HarvestPlus

Biofortification: Conventional plant breeding to increase the nutrient density of commonly consumed staple foods

An ex-ante analysis of the impact of biofortified zinc rice on dietary zinc inadequacy: Evidence from Bangladesh, Indonesia, and the Philippines

Background: South, East, and Southeast Asia are among the regions of the world with the highest estimated prevalence of inadequate zinc intake. Because populations in those regions eat rice as their main staple, zinc biofortification of rice can potentially improve zinc intake, especially among the most vulnerable. Objectives: We modeled the impact of the consumption of zinc-biofortified rice on zinc intake and inadequacy among women of childbearing age and young children nationally in Indonesia, the Philippines, and at a subnational level in Bangladesh. Methods: We conducted an ex-ante analysis by applying increments of zinc content in rice, from a baseline level of 16 parts per million (ppm) to 100 ppm, and based on rice consumption data to substitute levels of conventional rice with zinc-biofortified rice varying between 10% and 70%. Results: Among all datasets evaluated from these 3 countries, the prevalence of dietary zinc inadequacy at baseline was 94%–99% among women of childbearing age, 77%–100% among children 4–5 y old, and 27%–78% among children 1–3 y old. At the current breeding target of 28 ppm, zinc-biofortified rice has the potential to decrease zinc inadequacy by ≤50% among women and children in rural Bangladesh and among children in the Philippines where consumption of rice is higher compared with Indonesia. Conclusions: Our analysis shows that increasing zinc content in rice ≤45 ppm reduces the burden of zinc inadequacy substantially, after which we encourage programs to increase coverage to reach the highest number of beneficiaries.

Modeling and simulation of recurrent phenotypic and genomic selections in plant breeding under the presence of epistasis

Recurrent selection is an important breeding method for population improvement and selecting elite inbreds or fixed lines from the improved germplasm. Recently, a computer simulation tool called QuMARS has been developed, which allows the simulation and optimization of various recurrent selection strategies. Our major objective in this study was to use the QuMARS tool to compare phenotypic recurrent, marker-assisted recurrent, and genomic selections (abbreviated respectively as PS, MARS and GS) for both short- and long- term breeding procedures. For MARS, two marker selection models were considered, i.e., stepwise (Rstep) and forward regressions (Forward). For GS, three prediction models were considered, i.e., genomic best linear unbiased predictors (GBLUP), ridge regression (Ridge), and regression by Moore-Penrose general inverse (InverseMP). To generate genotypes and phenotypes for a given individual during simulation, one additive and two epistasis genetic models were considered with three levels of heritability. Results demonstrated that selection responses from GBLUP-based GS and MARS (Forward) were consistently greater than those from PS under the additive model, particularly in early selection cycles. In contrast, selection response from PS was consistently superior over MARS and GS under epistatic models. For the two epistasis models, total genetic variance and the additive variance component were increased in some cases after selection. Through simulation, we concluded that GS and PS were effective recurrent selection methods for improved breeding of targeted traits controlled by additive and epistatic quantitative trait loci (QTL). QuMARS provides an opportunity for breeders to compare, optimize and integrate new technology into their conventional breeding programs.