12 research outputs found

    Modeling the Impact of climate change on Peanut Production on the Basis of Increasing 2oc temperature in Future Environmental conditions of guilan Province, Iran

    Get PDF
    To evaluate the effect of climate change on peanut production in Northern Iran on the basis of 2oC rise in temperature, a study was conducted using the SSM-Peanut. The simulation was done based on the long-term data obtained from synoptic stations in Guilan including Anzali, Astara, Kiashahr (Astaneh Ashrafieh), Lahijan, Rasht (Agriculture station), Rasht (Airport station), Roudsar and Talesh. When model was run for each year and each scenario, the following parameters were recorded in the outputs: days to beginning bloom, days to beginning pod, days to beginning seed, days to harvest maturity, maximum leaf area index, accumulated crop dry matter, seed yield, and pod yield. Data analysis: data analysis was done using SPSS 18. Furthermore, from ArcGIS was used for zoning of Guilan in terms of peanut production in the current condition and after the climate change. To compare the difference between peanut growth and yield in the current condition and when the climate change happens, t-test and discriminant analysis were used. The results showed that there is a statistically significant difference in terms of all parameters between the current condition and after climate change 2oC rise in temperature) in Guilan Province. With the rise temperature, average peanut growth period in Guilan decreased from 142 days to 123 days. Generally, the average peanut yield changes in Guilan with 2- degree rise in temperature is 8.73 percent more than that in the current condition

    Mapping Water Stress Incidence and Intensity, Optimal Plant Populations, and Cultivar Duration for African Groundnut Productivity Enhancement

    Get PDF
    Groundnut production is limited in Sub-Saharan Africa and water deficit or “drought,” is often considered as the main yield-limiting factor. However, no comprehensive study has assessed the extent and intensity of “drought”-related yield decreases, nor has it explored avenues to enhance productivity. Hence, crop simulation modeling with SSM (Simple Simulation Modeling) was used to address these issues. To palliate the lack of reliable weather data as input to the model, the validity of weather data generated by Marksim, a weather generator, was tested. Marksim provided good weather representation across a large gradient of rainfall, representative of the region, and although rainfall generated by Marksim was above observations, run-off from Marksim data was also higher, and consequently simulations using observed or Marksim weather agreed closely across this gradient of weather conditions (root mean square of error = 99 g m-2; R2 = 0.81 for pod yield). More importantly, simulation of yield changes upon agronomic or genetic alterations in the model were equally predicted with Marksim weather. A 1° × 1° grid of weather data was generated. “Drought”-related yield reduction were limited to latitudes above 12–13° North in West Central Africa (WCA) and to the Eastern fringes of Tanzania and Mozambique in East South Africa (ESA). Simulation and experimental trials also showed that doubling the sowing density of Spanish cultivars from 20 to 40 plants m-2 would increase yield dramatically in both WCA and ESA. However, increasing density would require growers to invest in more seeds and likely additional labor. If these trade-offs cannot be alleviated, genetic improvement would then need to re-focus on a plant type that is adapted to the current low sowing density, like a runner rather than a bush plant type, which currently receives most of the genetic attention. Genetic improvement targeting “drought” adaptation should also be restricted to areas where water is indeed an issue, i.e., above 12–13°N latitude in WCA and the Eastern fringes of Tanzania and Mozambique

    Accelerating Genetic Gains in Legumes for the Development of Prosperous Smallholder Agriculture: Integrating Genomics, Phenotyping, Systems Modelling and Agronomy

    Get PDF
    Grain legumes form an important component of the human diet, feed for livestock and replenish soil fertility through biological nitrogen fixation. Globally, the demand for food legumes is increasing as they complement cereals in protein requirements and possess a high percentage of digestible protein. Climate change has enhanced the frequency and intensity of drought stress that is posing serious production constraints, especially in rainfed regions where most legumes are produced. Genetic improvement of legumes, like other crops, is mostly based on pedigree and performance-based selection over the last half century. For achieving faster genetic gains in legumes in rainfed conditions, this review article proposes the integration of modern genomics approaches, high throughput phenomics and simulation modelling as support for crop improvement that leads to improved varieties that perform with appropriate agronomy. Selection intensity, generation interval and improved operational efficiencies in breeding are expected to further enhance the genetic gain in experiment plots. Improved seed access to farmers, combined with appropriate agronomic packages in farmers’ fields, will deliver higher genetic gains. Enhanced genetic gains including not only productivity but also nutritional and market traits will increase the profitability of farmers and the availability of affordable nutritious food especially in developing countries

    ICRISAT Archival Report 2008

    Get PDF

    ICRISAT Archival Report 2009

    Get PDF

    ICRISAT Archival report 2007: the productivity and livelihoods of success in the SAT nourished

    Get PDF

    Abstracts of Papers, 82nd Annual Meeting of the Virginia Academy of Science, 2004

    Get PDF
    Abstracts of papers presented at the 82nd Annual Meeting of the Virginia Academy of Science on May 26-28th, 2004, Virginia Commonwealth University, Richmond, Virginia

    Evaluating the sustainability of urban agriculture projects

    Get PDF
    Evaluating the sustainability of urban agriculture projects. 5. International Symposium for Farming Systems Design (AGRO2015

    An assessment of synthetic landfill leachate attenuation in soil and the spatial and temporal implications of the leachate on bacterial community diversity.

    Get PDF
    Thesis (M.Sc.)-University of KwaZulu-Natal, Pietermaritzburg, 2008.The temporal fate of selected parameters, including redox potential; pH; phenol; nitrates; sulphates; copper and zinc, of a young synthetic acetogenic phase landfill leachate was assessed by perfusing a series of sequential soil (Hutton) microcosms (arrays) at two hydraulic loading rates (HLR). We chose HLRs that were representative of areas in South Africa with typically elevated rainfall (Pietermaritzburg – HLRh) and one with relatively low rainfall (Kimberley – HLRl). Preliminary phenol, copper, and zinc adsorption investigations on gamma radiation sterilized soil and unsterilized soil revealed superior adsorption rates for each compound in the unsterilized soil. This revealed the importance of the biological component of soil in phenol, copper, and zinc attenuation in soil. The results presented in this thesis suggest that the HLR of leachate into soil arrays contributes to significant differences in the fate of the landfill leachate parameters mentioned earlier. In addition, we assessed the temporal and spatial succession of bacterial community diversity in each of the soil arrays by polymerase chain reaction (PCR) and denaturing gradient gel electrophoresis (DGGE). Prior to this, we compared two soil DNA isolation techniques, the modified method of Duarte et al. (1998) (Bead Beat) and the commercial Mo-Bio UltraClean™ Soil DNA isolation kit (Kit). The DNA isolated by the Kit method was significantly superior regarding purity and absence of DNA fragmentation. However, the Bead Beat method produced a significantly higher yield per reaction before further purification with Wizard™ Clean-Up columns produced DNA extracts of similar purity at the cost of a significant reduction in DNA yield. The Kit method was chosen for future DNA isolation and PCR-DGGE based on the quality of the PCR amplicons generated from the Kit isolated DNA. PCR-DGGE was further optimized by comparing the efficiency and sensitivity of a silver stain against ethidium bromide. Silver stain generated DGGE gels with greater number of bands (species richness – S) and stronger band signal intensities. Captured DGGE fingerprints generated data that were subjected to the Shannon-Weaver Index (H’) and the associated Shannon-Weaver Evenness Index (EH) to measure the change in spatial and temporal bacterial diversity. There was a significant shift in S and H’ for both HLRs but a significant change in EH was only observed for HLRh. Furthermore, a temporal comparison of S and H’ between both HLRs revealed significant differences throughout the investigation. Canonical Correspondence Analysis (CCA) revealed spatial distribution of bacterial community diversity with depth. Effects of phenol concentration, redox potential, and pH of the effluent leachate on bacterial community diversity was tentatively assessed by three-dimensional graphical representation on PlotIT 3.2 software. Bacterial community diversity showed a decrease with elevated pH and phenol concentration along with decreasing redox potentials for both HLRs. While this study reveals the spatial and temporal dynamics of bacterial community diversity in situ, it provides important evidence with respect to: (i) the effects of rainfall / leaching rates (HLR) on spatial and temporal bacterial community succession; (ii) the importance of the biological component in natural attenuation; (iii) the ability of soil, previously unexposed to landfill leachate, to initiate natural attenuation of phenol and other leachate constituents; (iv) the capacity of PCRDGGE to fingerprint successional changes in bacterial community diversity, (v) and the potential to clone and sequence selected members of bacterial associations for future reference in environmental remediation strategies
    corecore