrastructure. Of great importance is erratic rainfall that tends to depress towards the end of long rain season, leading to crop failure. Combining ability analysis is one of the most valuable tools used to ascertain gene action effects and help in selecting desirable parents for making crosses and coming up with high yielding and early maturing lines. Combining ability for early maturity and yield has not been studied at the Kenyan coast. This study aimed at determining and identifying good, general, and specific combiners for selecting better parents and better cross combinations in rice crops for developing high yield and short duration lines in rain-fed rice farming. Seven lines were subjected to half-diallel mating design at the Kenya Agricultural and Livestock Research Organization (KALRO), Mtwapa, and at Bahari in Kilifi town. Evaluation for general combining ability (GCA) and specific combining ability (SCA) analysis was done. Combining ability variance and GCA and SCA effects were determined. Based on GCA effects, best parent for early maturity was Dourado Precoce, while for yield, Supaa, Komboka, and NERICA 10. SCA estimates indicated that best crosses for yield were D/S, D/N1, and K/N10, while the best performing cross for early maturity was D/N1.

Environments in sub-Saharan Africa fluctuate considerably across sites and seasons. This suggests the importance of assessing genotype x environment interaction (GEI) in cultivar development. The objective of this study was to estimate the magnitude of GEI for rice grain yield and identify high yielding and stable rice genotypes. Fifty six genotypes including 45 F3 rice populations, their 10 parents and one check were evaluated in 7 x 8 alpha lattice design with two replications under three no drought and one random managed drought stress condition at reproductive growth stage at three sites in coast region of Kenya. The additive main effects and multiplicative interaction (AMMI) analysis and genotype plus genotype x environment interaction (GGE) biplot analysis were used to measure grain yield stability of the 45 F3 populations and their 10 parents. Ranking of the genotypes changed in each environment and three mega environments were identified revealing a crossover type of GEI. The genotypes G39 (Luyin 46 x IR74371-54-1-1) and G40 (NERICA-L-25 x IR55423-01) were the most stable high yielding genotypes. These were identified as candidates with general adaption for advancement to homozygozity simultaneously selecting within each population good performing pure lines for release in the region. Key words: Additive main effects and multiplicative interaction (AMMI), genotype x environment interactions, genotype plus genotype x environment interaction (GGE) biplot, rice, yield stability.

The average annual rainfall in coastal Kenya is 450–700 mm per annum in most places while the total annual evapotranspiration is 1200–1800 mm. In arid and semi-arid lands (ASALs), farmers grow maize varieties for medium to high rainfall zones without considering the need for water harvesting to enhance crop yield. To address the moisture constraint, a study was conducted to evaluate the performance of drought tolerant maize varieties under different water harvesting technologies (Zai pits, tied ridges and conventional). The treatments were laid out in a split - plot design with water harvesting methods as the main plots and maize varieties as the sub-plots. The response of four maize varieties (DK8031, DUMA 43, KDV1 and PH4) to three water harvesting technologies was evaluated. Variety Duma 43 produced the highest grain yield (P < 0.05) compared to the other varieties whereas yields for Zai pits and tied ridges were higher (P < 0.05) than for conventional treatment. Economic analysis revealed a higher gross margin for tied ridges than for Zai pits. Conventional planting showed a negative gross margin under the ASAL conditions. The variety DUMA 43 was selected for yield and cob size components whereas PH4 was selected for grain recovery when pounded and high stover biomass.

Phosphorus (P) is an essential macronutrient for rice (Oryza sativa L.) production, yet its availability is often limited in tropical soils, constraining crop growth and yield. Optimizing phosphorus use efficiency (PUE) is crucial for enhancing rice productivity while minimizing fertilizer input costs. This study evaluates the yield and phosphorus use efficiencies of two upland rice varieties, Nerica 4 and Komboka, under different phosphorus application levels across two growing seasons (short and long rains) in Kenya. The findings provide insights into varietal differences in phosphorus acquisition and utilization, contributing to site-specific fertilizer recommendations for sustainable upland rice production. A field experiment was conducted using a randomized complete block design (RCBD) in a split-plot arrangement. The main plots consisted of two rice varieties, Nerica 4 and Komboka, while the sub-plots comprised four phosphorus application levels (0, 30, 50 and 70 kg P ha?¹), with three replications. Grain and stover yields were measured at harvest, and plant samples were collected for phosphorus analysis. Phosphorus use efficiencies, including agronomic efficiency, physiological efficiency, partial factor productivity, recovery efficiency, and internal utilization efficiency, were calculated. Nerica 4 exhibited significantly higher grain yield and phosphorus-use efficiency than Komboka. During the short rains, grain yield in Nerica 4 ranged from 2.34 t ha?¹ (P0) to 5.75 t ha?¹ (P70), while Komboka recorded yields between 1.97 t ha?¹ (P0) and 3.5 t ha?¹ (P70). In the long rains, grain yield in Nerica 4 ranged from 0.6 to 2.4 t ha?¹, whereas Komboka recorded yields between 0.6 and 1.85 t ha?¹. Additionally, Nerica 4 demonstrated significantly superior agronomic efficiency, partial factor productivity, and recovery efficiency compared to Komboka. Phosphorus application rates, rice variety and seasonal conditions significantly influenced rice yield, phosphorus uptake, efficiency, and overall plant performance. The findings highlight the importance of variety-specific phosphorus management strategies to enhance the productivity and sustainability of upland rice. Based on the results, an application rate of P 70 kg ha-1 is recommended for optimal yield and P 50 kg ha-1 for efficient nutrient use, and a cost-effective option with relatively good yields.