Effect of water availability pattern on yield of pearl millet in semi-arid tropical environments

Throughout much of the semi-arid tropics, fluctuations in grain yield can largely be attributed to differences in timing and intensity of drought stress. Since seasonal rainfall in these environments is often poorly related to grain yield, the aim of this paper was to establish a relationship between water availability and grain yield for pearl millet (Pennisetum glaucum (L.) R. Br.), grown across 24 semi-arid tropical environments in India. We used a simple soil water budget to calculate a water satisfaction index (WSI) throughout the season. The cumulative WSI at maturity explained 76% of the variance in grain yield. This was three times as much as explained by actual rainfall, because WSI accounted for differences in water losses and pan evaporation. A classification of environments into four groups of water availability patterns explained 75% of the environmental sum of squares for grain yield. For a subset of 13 environments, environmental differences in grain number could also be explained by water availability patterns, whereas differences in grain mass were related to both water availability and temperature. Our results indicate that cumulative WSI, which is an integrated measure of plant-available water, can provide an adequate estimation of the environmental potential for yield in environments where grain yield is mainly limited by variable availability of water

Application of the Hybrid-Maize model for limits to maize productivity analysis in a semiarid environment

Effects of meteorological variables on crop production can be evaluated using various models. We have evaluated the ability of the Hybrid-Maize model to simulate growth, development and grain yield of maize (Zea mays L.) cultivated on the Loess Plateau, China, and applied it to assess effects of meteorological variations on the performance of maize under rain-fed and irrigated conditions. The model was calibrated and evaluated with data obtained from field experiments performed in 2007 and 2008, then applied to yield determinants using daily weather data for 2005-2009, in simulations under both rain-fed and irrigated conditions. The model accurately simulated Leaf Area Index , biomass, and soil water data from the field experiments in both years, with normalized percentage root mean square errors < 25 %. Gr.Y and yield components were also accurately simulated, with prediction deviations ranging from -2.3 % to 22.0 % for both years. According to the simulations, the maize potential productivity averaged 9.7 t ha-1 under rain-fed conditions and 11.53 t ha-1 under irrigated conditions, and the average rain-fed yield was 1.83 t ha-1 less than the average potential yield with irrigation. Soil moisture status analysis demonstrated that substantial potential yield may have been lost due to water stress under rain-fed conditions

Transpiration and leaf growth of potato clones in response to soil water deficit

Potato (Solanum tuberosum ssp. Tuberosum) crop is particularly susceptible to water deficit because of its small and shallow root system. The fraction of transpirable soil water (FTSW) approach has been widely used in the evaluation of plant responses to water deficit in different crops. The FTSW 34 threshold (when stomatal closure starts) is a trait of particular interest because it is an indicator of tolerance to water deficit. The FTSW threshold for decline in transpiration and leaf growth was evaluated in a drying soil to identify potato clones tolerant to water deficit. Two greenhouse experiments were carried out in pots, with three advanced clones and the cultivar Asterix. The FTSW, transpiration and leaf growth were measured on a daily basis, during the period of soil drying. FTSW was an efficient method to separate potato clones with regard to their response to water deficit. The advancedclones SMINIA 02106-11 and SMINIA 00017-6 are more tolerant to soil water deficit than the cultivar Asterix, and the clone SMINIA 793101-3 is more tolerant only under high solar radiation

Forecasting Australian sugar yields using phases of the Southern Oscillation Index

Yields for the Australian sugar industry can vary seasonally and regionally. Advanced knowledge of likely sugar productivity levels for mill regions in a particular season would assist marketers to forward sell Australian sugar, and allow mill managers and harvest operators to better plan for the coming season. Given that climate is a key driver of productivity, the purpose of this paper is to investigate the potential usefulness of a climate forecast system which incorporates five patterns or phases of the Southern Oscillation Index (SOI) to forecast sugar yields. The chance of obtaining a sugar yield above the long-term median was computed for each SOI phase across eight regions which span the coastline of Queensland, where most of Australia's sugarcane is grown. Results indicate that for certain regions, the chance of obtaining an above average crop can be greatly increased, and in some cases decreased depending on the phase of the SOI. Since many decisions in the Australian sugar industry are based on crop size, the SOI phases provide a useful tool for enhancing decision making and risk management capability for the industry