The potential of near-infrared reflectance spectroscopy (NIRS) for simultaneous analysis of grain weight (mg), brown rice weight (mg) and milled rice amylose content (AC, %) in single rice grains was studied. Calibration equations were developed using 474 single grain samples, scanned as both rice grain and brown rice. An independent set containing 90 F2 generation grains was used to validate the equations. In general, equations developed using the first derivative resulted in superior calibration and validation statistics compared with the second derivative and those developed using brown rice were superior to those developed from the rice grain. Fitting equations were developed and monitored with an external validation set. The standard error of prediction (corrected for bias) SEP(C) for AC, brown rice weight and rice grain weight for equations developed using brown rice were 2.82, 1.09 and 1.30, with corresponding coefficient of determinations (r2) of 0.85, 0.71 and 0.67, and SEP(C)/S.D. of 0.39, 0.57 and 0.59, respectively. It was demonstrated that NIRS provides a convenient way to screen single intact grains. This will be advantageous in early generation selection in rice breeding programs.

The aim of this study was to evaluate the potential of near-infrared reflectance spectroscopy (NIRS) as a rapid method to estimate the cooking characteristics of rice. A total of 586 samples from rice breeding lines from 1999 to 2002, which had high variation for agronomy, location and year, were scanned by NIRS for calibration optimization by chemometric methods. Two subsets of 212 samples from one year and 400 samples from three years were employed to find suitable sample status for extending the NIRS utilities. There were three algorithms of PCA, PL1 and PL2, in which the first one was only based on the sample spectra variant and the remaining two based on the variant of both spectra and chemical characteristics to describe the relationship between any two neighboring samples. According to the results of calibration and validation by the three algorithms used, the suitable calibration samples could be chosen by the cutoff of neighborhood distance (NH) of 0.35, 0.4 and 0.45, respectively. For the cooking characteristics, the combination of SNV+D/4,4,1 was the best pretreatment and the accuracy models were obtained with low SECV and high 1 VRof amylose content (1.42% and 0.95%), gel consistency (9.49 and 0.76 mm) and alkali spread value (0.86 and 0.79 grade) . The models developed using brown rice and milled rice were superior to those using intact rice grains, but slightly poorer to those using their corresponding flour samples. Therefore, on-line monitoring of rice quality could be conducted in rice processing at milling stages. Due to the fewer sample mass destroyed, the brown rice (3 g) and brown rice flour (3g or 0.5g), by which the NIRS models were successfully developed for cooking characteristic analyses, could be introduced into quality evaluation of germplasm and intermediate lines selection in breeding projects.

The low fertility of naked seed rice (NSR) was investigated by the following observations: somatic chromosome constitute, behavior of pollen mother cells (PMCs), the germination of mature pollen grains, the development of male and female gametes and the structure of the anther opening. The results indicated that somatic chromosomal number was 2n=24, behavior of PMCs were normal and most of pollen grains could regularly develop further to mature male gametophytes in NSR. And dehiscence chamber and thickened endothecium cell (TEC) in numerous anthers of the NSR were developed abnormally after dicaryotic phase, result in few anthers complete opening and most partly opening or failure to opening, therefore much fewer of pollen grains attach on the stigma as compared with normal variety. Furthermore most of embryo sacs possessed abnormal structure and were sterile. All of above illustrated that the failure of the anther opening and the abortion of female gametophyte were main factors controlling the low seed-setting rate of the NSR.

The genetic effects of the cooking quality traits amylose content (AC) and gel consistency (GC) of japonica rice were analyzed by using a genetic model including genotype environment (GE) interaction effects for quality traits of the endosperm in cereal crops. The results indicated that AC and GC of japonica rice were greatly controlled by the genetic main effects from endosperm, cytoplasm and maternal plant genes, but were also affected by GE interaction effects. The endosperm effects were most important among genetic main effects for the performance of AC and GC, while the cytoplasmic interaction effect or maternal interaction effects for AC or GC were more essential among GE interaction effects, respectively. Additive effects and cytoplasmic interaction effect were the main factors ontrolling the performance of AC, but GC was mainly affected by additive effects, additive interaction effects and cytoplasmic interaction effect. The endosperm general heritabilities were the largest ones among heritability components for AC and GC. A significant negative genotypic correlation was found between AC and GC. The genetic effects predicted for 13 parents showed that Liaojing 326 A and Hu 161 were the better parents for improving the rice cooking quality traits.

Using a newly developed mapping model with endosperm and maternal main effects and QTL environment interaction effects on quantitative quality traits of seed in cereal crops, the investigation of quantitative trait loci (QTLs) located on triploid endosperm and diploid maternal plant genomes for protein content and lysine content of rice grain under different environments was carried out with two backcross (BC1F1 and BC2F1) populations from a set of 241 recombinant inbred lines derived from an elite hybrid cross of Shanyou 63. The results showed a total of 18 QTLs to be associated with these two quality traits of rice, which were subsequently mapped on chromosomes 2, 3, 5, 6, 7, 10, 11 and 12. Three of these QTLs were also found havingQTL environment interaction effects. Therefore, the genetic main effects from QTLs located on chromosomes in endosperm and maternal plant genomes and their QTL environment interaction effects in different environments were all important for protein and lysine contents in rice. The influence of environmental factors on the expression of some QTLs located in different genetic systems could not be ignored for both nutrient quality traits.