Assessment of methods of acquiring analyzing, and reporting crop production statistics, volume 4

There are no author-identified significant results in this report

Agricultural Structures and Mechanization

In our globalized world, the need to produce quality and safe food has increased exponentially in recent decades to meet the growing demands of the world population. This expectation is being met by acting at multiple levels, but mainly through the introduction of new technologies in the agricultural and agri-food sectors. In this context, agricultural, livestock, agro-industrial buildings, and agrarian infrastructure are being built on the basis of a sophisticated design that integrates environmental, landscape, and occupational safety, new construction materials, new facilities, and mechanization with state-of-the-art automatic systems, using calculation models and computer programs. It is necessary to promote research and dissemination of results in the field of mechanization and agricultural structures, specifically with regard to farm building and rural landscape, land and water use and environment, power and machinery, information systems and precision farming, processing and post-harvest technology and logistics, energy and non-food production technology, systems engineering and management, and fruit and vegetable cultivation systems. This Special Issue focuses on the role that mechanization and agricultural structures play in the production of high-quality food and continuously over time. For this reason, it publishes highly interdisciplinary quality studies from disparate research fields including agriculture, engineering design, calculation and modeling, landscaping, environmentalism, and even ergonomics and occupational risk prevention

Data documentation for the 1981 summer vegetation experiment

The mobile agricultural radar sensor was used to collect data from 31 fields in the floodplain of the Kansas River east of Lawrence, Kansas during the summer of 1981. Corn, soybeans, and wheat crops were observed from May 1 to November 11. Radar backscattering measurements were acquired at 10.2 GHz for VV and VH polarizations at 50 deg incidence angles for all fields and at 30 deg, 40 deg, 50 deg, 60 deg, and 70 deg for nine of the 31 fields. Target parameters describing the vegatation and soil characteristics, such as plant moisture, plant height, soil moisture, etc., were also measured. The methodology, radar backscatter data and associated ground-truth data obtained during this experiment are documented

Development of Drums for an Axial Flow Maize Shelling Unit

Shelling drums have an important effect on the performance of machinery used in maize harvesting. This study was aimed to develop axial flow drums for a maize shelling unit. They were 900 mm long and 300 mm in diameter. Comparative maize shelling experiments were carried out with peg-toothed (A), peg-rasp bar-toothed (B), peg-rectangular-toothed (C), and disc peg (D) drums with four levels of concave clearance (CC), 15, 20, 25, and 30 mm and three rotor speeds (RS), 6, 10, and 14 m/s. The results showed that the CC had a significant effect on the shelling efficiency (SE) and total losses (TL), while grain breakage (GB) was not significant.  Furthermore, no interaction was found between the power requirements (P) and the specific energy consumption (SEC), the SE, and the GB.  However, interaction between TL, P, and SEC was found with various drum types and the CC. The RS was found to have a significant effect on the SE, TL, GB, P, and SEC with different drum types. Moreover, the interaction between the drum types and the RS affected shelling at the α=0.05 level. Furthermore, it was found that the Type D drum had higher performance in shelling maize

Optimization of Millet Axial Flow Threshing and Separation Device Based on Discrete Element Method

The difficulties of threshing and separation of millet have not been solved yet which has restricted the development of the millet industry because of the special biological structure and lack of professional agricultural machinery. In order to improve the quality of millet harvest and meet the market demand for millet, in this paper, according to the branching structure of millet, the millet earhead model was established by Discrete Element Method. Using virtual models of millet and device, the simulation tests were carried out whose results have shown that the threshing effect of the rasp-bar threshing element is better than that of the teeth threshing element. Then the rotor structure was optimized into a combined type of the rasp-bar and the teeth. A three-factor five-level quadratic orthogonal rotation combination test was carried out whose results have shown that the combined rotor can meet the requirements of millet harvest

Design and Evaluation of a Small Axial Flow Sunflower Thresher Unit

The design of a small axial flow sunflower thresher for tractor installation needs to be developed and evaluated to obtain performance data suitable for sunflower seed production in Thailand. Therefore, the purpose of this research is to design and evaluate a small axial flow sunflower thresher. The design of this unit was done according to the concept of a plant thresher machine, which consists of a set of rotor drums and threshing sieves. The performance of the small axial flow sunflower thresher was evaluated in terms of sunflower moisture in the range of 8.92 to 21.72%, feed rate in the range of 800 to 1,600 kg/h, and linear rotor speed of spike-teeth in the range of 6 to 14 m/s. Evaluation of the threshing unit showed that these three factors had a statistically significant effect on sunflower threshing performance. The optimal parameters to achieve maximal performance are as follows. First, the sunflower moisture content should be in the range of 12 to 14% on a wet basis.  Second, the feed rate should be in the range of 1,000 to 1,200 kg/h. Last, the linear velocity of the threshing rotor should range from 10 to 12 m/s. This will achieve greater than 98% threshing efficiency with threshing losses and grain breakage of less than 2%. Future research should investigate additional factors influencing the separation and cleaning of axial flow sunflower thresher machines

Seed production in corn and soybean

Seed production is one of the least visible yet most important aspects of food and feed production. This part of the system is often taken for granted, even by the farmers who plant the seed. One of the reasons is that much of the seed in the United States is provided by the private sector, particularly for corn and soybean. Also, seed production is a technical process that requires in-depth knowledge of the reproductive mechanisms in plants

ENHANCED GRAIN CROP YIELD MONITOR ACCURACY THROUGH SENSOR FUSION AND POST-PROCESSING ALGORITHMS

Yield monitors have become an indispensable part of precision agriculture systemsbecause of their ability to measure the yield variability. Accurate yield monitor data availabilityis essential for the assessment of farm practices. The current technology of measuring grainyields is prone to errors that can be attributed to mass flow variations caused by the mechanismswithin a grain combine. Because of throughput variations, there are doubts regarding thecorrelation between the mass flow measurement and the actual grain volume produced at aspecific location. Another inaccuracy observed in yield monitor data can be attributed to inexactcut-widths values entered by the machine operator.To effectively address these yield monitor errors, two crop mass flow sensing deviceswere developed and used to correct yield monitor data. The two quantities associated with cropmaterial mass flow that were sensed were tension on the feeder housing drive chain and thehydraulic pressure on the threshing cylinder\u27s variable speed drive. Both sensing approacheswere capable of detecting zero mass flow conditions better than the traditional grain mass flowsensor. The alternative sensors also operate without being adversely affected by materialtransport delays. The feeder housing-based sensor was more sensitive to variations in cropmaterial throughput than the hydraulic pressure sensor. Crop mass flow is not a surrogate forgrain mass flow because of a weak relationship (R2 andlt; 0.60) between the two quantities. The cropmass flow signal does denote the location and magnitude of material throughput variations intothe combine. This delineation was used to redistribute grain mass flow by aligning grain andcrop mass flow transitions using sensor fusion techniques. Significant improvements (?? = 0.05)in yield distribution profile were found after the correction was applied.To address the cut-width entry error, a GIS-based post-processing algorithm wasdeveloped to calculate the true harvest area for each yield monitor data point. Based on theresults of this method, a combine operator can introduce yield calculation errors of 15%. Whenthese two correction methods applied to yield monitor data, the result is yield maps withdramatically improved yield estimates and enhanced spatial accuracy