Effect of Vibration on Rapeseed Header Loss and Optimization of Header Frame

HighlightsThe relationship of vibration and header loss was studied by multi-point vibration measurement and loss collection test.There was an approximately linear positive correlation between total header vibration and total rapeseed header loss.The header frame was analyzed and optimized through modal simulation and testing.The total rapeseed header loss of the improved header was reduced by 33.2% to 46.9%.Abstract. In view of the current large rapeseed header losses of rape combine harvesters, the effects of the header on rapeseed header loss were studied from the perspective of vibration. First, the vibrations at various measuring points on the header during rape harvest were studied using a data acquisition and analysis system while performing collection tests of rapeseed header loss with the sample slot method. The relationships between total header vibration and total rapeseed header loss and between vertical cutter vibration and rapeseed vertical cutter loss were shown to have a positive correlation, and they all increased with the increase in engine speed. Vertical cutter loss accounted for 31.2% to 42.4% of the total rapeseed header loss. Modal analysis and optimization of the header frame were then performed by simulation and test. The natural frequencies of the first-order and second-order modes of the optimized header were increased, and the possibility of resonance with other working parts was eliminated. Finally, the improved header was tested during rape harvest. The results showed that the total vibration of the improved header was reduced by 19.9% to 43.9%, and the total rapeseed header loss was reduced by 33.2% to 46.9%. The vertical cutter vibration was reduced by 30.5% to 49.8%, and the rapeseed vertical cutter loss was reduced by 20.8% to 34.7%. In addition, the vibration and rapeseed loss of the improved header had relatively slow rates of increase with the increase in engine speed. The method of reducing rapeseed loss by reducing the header vibration achieved an obvious and positive effect. Keywords: Frame optimization, Modal analysis, Rape combine harvester, Rapeseed header loss, Vibration.

Microwave Nondestructive Sensing of Moisture Content and Water Activity of Almonds

HighlightsMoisture and water activity were determined nondestructively and in real time from measurement of dielectric properties.Moisture and water activity calibration equations were established in terms of the dielectric properties.Situations in which bulk density was known or unknown were considered.SEC ranged from 0.41% to 0.68% for moisture and from 0.02 to 0.04 for water activity.Abstract. A method for rapid and nondestructive determination of moisture content and water activity of granular and particulate materials was developed. The method relies on measurement of the dielectric constant and dielectric loss factor at a single microwave frequency. For the purpose of illustration, the method was applied to predicting the moisture content and water activity of almond kernels. A free-space transmission technique was used for accurate measurement of the dielectric properties. Samples of Bute Padre almond kernels with moisture content ranging from 4.8% to 16.5%, wet basis (w.b.), and water activity ranging from 0.50 to 0.93 were loaded into a Styrofoam sample holder and placed between two horn-lens antennas connected to a vector network analyzer. The dielectric properties were calculated from measurement of the attenuation and phase shift at 8 GHz and 25°C. The dielectric properties increased linearly with moisture content, while they showed an exponential increase with water activity. Situations in which the bulk density was known and unknown were considered. Linear and exponential growth regressions provided equations correlating the dielectric properties with moisture content and water activity with coefficients of determination (r2) higher than 0.96. Analytical expressions of moisture content and water activity in terms of the dielectric properties measured at 8 GHz and 25°C are provided. The standard error of calibration (SEC) was calculated for each calibration equation. Results show that moisture content can be predicted with SECs ranging from 0.41% to 0.68% (w.b.) and water activity with SECs ranging from 0.02 to 0.04 for almond kernel samples with water activity ranging from 0.5 to 0.9 and moisture contents ranging from 4.8% to 16.5% (w.b.). Keywords: Bulk density, Dielectric constant, Dielectric loss factor, Free-space measurements, Loss tangent, Microwave frequencies, Moisture content, Water activity.

Experiment and Optimization of High-Efficiency Mechanical Separation of Peanut Seedlings and Residual Film Based on Suspension Velocity

HighlightsAn efficient method for separating peanut seedlings and residual film harvested from film-mulched peanut was proposed, and the mechanism was optimized.The relationships between the suspension velocity and moisture content of different shredded materials were studied.Four-factor, three-level Box-Behnken experiments were carried out and analyzed, and the optimal parameter combination was determined.A validation test was carried out to verify the rationality and accuracy of the optimized regression model.Abstract. To address the problems of lower residual film removal and higher material loss in the forage utilization of peanut seedlings wrapped in residual film, this study explored the relationships between the suspension velocity and moisture content of different shredded materials derived from peanut seedlings and conducted performance tests and parameter optimization for a machine that uses peanut seedlings as forage material. Four-factor, three-level Box-Behnken experiments were designed using the rotational speeds of the shredding shaft, upper fans, and lower fans and the frequency of the vibrating sieve as test factors, and using the residual film removal rate and material loss rate as response values. The test results indicated that the suspension velocity of the shredded materials showed a quadratic relationship with moisture content. The performance tests showed that the significance sequence of the test factors for the residual film removal rate was: rotational speed of the lower fans, rotational speed of the upper fans, rotational speed of the shredding shaft, and frequency of the vibrating sieve. The significance sequence for the material loss rate was: rotational speed of the lower fans, rotational speed of the shredding shaft, frequency of the vibrating sieve, and rotational speed of the upper fans. The parameter optimization and validation test showed that the residual film removal rate was 92.71% and the material loss rate was 8.19% when the rotational speeds of the shredding shaft, upper fans, and lower fans were 1650, 770, and 665 rpm, respectively, and the frequency of the vibrating sieve was 4 Hz. The relative errors between the validation test results and the predicted values from the regression models were less than 3%, which suggests that the regression models are reliable. This study provides a reference for the forage utilization of peanut seedlings harvested from film-mulched peanut and provides a reference for determining the optimal working parameters of forage processing machines. Keywords: Agricultural machinery, Box-Behnken experiment, Optimization, Peanut film-seedling separation, Suspension velocity.

Development and Evaluation of a Variable-Rate Irrigation Management Method in the Mississippi Delta

HighlightsWe developed and evaluated a variable-rate irrigation (VRI) management method for five crop years in the Mississippi Delta.VRI management significantly reduced irrigation water use in comparison with uniform-rate irrigation (URI). There was no significant difference in grain yield and irrigation water productivity between VRI and URI management.Soil apparent electrical conductivity (ECa) was used to delineate irrigation management zones and generate VRI prescriptions.Sensor-measured soil water content was used in irrigation scheduling.Abstract. Variable-rate irrigation (VRI) allows producers to site-specifically apply irrigation water at variable rates within a field to account for the temporal and spatial variability in soil and plant characteristics. Developing practical VRI methods and documenting the benefits of VRI application are critical to accelerate the adoption of VRI technologies. Using apparent soil electrical conductivity (ECa) and soil moisture sensors, a VRI method was developed and evaluated with corn and soybean for five crop years in the Mississippi Delta. Soil ECa of the study fields was mapped and used to delineate VRI management zones and create VRI prescriptions. Irrigation was scheduled using soil volumetric water content measured by soil moisture sensors. A center pivot VRI system was employed to deliver irrigation water according to the VRI prescription. Grain yield, irrigation water use, and irrigation water productivity in the VRI treatment were determined and compared with that in a uniform-rate irrigation (URI) treatment. Results showed that the grain yield and irrigation water productivity between the VRI and URI treatments were not statistically different with both corn and soybean crops. The VRI management significantly reduced the amount of irrigation water by 22% in corn and by 11% in soybean (p = 0.05). Adoption of VRI management could improve irrigation water use efficiency in the Mississippi Delta. Keywords: Soil electrical conductivity, Soil moisture sensor, Variable rate irrigation, Water management.

Inverse AERMOD and SCIPUFF Dispersion Modeling for Farm-Level PM10 Emission Rate Assessment

HighlightsAERMOD and SCIPUFF were employed to back-calculate farm-level PM10 emission rates based on inverse modeling.Both AERMOD and SCIPUFF did not capture the diurnal and seasonal variations of farm-level PM10 emission rates.AERMOD modeling results were affected by wind speed, with higher wind speed leading to higher emission rates.Higher numbers of receptors and PM10 measurements with greater time resolution may be recommended in the future.Abstract. Air pollutant emissions from animal feeding operations (AFOs) have become a serious concern for public health and ambient air quality. Particulate matter with aerodynamic equivalent diameter less than or equal to 10 µm (PM10) is one of the major air pollutants emitted from AFOs. To assess the impacts of PM10 emissions from AFOs, knowledge about farm-level PM10 emission rates is needed but is challenging to obtain through field measurements. The inverse dispersion modeling approach provides an alternative way to estimate farm-level PM10 emission rates. In this study, two dispersion models, AERMOD and SCIPUFF, were employed to back-calculate farm-level PM10 emission rates based on hourly PM10 concentration measurements at four downwind locations in the vicinity of a commercial egg production farm in the southeast U.S. Onsite meteorological data were simultaneously recorded using a 10 m weather tower to facilitate the dispersion modeling. The modeling results were compared with PM10 emission measurements from two layer houses on the farm. Single-area source, double-area source, and double-volume source were used in AERMOD, while only single-point source was used in SCIPUFF. The inverse modeling results indicated that both SCIPUFF and AERMOD did not capture the diurnal and seasonal variations of the farm-level PM10 emission rates. In addition, the AERMOD modeling results were affected by wind speed, and higher emission rates may be predicted at higher wind speeds. The single-point source for SCIPUFF, the plume rise simplification for AERMOD, and insufficient concentration measurement resolution in response to temporal changes in wind direction may have added uncertainties to the modeling results. The results of this study suggest that more receptors covering more representative downwind locations should be considered in future modeling for farm-level emissions assessment. Moreover, ambient data collection with greater time resolution (e.g., less than one hour) is recommended to capture diurnal and seasonal patterns more rigorously. Only in this way can researchers achieve a better understanding of the effectiveness of inverse dispersion modeling for estimation of pollutant emission rates. Keywords: AERMOD, Animal feeding operations, Egg production, Farm-level emission rate, Inverse dispersion modeling, PM10, SCIPUFF.

Evaluation of Horizontal Patternators According to International Standard Requirements for Boom Sprayers

HighlightsHorizontal distribution according ISO Standard 16119 is a measurement procedure to evaluate boom sprayers.ISO Standards 5682-1 and 5682-2 establish technical requirements for horizontal patternators.In this study, three types of patternators were evaluated to test their capability to meet the standards.The evaluated patternators showed similar results for spray distribution patterns.Minor deviations from ISO Standard 5682 did not imply differences according ISO Standard 16119.Abstract. Uniformity of spray volume distribution is one of the officially established measurements for the evaluation of horizontal boom sprayers according to ISO Standard 16119 and requirements established by ISO Standard 16122. Measurement of spray distribution patterns requires the use of specific devices such as horizontal patternators, which are included in the technical specifications for ISO Standards 5682-1 and 5682-2. Three such devices were tested, including two manual patternators (fixed and mobile) and one electronic patternator. According to information provided by the manufacturers, all three patternators align with ISO requirements. This study evaluated and compared the results obtained with the three patternators. Specifically, the horizontal distributions measured by the patternators were evaluated and compared using four nozzle types (XR 11003, AIXR 11003, TTJ60 11003, and AITTJ60 11003), three boom heights, and three operating pressures. Tests were conducted to quantify single-nozzle spray patterns, the coefficient of variation (CV) of the entire boom distribution, the liquid recovery capability of the three patternators, and the ability to simulate the entire boom spray distribution from a single-nozzle spray pattern. Results demonstrated correct functioning of all three patternators, resulting in identical conclusions considering the requirements established in the ISO standards. The CV values of the horizontal distributions were less than 10% for all cases. Moreover, the trends in values for all the evaluated factors (nozzle type, boom height, and operating pressure) were the same, independent of the patternator used. Keywords: ISO 16119, ISO 16122, ISO 5682, Liquid recovery, Nozzle spray pattern, Patternator, Spray boom, Transverse distribution, Uniformity.

Characteristics of Particulate Matter Emissions from Swine and Poultry Production Houses in the United States

HighlightsParticulate matter (PM) data were analyzed to identify PM emission characteristics among different animal types.The PM concentrations were higher in broiler chicken and swine farrowing houses and were higher in winter.The PM emissions were also higher in broiler chicken houses and swine farrowing rooms.The PM in the layer chicken house in Indiana had narrower distributions with a greater percentage of smaller particles.Abstract. Understanding the characteristics of particulate matter (PM) emissions from animal feeding operations (AFOs) is essential to address the associated health and environmental impacts and to develop control strategies to mitigate such impacts. This article reports a study of PM concentrations and emission characteristics from 26 poultry and swine production houses to investigate the similarities and differences in PM emission characteristics, e.g., concentrations, emission rates, and particle size distribution (PSD), among different animal and housing types. Concentration and emission data for PM2.5, PM10, and total suspended particulates (TSP) collected by the National Air Emission Monitoring Study (NAEMS) were used to compare the differences among different production practices and animal types. The PSDs of the PM were examined based on the PM2.5/PM10 and PM10/TSP emission rate ratios. It was discovered that the concentrations of PM varied among animal types. For poultry, the concentrations of PM were higher in broiler houses than in other poultry houses. For swine, the average concentrations of PM were higher in farrowing rooms than in swine barns. Moreover, the PM concentrations in poultry and swine houses exhibited significant seasonal trends, with higher concentrations in winter and lower concentrations in summer, which were in a reverse relationship with ventilation rates. The PM emissions also varied among animal types. For poultry, the PM emissions were significantly higher for poultry production houses in California. For swine, the PM emissions were significantly higher for farrowing rooms than other swine houses. The PSD of PM varied among animal types, with mass median diameters (MMD) in the ranges of 6.51 to 13.62 µm for poultry houses and 7.94 to 17.19 µm for swine houses. The geometric standard deviations (GSD) were in the ranges of 1.66 to 2.71 and 1.65 to 2.9 for poultry and swine PM, respectively. The PM in the layer house in Indiana had a narrower distribution (smaller GSD) with a greater percentage of smaller particles than the other poultry houses, while the PM in the broiler house in California had a broader distribution (larger GSD) than the other poultry houses. For swine, the PM in the sow barn in North Carolina had a narrower distribution (smaller GSD) than the other swine houses, while the PM in the farrowing houses in Oklahoma had a broader distribution (larger GSD) than the other swine houses. The knowledge gained from this research may provide insights for addressing the PM emissions from various animal production systems. Keywords: Concentration and emission, Particulate matter, PM2.5, PM10, Poultry, swine, PSD, TSP.

Field Reliability Estimation of Agricultural Tractors Based on Warranty Data

HighlightsA LightGBM regression model for predicting tractor usage rates was established based on warranty data and considering agricultural tractors’ usage context (region and season) and was then interpreted using SHAP.The field reliability of tractors was estimated based on the usage of failed and unfailed tractors, after unfailed tractors’ usage was imputed using the LightGBM regression model.The proposed methodology was validated by predicting warranty claims using estimated reliability parameters.The proposed methodology was demonstrated using warranty data from a tractor manufacturing company in China.Abstract. Warranty data provide a valuable source of information for assessing the reliability of products in operation (called the field reliability). However, warranty data consist of failure information only. The unavailability of usage data for unfailed products makes it difficult to estimate the reliability of durable products such as agricultural tractors, for which usage is a greater concern than age for reliability analysis. Several studies have proposed methods to address this problem, but they did not include information on the usage context. This study proposes a methodology to estimate the field reliability of agricultural tractors from warranty data considering the tractors’ usage context. First, by taking features representing tractors’ usage context as the input, a usage rate regression model was established using a light gradient boosting machine (LightGBM). The usage of unfailed tractors was then generated. Finally, parametric estimates of the tractors’ reliability were determined based on the usage of failed and unfailed tractors. By interpreting the LightGBM model using SHapley Additive exPlanations (SHAP), it was found that tractors that were used more days in October and April had higher predicted usage rates. To validate the effectiveness of the proposed methodology, the estimated reliability parameters were used to predict the warranty claims of six types of tractors. The results showed that the proposed methodology performed the best in four cases and close to the best in two other cases when compared with two other baseline methods. The proposed methodology was demonstrated using warranty data from an agricultural tractor manufacturing company in China and can be applied to improve understanding of tractor reliability. Keywords: Field reliability, LightGBM, SHAP, Usage context, Warranty data.

Experimental Study on Critical Shear Stress of Cohesive Soils and Soil Mixtures

HighlightsErosion tests were performed to study the critical shear stress of cohesive soils and soil mixtures.Linear relationships were observed between critical shear stress and cohesion of cohesive soils.Mixture critical shear stress relates to noncohesive particle size and cohesive soil erodibility.A formula for calculating the critical shear stress of soil mixtures is proposed and verified.Abstract. The incipient motion of soil is an important engineering property that impacts reservoir sedimentation, stable channel design, river bed degradation, and dam breach. Due to numerous factors influencing the erodibility parameters, the study of critical shear stress (tc) of cohesive soils and soil mixtures is still far from mature. In this study, erosion experiments were conducted to investigate the influence of soil properties on the tc of remolded cohesive soils and cohesive and noncohesive soil mixtures with mud contents varying from 0% to 100% using an erosion function apparatus (EFA). For cohesive soils, direct linear relationships were observed between tc and cohesion (c). The critical shear stress for soil mixture (tcm) erosion increased monotonically with an increase in mud content (pm). The median diameter of noncohesive soil (Ds), the void ratio (e), and the organic content of cohesive soil also influenced tcm. A formula for calculating tcm considering the effect of pm and the tc of noncohesive soil and pure mud was developed. The proposed formula was validated using experimental data from the present and previous research, and it can reproduce the variation of tcm for reconstituted soil mixtures. To use the proposed formula to predict the tcm for artificial engineering problems, experimental erosion tests should be performed. Future research should further test the proposed formula based on additional experimental data. Keywords: Cohesive and noncohesive soil mixture, Critical shear stress, Erodibility, Mud content, Soil property.

Frontier: Autonomy in Detection, Actuation, and Planning for Robotic Weeding Systems

HighlightsRecent research and development efforts center around developing smaller, portable robotic weeding systems.Deep learning methods have resulted in accurate, fast, and robust weed detection and identification.Additional key technologies under development include precision actuation and multi-vehicle planning. Keywords: Artificial intelligence, Automated systems, Automated weeding, Weed control.