2 resultados para Average of min and max value

em Universitätsbibliothek Kassel, Universität Kassel, Germany


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Increasing food production to feed its rapidly growing population is a major policy goal of Pakistan. The production of traditional staples such as rice (Oryza sativa L.) and bread wheat (Triticum aestivum L.) has been intensified in many regions, but not in remote, drought-ridden areas. In these arid, marginal environments dates and their by-products are an option to complement staples given their high nutritive value and storability. To fill knowledge gaps about the role of date palm in the household (HH) income of rural communities and the structure of date value chains, this project studied date palm production across six districts in four provinces of Pakistan. During 2012–2013 a total of 170 HHs were interviewed with a structured questionnaire using a snowball sampling approach. The results showed that most of the HH were headed by males (99 %) who were married (74 %) and often illiterate (40 %). Agriculture was the main occupation of date palm growers (56 %), while a few coupled agricultural activities with business (17 %) or extra-farm employment opportunities (government 9 %; private sector 8 %). Date sales contributed >50 % to the total income of 39 % of HH and 90–100 % to 24 % of HH. Overall farmers grew a total of 39 date palm cultivars and cultivated an average of 409 ± 559 mature date palms. The majority of the respondents sold dates to commission agents (35 %), contractors (22 %) and wholesalers (21 %), while 28 % of HH cultivated date palms only for self-consumption. Date palm growers had only limited knowledge about high quality date cultivars, optimized farm management and about effective post-harvest conservation. Changes in extension and marketing efforts are needed to allow farmers to better exploit value chains in date thereby reaping higher benefits from improved market access to secure their often marginal income.

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Summary: Productivity, botanical composition and forage quality of legume-grass swards are important factors for successful arable farming in both organic and conventional farming systems. As these attributes can vary considerably within a field, a non-destructive method of detection while doing other tasks would facilitate a more targeted management of crops, forage and nutrients in the soil-plant-animal system. This study was undertaken to explore the potential of field spectral measurements for a non destructive prediction of dry matter (DM) yield, legume proportion in the sward, metabolizable energy (ME), ash content, crude protein (CP) and acid detergent fiber (ADF) of legume-grass mixtures. Two experiments were conducted in a greenhouse under controlled conditions which allowed collecting spectral measurements which were free from interferences such as wind, passing clouds and changing angles of solar irradiation. In a second step this initial investigation was evaluated in the field by a two year experiment with the same legume-grass swards. Several techniques for analysis of the hyperspectral data set were examined in this study: four vegetation indices (VIs): simple ratio (SR), normalized difference vegetation index (NDVI), enhanced vegetation index (EVI) and red edge position (REP), two-waveband reflectance ratios, modified partial least squares (MPLS) regression and stepwise multiple linear regression (SMLR). The results showed the potential of field spectroscopy and proved its usefulness for the prediction of DM yield, ash content and CP across a wide range of legume proportion and growth stage. In all investigations prediction accuracy of DM yield, ash content and CP could be improved by legume-specific calibrations which included mixtures and pure swards of perennial ryegrass and of the respective legume species. The comparison between the greenhouse and the field experiments showed that the interaction between spectral reflectance and weather conditions as well as incidence angle of light interfered with an accurate determination of DM yield. Further research is hence needed to improve the validity of spectral measurements in the field. Furthermore, the developed models should be tested on varying sites and vegetation periods to enhance the robustness and portability of the models to other environmental conditions.