973 resultados para cash crop
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Literature on agency problems arising between controlling and minority owners claim that separation of cash flow and control rights allows controllers to expropriate listed firms, and further that separation emerges when dual class shares or pyramiding corporate structures exist. Dual class share and pyramiding coexisted in listed companies of China until discriminated share reform was implemented in 2005. This paper presents a model of controller to expropriate behavior as well as empirical tests of expropriation via particular accounting items and pyramiding generated expropriation. Results show that expropriation is apparent for state controlled listed companies. While reforms have weakened the power to expropriate, separation remains and still generates expropriation. Size of expropriation is estimated to be 7 to 8 per cent of total asset at mean. If the "one share, one vote" principle were to be realized, asset inflation could be reduced by 13 percent.
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This study examines the significance of food crop diversification as a household risk mitigating strategy to achieve "self-sufficiency" to ensure food security during the civil conflict in Cote d’Ivoire. The main motivation for seeking self-sufficiency stems from the fact that during the period of heightened tension due to conflict, the north–south divide set by the UN peacekeeping line disrupted the agricultural supply chain from the food surplus zone, Savane in the north. While we theoretically predict a positive effect on crop diversification because of interrupted food supply chain, we also consider a negative effect due to the covariate shocks. We find robust and statistically significant empirical outcomes supporting such claims. The baseline outcomes withstand a series of robustness checks. The net effect of conflict on crop diversification is positive but not statistically significant. In addition, we find that increasing vulnerability to poverty and food insecurity during conflict seems to be the underlying factors that motivate farm households to adopt such coping strategies.
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Inoculum sources and Preservation in Soils of Phytophthora parasitica from Cherry Tomato in Continental Crop Areas in Southeast Spain
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In order to establish a rational nitrogen (N) fertilisation and reduce groundwater contamination, a clearer understanding of the N distribution through the growing season and its dynamics inside the plant is crucial. In two successive years, a melon crop (Cucumis melo L. cv. Sancho) was grown under field conditions to determine the uptake of N fertiliser, applied by means of fertigation at different stages of plant growth, and to follow the translocation of N in the plant using 15N-labelled N. In 2006, two experiments were carried out. In the first experiment, labelled 15N fertiliser was supplied at the female-bloom stage and in the second, at the end of fruit ripening. Labelled 15N fertiliser was made from 15NH415NO3 (10 at.% 15N) and 9.6 kg N ha−1 were applied in each experiment over 6 days (1.6 kg N ha−1 d−1). In 2007, the 15N treatment consisted of applying 20.4 kg N ha−1 as 15NH415NO3 (10 at.% 15N) in the middle of fruit growth, over 6 days (3.4 kg N ha−1 d−1). In addition, 93 and 95 kg N ha−1 were supplied daily by fertigation as ammonium nitrate in 2006 and 2007, respectively. The results obtained in 2006 suggest that the uptake of N derived from labelled fertiliser by the above-ground parts of the plants was not affected by the time of fertiliser application. At the female-flowering and fruit-ripening stages, the N content derived from 15N-labelled fertiliser was close to 0.435 g m−2 (about 45% of the N applied), while in the middle of fruit growth it was 1.45 g m−2 (71% of the N applied). The N application time affected the amount of N derived from labelled fertiliser that was translocated to the fruits. When the N was supplied later, the N translocation was lower, ranging between 54% at female flowering and 32% at the end of fruit ripening. Approximately 85% of the N translocated came from the leaf when the N was applied at female flowering or in the middle of fruit growth. This value decreased to 72% when the 15N application was at the end of fruit ripening. The ammonium nitrate became available to the plant between 2 and 2.5 weeks after its application. Although the leaf N uptake varied during the crop cycle, the N absorption rate in the whole plant was linear, suggesting that the melon crop could be fertilised with constant daily N amounts until 2–3 weeks before the last harvest.
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The evapotranspiration (ETc) of sprinkler-irrigated rice was determined for the semiarid conditions of NE Spain during 2001, 2002 and 2003. The surface renewal method, after calibration against the eddy covariance method, was used to obtain values of sensible heat flux (H) from high-frequency temperature readings. Latent heat flux values were obtained by solving the energy balance equation. Finally, lysimeter measurements were used to validate the evapotranspiration values obtained with the surface renewal method. Seasonal rice evapotranspiration was about 750–800 mm. Average daily ETc for mid-season (from 90 to 130 days after sowing) was 5.1, 4.5 and 6.1 mm day−1 for 2001, 2002 and 2003, respectively. The experimental weekly crop coefficients fluctuated in the range of 0.83–1.20 for 2001, 0.81–1.03 for 2002 and 0.84–1.15 for 2003. The total growing season was about 150–160 days. In average, the crop coefficients for the initial (Kcini), mid-season (Kcmid) and late-season stages (Kcend) were 0.92, 1.06 and 1.03, respectively, the length of these stages being about 55, 45 and 25 days, respectively.
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Determination of the soil coverage by crop residues after ploughing is a fundamental element of Conservation Agriculture. This paper presents the application of genetic algorithms employed during the fine tuning of the segmentation process of a digital image with the aim of automatically quantifying the residue coverage. In other words, the objective is to achieve a segmentation that would permit the discrimination of the texture of the residue so that the output of the segmentation process is a binary image in which residue zones are isolated from the rest. The RGB images used come from a sample of images in which sections of terrain were photographed with a conventional camera positioned in zenith orientation atop a tripod. The images were taken outdoors under uncontrolled lighting conditions. Up to 92% similarity was achieved between the images obtained by the segmentation process proposed in this paper and the templates made by an elaborate manual tracing process. In addition to the proposed segmentation procedure and the fine tuning procedure that was developed, a global quantification of the soil coverage by residues for the sampled area was achieved that differed by only 0.85% from the quantification obtained using template images. Moreover, the proposed method does not depend on the type of residue present in the image. The study was conducted at the experimental farm “El Encín” in Alcalá de Henares (Madrid, Spain).
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This paper presents a computer vision system that successfully discriminates between weed patches and crop rows under uncontrolled lighting in real-time. The system consists of two independent subsystems, a fast image processing delivering results in real-time (Fast Image Processing, FIP), and a slower and more accurate processing (Robust Crop Row Detection, RCRD) that is used to correct the first subsystem's mistakes. This combination produces a system that achieves very good results under a wide variety of conditions. Tested on several maize videos taken of different fields and during different years, the system successfully detects an average of 95% of weeds and 80% of crops under different illumination, soil humidity and weed/crop growth conditions. Moreover, the system has been shown to produce acceptable results even under very difficult conditions, such as in the presence of dramatic sowing errors or abrupt camera movements. The computer vision system has been developed for integration into a treatment system because the ideal setup for any weed sprayer system would include a tool that could provide information on the weeds and crops present at each point in real-time, while the tractor mounting the spraying bar is moving
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Agro-areas of Arroyos Menores (La Colacha) west and south of Rand south of R?o Cuarto (Prov. of Cordoba, Argentina) basins are very fertile but have high soil loses. Extreme rain events, inundations and other severe erosions forming gullies demand urgently actions in this area to avoid soil degradation and erosion supporting good levels of agro production. The authors first improved hydrologic data on La Colacha, evaluated the systems of soil uses and actions that could be recommended considering the relevant aspects of the study area and applied decision support systems (DSS) with mathematic tools for planning of defences and uses of soils in these areas. These were conducted here using multi-criteria models, in multi-criteria decision making (MCDM); first of discrete MCDM to chose among global types of use of soils, and then of continuous MCDM to evaluate and optimize combined actions, including repartition of soil use and the necessary levels of works for soil conservation and for hydraulic management to conserve against erosion these basins. Relatively global solutions for La Colacha area have been defined and were optimised by Linear Programming in Goal Programming forms that are presented as Weighted or Lexicographic Goal Programming and as Compromise Programming. The decision methods used are described, indicating algorithms used, and examples for some representative scenarios on La Colacha area are given.
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Canopy characterization is essential for describing the interaction of a crop with its environment. The goal of this work was to determine the relationship between leaf area index (LAI) and ground cover (GC) in a grass, a legume and a crucifer crop, and to assess the feasibility of using these relationships as well as LAI-2000 readings to estimate LAI. Twelve plots were sown with either barley (Hordeum vulgare L.), vetch (Vicia sativa L.), or rape (Brassica napus L.). On 10 sampling dates the LAI (both direct and LAI-2000 estimations), fraction intercepted of photosynthetically active radiation (FIPAR) and GC were measured. Linear and quadratic models fitted to the relationship between the GC and LAI for all of the crops, but they reached a plateau in the grass when the LAI mayor que 4. Before reaching full cover, the slope of the linear relationship between both variables was within the range of 0.025 to 0.030. The LAI-2000 readings were linearly correlated with the LAI but they tended to overestimation. Corrections based on the clumping effect reduced the root mean square error of the estimated LAI from the LAI-2000 readings from 1.2 to less than 0.50 for the crucifer and the legume, but were not effective for barley.
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Field studies were conducted in walk-in tunnels to determine the flying capacity in the presence and absence of crop, of the parasitoid Psyttalia concolor and the predator Chrysoperla carnea under a UV-absorbent net (Bionet®). Yellow sticky cards were used for insect recovery but neither P. concolor nor C. carnea were very attracted to them, thus captures were too low to permit any meaningful comparisons. Bionet® did not seem to affect the mobility of any natural enemy irrespective of the trap location and monitoring hour. Climatic conditions inside nets were very extreme (average temperatures very high and relative humidity very low) threatening insect survival. New experiments are being developed, trying to find new attractants that permit a significant capture of both natural enemies.
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No tillage, minimum tillage and conventional tillage practices are commonly used in maize crops in Alentejo, affecting soil physic conditions and determining seeders performance. Seeders distribution can be evaluated in the longitudinal and vertical planes. Vertical plane is specified by seeding depth (Karayel et al., 2008). If, in one hand seeding depth uniformity is a goal for all crop establishment , in the other hand, seeders furrow openers depth control is never constant depending on soil conditions. Seed depth uniformity affects crop emergence, Liu et al. (2004) showed an higher correlation between crop productivity and emergence uniformity than with longitudinal plants distribution. Neto et al. (2007) evaluating seed depth placement by measuring maize mesocotyl length under no tillage conditions in 38 farms concluded that 20% of coefficient of variation suggests the need of improvement seeders depth control mechanisms. The objective of this study was to evaluate casual relationships and create spatial variability maps between soil mechanic resistance and vertical distribution under three different soil practices to improve seed depth uniformity.
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This paper proposes a new method, oriented to crop row detection in images from maize fields with high weed pressure. The vision system is designed to be installed onboard a mobile agricultural vehicle, i.e. submitted to gyros, vibrations and undesired movements. The images are captured under image perspective, being affected by the above undesired effects. The image processing consists of three main processes: image segmentation, double thresholding, based on the Otsu’s method, and crop row detection. Image segmentation is based on the application of a vegetation index, the double thresholding achieves the separation between weeds and crops and the crop row detection applies least squares linear regression for line adjustment. Crop and weed separation becomes effective and the crop row detection can be favorably compared against the classical approach based on the Hough transform. Both gain effectiveness and accuracy thanks to the double thresholding that makes the main finding of the paper.
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This paper proposes a new method, oriented to image real-time processing, for identifying crop rows in maize fields in the images. The vision system is designed to be installed onboard a mobile agricultural vehicle, that is, submitted to gyros, vibrations, and undesired movements. The images are captured under image perspective, being affected by the above undesired effects. The image processing consists of two main processes: image segmentation and crop row detection. The first one applies a threshold to separate green plants or pixels (crops and weeds) from the rest (soil, stones, and others). It is based on a fuzzy clustering process, which allows obtaining the threshold to be applied during the normal operation process. The crop row detection applies a method based on image perspective projection that searches for maximum accumulation of segmented green pixels along straight alignments. They determine the expected crop lines in the images. The method is robust enough to work under the above-mentioned undesired effects. It is favorably compared against the well-tested Hough transformation for line detection.