Breeding Rice for Drought-Prone Environments

A large portion of the world’s poor farm in rainfed systems where the water supply is unpredictable and droughts are common. In Asia, about 50% of all the rice land is rainfed and, although rice yields in irrigated systems have doubled and tripled over the past 30 years, only modest gains have occurred in rainfed rice systems. In part, this is because of the difficulty in improving rice varieties for environments that are heterogeneous and variable, and in part because there has been little effort to breed rice for drought tolerance. Information available for other cereals (for example, maize, Bänziger et al 2000) and for wheat and the limited or circumstantial evidence available for rice indicate that we can now breed varieties that have improved yield under drought and produce high yields in the good seasons. This manual aims to help plant breeders develop such varieties. While the manual focuses on drought tolerance, this must be integrated with the mainstream breeding program that also deals with agronomic adaptation, grain quality, and pest and disease resistance. Mackill et al (1996) have written a guide to the overall improvement of rice for rainfed conditions. This manual should be seen as an amplification of and updating of the section on drought tolerance in that book. Because final proof of many approaches for breeding drought-tolerant rice is not yet available, and because some aspects may not work in all environments and germplasm, we recommend that you use this manual with caution. Test the suggested approaches and only implement them on a large scale if they are effective and realistic for your own situation

Peanut farmers experience with FARMSCAPE in peninsular India

Researchers and extension officers collaborated with farmers in addressing peanut cropping and sowing decisions using on-farm experiments and cropping systems simulation in the Pollachi region of Tamil Nadu, India. The most influential variable affecting the peanut productivity in this irrigated region regard sowing date. During the 1998-1999 rabi (post rainy) season, three farmers fields in villages in Pollachi region were selected and monitored. The APSIM model was used to simulate the effect of sowing date. The APSIM-Peanut module simulation demonstrated close correspondence with the field observation in predicting yield. The model predicted that December sowing resulted in higher yield than January sowing due to longer pod filling period, and this was confirmed by farmer experience. The farmers and extension officers became comfortable with their role as owners of the collaborative experiments and custodians of the learning environment.