Low Light During Grain Filling Stage Deteriorates Rice Cooking Quality, but not Nutritional Value

To investigate the effect of low light （LL, 50% natural light） during grain filling （GF） stage on rice transamination, amino acid （AA） accumulation, nutritional value, and cooking quality in three different rice genotypes, transaminase activities and AA levels in grains during GF stage and the traits that significantly affected rice quality （physical appearance, cooking quality, and nutritional value） were analyzed. LL did not disturb transamination in rice grains during GF stage, as minimal impact was found on alanine and aspartate transaminase activities. Nevertheless, most AAs in caryopses, including lysine and threonine, increased in response to LL, except for sulfur-containing AAs. These results suggest that AA metabolism and accumulation in rice grains were rarely suppressed by LL during GF stage. Rice nutritional ingredients at harvest, such as major protein components including glutelin and most important essential amino acids （EAAs） including lysine and threonine, increased significantly in response to LL, whereas most protein and EAA ratios were rarely affected. However, LL markedly affected physical appearance of rice grains by reducing brown rice rate, milled rice rate, and 1000-grain weight and increasing the chalkiness rate. In addition, cooking qualities decreased in response to LL, while breakdown values and amylose levels decreased and setback values increased. We concluded that LL during GF stage decreased the cooking quality of rice, but could potentially improve the nutritional value of rice.

Index selection on seed traits under direct,cytoplasmic and maternal effects in multiple environments

Crop seeds are important sources of protein, oil, and carbohydrates for food, animal feeds, and industrial products. Recently, much attention has been paid to quality and functional properties of crop seeds. However, seed traits possess some distinct genetic characteristics in comparison with plant traits, which increase the difficulty of genetically improving these traits. In this study, diallel analysis for seed models with genotype by environment interaction （GE） effect was applied to estimate the variance-covariance components of seed traits. Mixed linear model approaches were used to estimate the genetic covariances between pair-wise seed and plant traits. The breeding values （BV） were divided into two categories for the seed models. The first category of BV was defined as the combination of direct additive, cytoplasmic, and maternal additive effects, which should be utilized for selecting stable cultivars over multi-environments. The three genetic effects, together with their GE interaction, were included in the second category of BV for selecting special lines to be grown in specific ecosystems. Accordingly, two types of selection indices for seed traits, i.e., general selection index and interaction selection index, were developed and constructed on the first and the second category BV, respectively. These proposed selection indices can be applied to solve the difficult task of simultaneously improving multiple seed traits in various environments. Data of crop seeds with regard to four seed traits and four yield traits based on the modified diallel crosses in Upland cotton （Gossypium hirsutum L.） were used as an example for demonstrating the proposed methodology.