Abstract
AbstractThe frequent fluctuations in global climate variability (GCV), decreases in farmland and irrigation water, soil degradation and erosion, and increasing fertilizer costs are the significant factors in declining rice productivity, mainly in Asia and Africa. Under GCV scenarios, it is a challenging task to meet the rice food demand of the growing population. Identifying green traits (tolerance of biotic and abiotic stresses, nutrient-use efficiency, and nutritional grain quality) and stacking them in high-yielding elite genetic backgrounds is one promising approach to increase rice productivity. To this end, the Green Super Rice (GSR) breeding strategy helps to pool multi-stress-tolerance traits by stringent selection processes and to develop superior GSR cultivars within a short span of 4–5 years. In the crossing and selection process of GSR breeding, selective introgression lines (SILs) derived from sets of early backcross BC1F2bulk populations through both target traits and non-target traits were selected. Genotyping of SILs with high-density SNP markers leads to the identification of a large number of SNP markers linked with the target green traits. The identified SILs with superior trait combinations were used for designed QTL pyramiding to combine different target green traits. The GSR breeding strategy also focused on nutrient- and water-use efficiency besides environment-friendly green features primarily to increase grain yield and income returns for resource-poor farmers. In this chapter, we have highlighted the GSR breeding strategy and QTL introgression of green traits in rice. This breeding strategy has successfully dissected many complex traits and also released several multi-stress-tolerant varieties with high grain yield and productivity in the target regions of Asia and Africa.
Highlights
Food security is a global challenge for plant researchers to increase crop productivity, especially under changing climatic conditions
These include the critical genes OsAAP6 on chromosome 1, OsNPF7.2 and GROWTH-REGULATOR FACTOR 4 (OsGRF4) on chromosome 2, three genes (GNP1, lgy3, and GL3) on chromosome 3, two genes (Chalk5 and GW5) on chromosome 5, two genes (W7 and OsSPL13) on chromosome 7, and a single gene (OsOTUB1) on chromosome 8 associated with grain quality traits, and some of these genes are significantly associated with yield- attributed traits and Nutrient-use efficiency (NUE) traits (Li et al 2018)
In the Green Super Rice (GSR) breeding program, we primarily focused on dissecting complex abiotic traits
Summary
Food security is a global challenge for plant researchers to increase crop productivity, especially under changing climatic conditions. More than 800 million people are affected by malnutrition, hindering sustainable development programs, and food demand is expected to increase by 59–98% by 2050 (Elferink and Schierhorn 2016) Apart from this great challenge, increased global climate variability (GCV) (abiotic stresses: drought, salinity, low/high temperature, submergence/flooding; and biotic stresses: blast, bacterial leaf blight, brown planthopper, etc.) and decreasing natural resources (NRS) (e.g., decreased availability of irrigation water, labor scarcity, arable land reduction, and soil nutrient deficiency and toxicity) are the foremost factors that slow the pace toward food security for the global population. It is essential to develop highyielding, multiple-stress-tolerant rice varieties with combinations of several green traits such as tolerance of/resistance to drought, salinity, high/low temperature, flooding, blast, bacterial blight, tungro, brown planthopper, and stem borer, along with water-use efficiency These multi-stress-tolerant varieties need to meet market segment requirements such as duration, grain shape, and quality preferences. The incorporation of desirable nutrients for improved grain quality such as iron and zinc in multi-stress-tolerant cultivars has become necessary in rice improvement programs to ensure food security and overcome hidden hunger (Ali et al 2020; Yu et al 2020)
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