Water-intensive systems of rice cultivation are facing major challenges to increase rice grain yield under conditions of water scarcity while also reducing greenhouse gas (GHG) emissions. The adoption of effective irrigation strategies in the paddy rice system is one of the most promising options for mitigating GHG emissions while maintaining high crop yields. To evaluate the effect of different alternate wetting and drying (AWD) irrigation strategies on GHG emissions from paddy rice in dry and wet seasons, a field experiment was conducted at the Tamil Nadu Rice Research Institute (TRRI), Aduthurai, Tamil Nadu, India. Four irrigation treatments were included: One-AWD (one early drying period), Two-AWD (two early drying periods), Full-AWD (wetting and drying cycles throughout the rice season), and CF (continuous flooding). Different rice varieties were also tested in the experiment. In this study, we emphasized one factor (irrigation effect) that affects the dependent variable. The results show that early AWD treatments reduced methane (CH₄) emissions by 35.7 to 51.5% in dry season and 18.5 to 20.1% in wet season, while full-AWD practice reduced CH₄ emissions by 52.8 to 61.4% compared with CF. Full-AWD in dry season not only significantly reduced CH₄ emission during that season, it also resulted in the decline of the early season emission in the succeeding wet season. Global warming potential (GWP) and yield-scaled GWP were reduced by early or full season AWD in both rice seasons. The GWP value from nitrous oxide (N₂O) was relatively low compared to that from CH₄ in both rice seasons. Rice yield was not affected by irrigation treatments although varietal differences in grain and straw yields were observed in both rice seasons. This study demonstrated that early season water managements are also effective in reducing CH₄ and total GHG emissions without affecting rice yield.

Two-year field experiments were conducted at Tamil Nadu Rice Research Institute, Aduthurai, Tamil Nadu, India, to evaluate the effect of continuous flooding (CF) and alternate wetting and drying (AWD) irrigation strategies on rice grain yield and greenhouse gas emissions from double-cropping paddy rice. Field observation results showed that AWD irrigation was found to reduce the total seasonal methane (CH₄) emission by 22.3% to 56.2% compared with CF while maintaining rice yield. By using the observed two-year field data, validation of the DNDC-Rice model was conducted for CF and AWD practices. The model overestimated rice grain yield by 24% and 29% in CF and AWD, respectively, averaged over the rice-growing seasons compared to observed values. The simulated seasonal CH₄ emissions for CF were 6.4% lower and 4.2% higher than observed values and for AWD were 9.3% and 12.7% lower in the summer and monsoon season, respectively. The relative deviation of simulated seasonal nitrous oxide (N₂O) emissions from observed emissions in CF were 27% and −35% and in AWD were 267% and 234% in the summer and monsoon season, respectively. Although the DNDC-Rice model reasonably estimated the total CH₄ emission in CF and reproduced the mitigation effect of AWD treatment on CH₄ emissions well, the model did not adequately predict the total N₂O emission under water-saving irrigation. In terms of global warming potential (GWP), nevertheless there was a good agreement between the simulated and observed values for both CF and AWD irrigations due to smaller contributions of N₂O to the GWP compared with that of CH₄. This study showed that the DNDC-Rice model could be used for the estimation of CH₄ emissions, the primary source of GWP from double-cropping paddy rice under different water management conditions in the tropical regions.

Addressing micronutrient deficiency is increasingly recognized as a critical aspect of food and nutrition security in developing nations. Leveraging diverse genetic resources offers a promising avenue for identifying and enhancing micronutrient-rich genotypes through breeding strategies, thus providing sustainable solutions to this pressing challenge. The study aimed to identify rice genotypes with high Fe content and to study the extent of genetic divergence based on morphological and grain quality traits in a set of 50 native rice landraces over 2 different locations. A wide range of variation for grain Fe content was observed among the studied genotypes, which varied from 9.28–14.45 mg kg-1 and 1.88–4.87 mg kg-1 in brown and polished rice respectively. Results showed that the genotypes Jaya, Kalanamak, Kottara Samba, Gandakasala and Gopalbhog recorded high grain Fe content before polishing whereas Kottara Samba, Kalapathi Black, Jyothi, Chinnar and Kalanamak were found to have high Fe content after polishing. Interestingly, landraces possessing red seed coat color and medium slender grain group were identified to possess high grain Fe content. This was further substantiated by the correlation study where kernel breadth recorded a negative association with Fe content after polishing. Clustering resulted in 5 groups where the high Fe content possessing genotypes were grouped into clusters 2 and 4. Thus, these genotypes could be utilized as donors in further bio-fortification breeding programs.