Developing a system of temperate and tropical aerobic rice in Asia (STAR)

The project “Developing a System of Temperate and Tropical Aerobic Rice in Asia (STAR) undertook strategic research to develop sustainable aerobic rice systems for water- scarce irrigated and rainfed environments in Asia. Aerobic rice is a production system in which specially developed rice varieties are grown in nonsaturated soils without ponded water just like wheat or maize. The target environments are areas where water is too short to grow conventional lowland rice, either rainfed or supplementary irrigated. In the Yellow River Basin of China, with a temperate climate, we have demonstrated that aerobic rice yields of 6 t ha-1 are attainable with about half of the water needed to grow lowland rice. In average rainfall years, farmers would need to give only 2-3 supplemental irrigations. The profitability is comparable with that of other food crops such as maize and soybean, depending on (yearly fluctuating) relative commodity prices (sometime profitability is lower, sometimes higher). Farmers like aerobic rice because it contributes to food self-sufficiency and requires less labor than transplanted lowland rice. It also allows them to diversify their cropping system. Moreover, aerobic rice can stand flooding and is an ideal crop for the large areas that get annually flooded by heavy rainfall or overflowing rivers that destroy the other crops. In the tropics, the development of aerobic rice is less advanced. In central India, in the Indo-Gangetic Plain, we identified rice varieties that can be grown in aerobic conditions, producing 4- 4.5 t ha-1 and using 30-40% less water than lowland rice at the same yield level. In the Philippines, although yield potentials of 6 t ha-1 have been demonstrated, attainable yield ranged from 2.9 to 3.8 t ha-1 in the dry season, and from 3.9 to 4.5 t ha-1 in the wet season. A risk of yield decline was demonstrated at a few sites caused by soil-borne pests (such as nematodes), nutrient disorders, or a combination of both. In our sites in Northeast Thailand and Laos, breeding lines were identified with yield potentials of 2 (Thailand) to 3.5 (Laos) t ha-1. Further research and development is needed to bring tropical aerobic rice to fruition, mainly on variety improvement (increasing yield potential and adaptation to aerobic soil) and sustainability. In conclusion, aerobic rice holds promise for those farmers in water-short irrigated or rainfed environments where water availability at the farm level is too low, or where water is too expensive, to grow flooded lowland rice

Linking X-band radar backscattering and optical reflectance with crop growth models

This thesis describes an investigation into the possibilities of linking X-band radar backscattering and optical remote sensing data with crop growth models for the monitoring of crop growth. The emphasis is on the usability of X-band radar data, with a detailed analysis of the main backscattering influencing factors of agricultural crops in The Netherlands.Six-years of ground-based X-band radar observations (VV and HH polarized, 10° to 80° incidence angle) were used to study the temporal radar backscattering of sugar beet, potato, wheat, barley and oats. The geometry of the crop canopy was found to be a major backscattering influencing factor, especially for the cereals. The possibilities of crop growth parameter (soil cover, biomass, height) estimation from the radar data were investigated using empirical and simple physical relationships. Except for sugar beet in the early growing season, the accuracies of parameter estimation were generally too low to be used in crop growth models.In the optical region, the accuracy of estimating the leaf area index ( LAI ) from vegetation indices was studied. In a case study for sugar beet, the LAI was fairly accurately estimated from the so-called Weighted Difference Vegetation Index ( WDVI ).Two methodologies were developed to link X-band radar and optical remote sensing data with crop growth models. In the first method, remote sensing data were used to estimate the fraction soil cover of a crop as input for a simple lightinterception growth model. This method was especially suitable for the use of optical remote sensing data. The use of X-band radar data was only feasible for sugar beet.In the second method, X-band radar and optical remote sensing data were used to initialize and re-parameterize the crop growth simulation model SUCROS (Simple and Universal Crop Growth Simulator). In six years of sugar beet observations, this method improved the simulation of canopy biomass over the use of SUCROS only. The radar and optical reflectance data were very effective in the initialization of SUCROS, and in adjusting the model during early, exponential crop growth. Optical data also adjusted SUCROS in the middle of the growing season