Current Issue : April - June Volume : 2012 Issue Number : 2 Articles : 6 Articles
Cotton defoliation and post-harvest destruction are important cultural practices for cotton production. Cotton root\nrot is a serious and destructive disease that affects cotton yield and lint quality. This paper presents an overview and summary\nof the methodologies and results on the use of remote sensing technology for evaluating cotton defoliation and regrowth control\nmethods and for assessing cotton root rot infection based on published studies. Ground reflectance spectra and airborne\nmultispectral and hyperspectral imagery were used in these studies. Ground reflectance spectra effectively separated different\nlevels of defoliation and airborne multispectral imagery permitted both visual and quantitative differentiations among\ndefoliation treatments. Both ground reflectance and airborne imagery were able to differentiate cotton regrowth among\ndifferent herbicide treatments for cotton stalk destruction. Airborne multispectral and hyperspectral imagery accurately\nidentified root rot-infected areas within cotton fields. Results from these studies indicate that remote sensing can be a useful\ntool for evaluating the effectiveness of cotton defoliation and regrowth control strategies and for detecting and mapping root rot\ndamage in cotton fields. Compared with traditional visual observations and ground measurements, remote sensing techniques\nhave the potential for effective and accurate assessments of various cotton production operations and pest conditions....
A computer program was developed in C++ language to predict the effect of soil bulk density on draft force on\r\nbottoms, share thickness, stresses distribution and maximum deflection on standards, bending stresses distribution on side plates,\r\ndiameter of shear pins, and tensile stress on hitch bar. It was found that, as soil bulk density increased, stresses distribution\r\nand maximum deflection on standards, bending stresses distribution on side plates, diameter of shear pins, and tensile stress on\r\nhitch bar increased. The diameter of shear pin should be larger to meet wide range of soil density....
Farmers need proven and new knowledge of engineering matters to solve technical problems and manage technical\ninvestments in their agricultural business. According to the recent budget restriction, the Bavarian state aims in the future to\nbe involved in providing only those goods and services which the private sector is not willing to provide. The overall aim of\nthis paper is the identification of a model which guarantees an effective and uninterrupted knowledge transfer, despite restricted\nresources. An important aspect of knowledge transfer in Agricultural Engineering is the missing availability of advice in\nengineering for farmers in the private sector. The sources used for identifying adequate transfer models were the literature,\nexisting models of advisory systems, expert panels, and questioning of selected actors in the existing knowledge transfer system.\nThe relevant criteria for developing a model is the limited number of public consultants, the farm-related amount of investments\nin sustainable farm businesses, key competences of Bavarian farms, the demand for advisory services of the majority of farms,\nand the possibilities of a work-sharing cooperation between public and private advisory services. In this model, public\nconsultants have to act as supra-regional multipliers, as knowledge engineers, they identify and provide relevant new expert\ninformation and expert knowledge for advisers in the regions, farmers and other demanders in time. Other identified\ninstruments for efficiency increase in knowledge transfer are the shortening of knowledge transfer ways, application of new\ninformation and communication technologies, and reorganisation according to communication channels. External\ncommunication can be improved by networks between actors in knowledge transfer and timely consultant profiles, next to the\ncooperation possibilities with private advisory organisations and the building-up of demand-oriented core capabilities....
The purity of product from agricultural cleaners (such as chile, cotton, bean, wheat and other crop cleaners) is needed\nto be measured under various conditions in order to adjust and optimize the machine at the design and improvement stages.\nThe traditional weight-based method of measuring purity is time consuming, and requires much labor. In this study, we used\nimage analysis to measure percent crop cover for the product output to infer the purity. Chile cleaner was used as one example\nmachine to compare between Photoshop�© and Arcview�© software for the analysis of fresh and dry harvest pictures. The data\ncollection process is more reproducible and less labor and time consuming than the traditional technique. Both software\npackages provided accurate estimations of purity for both fresh and dry harvest pictures. Photoshop�© had better accuracy than\nArcview�© (mean error ratio of 0.016 vs. 0.081 for fresh harvest; and 0.035 vs. 0.114 for dry harvest)....
Farming operations efficiency is a crucial factor that determines the overall\noperational cost in agricultural production systems. Improved efficiency can be achieved by\nimplementing advanced planning methods for the execution of field operations dealing,\nespecially with the routing and area coverage optimisation aspects. Recently, a new type of field\narea coverage patterns, the B-patterns, has been introduced. B-patterns are the result of a\ncombinatorial optimisation process that minimizes operational criterions such as, the operational\ntime, non-working travelled distance, fuel consumption etc. In this paper an algorithmic\napproach for the generation of B-patterns based on ant colony optimisation is presented. Ant\ncolony optimization metaheuristic was chosen for the solution of the graph optimisation problem\ninherent in the generation of B-patterns. Experimental results on two selected fields were\npresented for the demonstration of the effectiveness of the proposed approach. Based on the\nresults, it was shown that it is feasible to use ant colony optimization for the generation of\noptimal routes for field area coverage while tests made on the resulting routes indicated that they\ncan be followed by any farm machine equipped with auto-steering and navigation systems....
This research was conducted over one Iranian variety of Oak (Quercus Persica)\nwith 70 observations. Physical and mechanical properties of oak are necessary for equipment\nused in activities such as transportation, storage, grading, packing etc. Properties which were\nmeasured include fruit dimensions, mass, volume, projected area, fruit density, geometric\nmean diameter, sphericity and surface area. Bulk density, porosity and also packing\ncoefficient were measured. Experiments were carried out at moisture content of 51.8% (w.b.).\nResults showed that average mass and volume were 12.95 g and 10.27 mL, respectively.\nDimensions increased from 41.85 to 61.09 mm in length, 14.45 to 25.02 mm in width and\n14.42 to 24.38 mm in thickness. The mean projected area perpendicular to length, width and\nthickness obtained 433.91, 1085.48 and 1115.46 mm2, respectively. The geometric mean\ndiameter and surface area were calculated as 27.638 mm and 2423.82 mm2, respectively,\nwhile sphericity was measured 51.78%. Elasticity modulus (E), maximum force which fruit\ncan support (Fmax) and work which performed to this force have been determined....
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