1000 resultados para 300299 Crop and Pasture Production not elsewhere classified


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Leaf area growth and nitrogen concentration per unit leaf area, N-a (g m(-2) N) are two options plants can use to adapt to nitrogen limitation. Previous work indicated that potato (Solanum tuberosum L.) adapts the size of leaves to maintain Na and photosynthetic capacity per unit leaf area. This paper reports on the effect of N limitation on leaf area production and photosynthetic capacity in maize, a C4 cereal. Maize was grown in two experiments in pots in glasshouses with three (0.84-6.0 g N pot(-1)) and five rates (0.5-6.0 g pot(-1)) of N. Leaf tip and ligule appearance were monitored and final individual leaf area was determined. Changes with leaf age in leaf area, leaf N content and light-saturated photosynthetic capacity, P a,, were measured on two leaves per plant in each experiment. The final area of the largest leaf and total plant leaf area differed by 16 and 29% from the lowest to highest N supply, but leaf appearance rate and the duration of leaf expansion were unaffected. The N concentration of expanding leaves (N-a or %N in dry matter) differed by at least a factor 2 from the lowest to highest N supply. A hyperbolic function described the relation between P-max and N-a. The results confirm the 'maize strategy': leaf N content, photosynthetic capacity, and ultimately radiation use efficiency is more sensitive to nitrogen limitation than are leaf area expansion and light interception. The generality of the findings is discussed and it is suggested that at canopy level species showing the 'potato strategy' can be recognized from little effect of nitrogen supply on radiation use efficiency, while the reverse is true for species showing the 'maize strategy' for adaptation to N limitation. (c) 2004 Elsevier B.V. All rights reserved.

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Analysis of gene flow and migration of Helicoverpa armigera (Hubner) in a major cropping region of Australia identified substantial genetic structuring, migration events, and significant population genotype changes over the 38-mo sample period from November 1999 to January 2003. Five highly variable microsatellite markers were used to analyze 916 individuals from 77 collections across 10 localities in the Darling Downs. The molecular data indicate that in some years (e.g., April 2002-March 2003), low levels of H. armigera migration and high differentiation between populations occurred, whereas in other years (e.g., April 2001-March 2002), there were higher levels of adult moth movement resulting in little local structuring of populations. Analysis of populations in other Australian cropping regions provided insight into the quantity and direction of immigration of H. armigera adults into the Darling Downs growing region of Australia. These data provide evidence adult moth movement differs from season to season, highlighting the importance of studies in groups such as the Lepidoptera extending over consecutive years, because short-term sampling may be misleading when population dynamics and migration change so significantly. This research demonstrates the importance of maintaining a coordinated insecticide resistance management strategy, because in some years H. armigera populations may be independent within a region and thus significantly influenced by local management practices; however, periods with high migration will occur and resistance may rapidly spread.

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Sorghum is the main dryland summer crop in NE Australia and a number of agricultural businesses would benefit from an ability to forecast production likelihood at regional scale. In this study we sought to develop a simple agro-climatic modelling approach for predicting shire (statistical local area) sorghum yield. Actual shire yield data, available for the period 1983-1997 from the Australian Bureau of Statistics, were used to train the model. Shire yield was related to a water stress index (SI) that was derived from the agro-climatic model. The model involved a simple fallow and crop water balance that was driven by climate data available at recording stations within each shire. Parameters defining the soil water holding capacity, maximum number of sowings (MXNS) in any year, planting rainfall requirement, and critical period for stress during the crop cycle were optimised as part of the model fitting procedure. Cross-validated correlations (CVR) ranged from 0.5 to 0.9 at shire scale. When aggregated to regional and national scales, 78-84% of the annual variation in sorghum yield was explained. The model was used to examine trends in sorghum productivity and the approach to using it in an operational forecasting system was outlined. (c) 2005 Elsevier B.V. All rights reserved.

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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.