Selection, genetic parameters, and multi-year stability of cacao yield under agroforestry in Rondônia, Brazil

Cocoa is a commodity of great global importance and wide acceptance among consumers. Known as the chocolate tree, the cacao is cultivated in developing countries. More than 60% of that production is concentrated Côte d’Ivoire and Ghana and it is declining. This scenario presents a new opportunity for Brazil, the world’s seventh-largest producer. Rondônia, the fourth-largest producing Brazilian state, has several comparative advantages such as proximity to the Asian market, a predominance of a thousand small producers, and the potential to supply the market for fine cocoa. However, there is a need to recommend local clones selected for high performance and stability. To address this, we estimated genetic parameters and genotypic values using mixed models and investigated temporal stability by modeling the genotype × year interaction with covariance structures. Our study involved 30 clones under agroforestry, tested in randomized blocks with three replications and 9-plant plots. Cacao yield was assessed over seven consecutive years of harvests, counted from the third year in the field. Significant clonal effects were observed, and the mean dry bean yield (476 kg ha −1 ) showed marked amplitude (nearly sevenfold). Satisfactory experimental precision ( \(CV = 37.5%\) ), high values for the coefficient of genetic variation ( \(CVg = 60.7%\) ), the ratio \((CVᵣₐₜᵢₒ = 1.65\) ), and heritability ( \(Hg² = 0.932\) ) reflected favorable conditions for selection. Of the ten covariance matrix models evaluated to model the matrix related to the genotype × harvest year (G x A) interaction, the factor analytic with three factors (FA3) provided the best fit. This better fit with FA3 likely arises from the fact that capturing the latent structure of the G × A interaction is not restricted to the time series, allowing it to also accommodate non-autoregressive correlations. The heterogeneous diagonal matrix, associated with FA3, was applied to model the residual covariance matrix. Based on repeatability coefficient’s accuracy, two years of successive harvests were sufficient for selecting clones in advanced breeding cycles, and five years for cultivar release. The genetic correlation matrix between pairs of harvest years reveals that cacao yield remained moderately associated ( \({{C}} > 0.41\) ), with some years being more strongly associated ( \({{C}} > 0.80)\) than others. There was also a significant change in the ranking of clones over the years of harvests. With the factor analytic selection tools, we selected the five most productive and stable clones (EEOP 33, 63, 65, and 80, and Ipiranga 1), adapted to agroforestry conditions of Rondônia, with a substantial genetic gain of 64.66%. Productive and stable clones guarantee a relatively stable income over the years and ensure the grower’s long-term engagement in the activity.