Cell cycle events and expression of cell cycle regulators are determining factors in differential grain filling in rice spikelets based on their spatial location on compact panicles.

Rice being a staple crop for human, its production is required to be increased significantly, particularly keeping in view the expected world's population of 9.6 billion by the year 2050. In this context, although the rice breeding programs have been successful in increasing the number of spikelets per panicle, the basal spikelets remain poorly filled, undermining the yield potential. The present study also found the grain filling to bear negative correlation with the panicle grain density. The poorly filled basal spikelets of the compact-panicle cultivars showed a lower endosperm cell division rate and ploidy status of the endosperm nuclei coupled with no significant greater expression of CYCB;1 and CYCH;1 compared with the apical spikelets, unlike that observed in the lax-panicle cultivars, which might have prevented them from overcoming apical dominance. Significantly greater expression of CYCB2;2 in the basal spikelets than in the apical spikelets might also have prevented the former to enter into endoreduplication. Furthermore, expression studies of KRPs in the caryopses revealed that a higher expression of KRP;1 and KRP;4 in the basal spikelets than in the apical spikelets of the compact-panicle cultivars could also be detrimental to grain filling in the former, as KRPs form complex primarily with CDKA-CYCD that promotes S-phase activity and G1/S transition, and thus inhibits endosperm cell division. The study indicates that targeted manipulation of expression of CYCB1;1, CYCB2;2, CYCH1;1, KRP;1 and KRP4 in the basal spikelets of the compact-panicle cultivars may significantly improve their yield performance.

Grain density and its impact on grain filling characteristic of rice: mechanistic testing of the concept in genetically related cultivars.

Physiological factors controlling assimilate partitioning was compared in relation to panicle architecture of lax- (Upahar) and compact-panicle (Mahalaxmi) rice cultivars. Grain number and ethylene production at anthesis are low, but filling rate is high in the former compared to high grain number and ethylene production and poor filling trait of the latter. Similar to Mahalaxmi, its progenitors Pankaj and Mahshuri, had attributes of high grain number and grain density, but grain filling was higher and ethylene evolution was lower. Disturbed genetic coherence owing to imbalance of gene groups brought in the cross combinations of Mahshuri and Pankaj could be responsible for high ethylene production leading to semi sterility of Mahalaxmi as the hormone slackened endosperm starch bio-synthesis enzyme activities. Mahalaxmi inherited grain compactness trait of its progenitors, but not the physiological attribute for reduced ethylene production, which impacted grain filling. Upahar, the progeny genotype of Mahalaxmi and IR62 cross, inherited the dominant allele for low ethylene production and good grain filling traits from the high yielding IR62. In conclusion grain filling in compact-panicle rice becomes poor subject to expression of recessive allele for high ethylene production, but the allele is amenable for suppression by corresponding dominant allele in a genetic breeding.

Quantitative monitoring of sucrose, reducing sugar and total sugar dynamics for phenotyping of water-deficit stress tolerance in rice through spectroscopy and chemometrics.

In the present investigation, the changes in sucrose, reducing and total sugar content due to water-deficit stress in rice leaves were modeled using visible, near infrared (VNIR) and shortwave infrared (SWIR) spectroscopy. The objectives of the study were to identify the best vegetation indices and suitable multivariate technique based on precise analysis of hyperspectral data (350 to 2500nm) and sucrose, reducing sugar and total sugar content measured at different stress levels from 16 different rice genotypes. Spectral data analysis was done to identify suitable spectral indices and models for sucrose estimation. Novel spectral indices in near infrared (NIR) range viz. ratio spectral index (RSI) and normalised difference spectral indices (NDSI) sensitive to sucrose, reducing sugar and total sugar content were identified which were subsequently calibrated and validated. The RSI and NDSI models had R2 values of 0.65, 0.71 and 0.67; RPD values of 1.68, 1.95 and 1.66 for sucrose, reducing sugar and total sugar, respectively for validation dataset. Different multivariate spectral models such as artificial neural network (ANN), multivariate adaptive regression splines (MARS), multiple linear regression (MLR), partial least square regression (PLSR), random forest regression (RFR) and support vector machine regression (SVMR) were also evaluated. The best performing multivariate models for sucrose, reducing sugars and total sugars were found to be, MARS, ANN and MARS, respectively with respect to RPD values of 2.08, 2.44, and 1.93. Results indicated that VNIR and SWIR spectroscopy combined with multivariate calibration can be used as a reliable alternative to conventional methods for measurement of sucrose, reducing sugars and total sugars of rice under water-deficit stress as this technique is fast, economic, and noninvasive.