Participatory approach of preferred traits, production constraints and mitigation strategies: implications for soybean breeding in Guinea Savannah zone of Ghana.

Soybean production is concentrated in the Guinea Savannah agro-ecological zone of Ghana. However, its cultivation is plagued with a number of constraints leading to low yields. A participatory approach was, therefore, used to identify farmers' and processors' preferred soybean traits and production constraints, climate change effects and strategies employed for mitigating these effects in three districts within the soybean growing areas in Northern Ghana. The study revealed that 72.0 % and 68.8 % of farmers in the Tolon and Savelugu districts, respectively, used improved soybean seeds for planting their fields. Over 13.0 % of farmers indicated late maturity as the most important constraint, followed by manual threshing difficulty and terminal drought which results in low grain yield and poor quality. About 70.0 % of farmers opined that climate change effects are causing obvious shifts in the rainfall pattern. Majority of the farmers (94.6 %) indicated that the onset of peak rainfall has changed in the past decade. Almost 44.0% of farmers also indicated that severe drought has affected pods filling in the past. A third (33.3%) of farmers indicated that drought usually sets in at pod initiation. The farmers enumerated some of the effects of early cessation of the rainfall in soybean production as drying up of immature and green seed (28.3%), low grain yield (27.1%) and poor seed quality (22.1%). Some of the mitigation strategies employed by the farmers include early planting (40.0%) and mulching (25.0%) to retain soil moisture for enhanced growth of crops. The order of farmers' preferences new soybean varieties were shattering resistance (16.0%), high grain yield (14.0%), large seeds size (13.1%), and early maturity (11.8%), whereas processors preferred varieties with large seed size (30.6%), high protein content (28.7%), pest resistance (15.9%) and short cooking duration (12.7%). Both the farmers and processors indicated their willingness to pay more for seeds with the desired traits. These findings will aid soybean breeders in developing new varieties that possess desired traits preferred by both farmers and processors for increased soybean cultivation and utilization.

Characterization of Groundnut (Arachis hypogaea L.) Test Locations Using Representative Testing Environments With Farmer-Preferred Traits.

In this study, the differential rankings of 36 groundnut genotypes under varying environmental conditions were studied at various levels of phenotype. Locations that are generally accepted by the crop- and soil-based research community to represent the entire Guinea and Sudan Savanna agro-ecological zones in Ghana were characterized, this time using a crop. The characterization was done based on four farmer-preferred traits (early and late leaf spot disease ratings, and haulm and pod yields) using three models (i.e., AMMI, GGE, and Finlay-Wilkinson regression). These models were used to capture specific levels of phenotype, namely, genotype-by-environment interaction (GE), genotype main effect plus GE (G+GE), and environment and genotype main effects plus GE (E+G+GE), respectively. The effect of three major environmental covariables was also determined using factorial regression. Location main effect was found to be highly significant (p < 0.001), confirming its importance in cultivar placement. However, unlike genotypes where the best is usually adjudged through statistical ranking, locations are judged against a benchmark, particularly when phenotyping for disease severity. It was also found that the locations represent one complex mega-environment, justifying the need to test new technologies, including genotypes in all of them before they can be approved for adoption nationally. Again, depending on the phenotypic level considered, genotypic rankings may change, causing environmental groupings to change. For instance, all locations clustered to form one group in 2017 for early and late leaf spot diseases and pod yield when GE was considered, but the groupings changed when G+GE was considered for the same traits in the same year. As a result, assessing genotypic performance at the various levels to arrive at a consensus decision is suggested. Genotypes ICGV-IS 141120 and ICGV-IS 13937 were found to be the best performing.