EFFECTS OF DRYING AIR TEMPERATURE AND GRAIN INITIAL MOISTURE CONTENT ON SOYBEAN QUALITY (GLYCINE MAX (L.) MERRILL)

ABSTRACT: This study aimed to evaluate the effect of air-drying temperature and initial moisture content on volume shrinkage, physical quality and oil extraction yield of soybean grains. The grains used in this experiment were harvested at two distinct moisture levels of 19 and 25%. Then, these grains were taken to dryness at three different air temperatures of 75 °C, 90 °C and 105 °C, in a forced circulation convection oven of the air. The results showed a drying time reduction with increasing air temperatures. Regarding volume shrinkage, moisture content reductions influenced grain volume and the Rahman's model was the one that best fit the data. Moreover, the higher the air temperature, the greater the effects on soybean grain shrinkage and physical quality. By grain volume reduction effected on oil yield, major impacts were observed when assessing grain initial moisture content were higher. Furthermore, the temperature of 105°C and an initial moisture content of 25% were the factors that most affected soybean grain quality, however not affecting oil extraction yield

MACHINE LEARNING MODELS FOR PREDICTING MECHANICAL DAMAGE, VIGOR AND VIABILITY OF SOYBEAN SEEDS DURING STORAGE

ABSTRACT Artificial Intelligence has been widely applied in data prediction for better decision making and process optimization. In the post-harvest, the control of biotic and abiotic factors is fundamental for the conservation of seed quality. Meanwhile, the tetrazolium test has been used to evaluate seed quality, however, with several limitations that can lead to evaluation errors. Thus, machine learning models can be an alternative to predict the quality of soybean seeds, with gains in the speed of obtaining results in relation to laboratory analysis methods, making the processes more robust and with low operational cost. With this, the aim of this study was to identify the best machine learning model for predicting mechanical damage, vigor and viability of soybean seeds during storage, depending on different conditions (10, 15 and 25 ºC), packaging (with coating and uncoated) and storage times (0, 3, 6, 9 and 12 months). M5P decision tree (M5P) and Random Forest (RF) models showed the best performance for predicting seed vigor (r = 0.75 and MAE = 10.0), and viability (r = 0.85 and MAE = 5.1), and mechanical damage to seeds (r = 0.64 and MAE = 11.2). It was concluded that the Random Forest (RF) model was the one that best predicted the results of soybean seed quality, with a more simplified and agile analysis for the development of vigor and viability of soybean seeds in storage

Experimental silo-dryer-aerator for the storage of soybean grains

ABSTRACT This study aimed to verify the capacity of silo-dryer-aerator prototype equipment operating as a silo-storage-aerator for soybean quality analysis. Soybeans with water content of 17% (wet basis – w.b.) were dried and stored in a silo-dryer-aerator system that was designed using a drying chamber, four independent storage cells, and a static capacity of 164 kg. Another batch of grains was stored in a silo-storage-aerator with a capacity of 1,200 kg. The experiment was set up in a completely randomized factorial 5 × 4 experimental design including five grain batches stored after being dried at 30, 40, and 50 °C (mixed grains were dried at three temperatures) in the silo-dryer-aerator cells and one mixed grain batch stored in the silo-storage-aerator system under ambient air conditions for four storage times (zero, one, two, and three months). There was no difference between the grains stored in the silo-dryer-aerator and silo-storage-aerator at the end of the three-month storage in terms of the physico-chemical quality. The storage time associated with drying at 50 °C caused a reduction in the physical-chemical quality of the grains. The silo-dryer-aerator system was presented as a possible alternative to store soybean (Glycine max L.) grains

Experimental silo-dryer-aerator for the storage of soybean grains

<div><p>ABSTRACT This study aimed to verify the capacity of silo-dryer-aerator prototype equipment operating as a silo-storage-aerator for soybean quality analysis. Soybeans with water content of 17% (wet basis – w.b.) were dried and stored in a silo-dryer-aerator system that was designed using a drying chamber, four independent storage cells, and a static capacity of 164 kg. Another batch of grains was stored in a silo-storage-aerator with a capacity of 1,200 kg. The experiment was set up in a completely randomized factorial 5 × 4 experimental design including five grain batches stored after being dried at 30, 40, and 50 °C (mixed grains were dried at three temperatures) in the silo-dryer-aerator cells and one mixed grain batch stored in the silo-storage-aerator system under ambient air conditions for four storage times (zero, one, two, and three months). There was no difference between the grains stored in the silo-dryer-aerator and silo-storage-aerator at the end of the three-month storage in terms of the physico-chemical quality. The storage time associated with drying at 50 °C caused a reduction in the physical-chemical quality of the grains. The silo-dryer-aerator system was presented as a possible alternative to store soybean (Glycine max L.) grains.</p></div

Quality of raw materials from different regions of Minas Gerais State utilized in ration industry

The present work aimed at evaluating the quality of raw materials destined for animal feed production, as well as the quality of corn produced in different areas of the Minas Gerais State. The study was conducted in a feed mill for poultry, with production capacity of 1,000 t d-1. Samples of corn, soybean, flours, animal meals, and feed, during the year of 2008 were collected for analysis of moisture, acidity, peroxides, crude protein, ethereal extract, and physical classification of the corn for "type". The collection of samples, physical-chemical analysis and classification of corn according to "type" were performed at the Industrial Laboratory and at the Department of Agricultural Engineering of Federal University of Viçosa. It was concluded that: raw materials meet the minimum demands of quality (with regards to physical-chemical and nutritional aspects); the corn grains and some by-products present high indexes of moisture and are subject to microbiological contamination during storage; the corn produced in the different areas of Minas Gerais State can be classified as "type 1" for commercialization

Adjustment of mathematical models and quality of soybean grains in the drying with high temperatures

ABSTRACT The aim of this study was to evaluate the influence of the initial moisture content of soybeans and the drying air temperatures on drying kinetics and grain quality, and find the best mathematical model that fit the experimental data of drying, effective diffusivity and isosteric heat of desorption. The experimental design was completely randomized (CRD), with a factorial scheme (4 x 2), four drying temperatures (75, 90, 105 and 120 ºC) and two initial moisture contents (25 and 19% d.b.), with three replicates. The initial moisture content of the product interferes with the drying time. The model of Wang and Singh proved to be more suitable to describe the drying of soybeans to temperature ranges of the drying air of 75, 90, 105 and 120 °C and initial moisture contents of 19 and 25% (d.b.). The effective diffusivity obtained from the drying of soybeans was higher (2.5 x 10-11 m2 s-1) for a temperature of 120 °C and water content of 25% (d.b.). Drying of soybeans at higher temperatures (above 105 °C) and higher initial water content (25% d.b.) also increases the amount of energy (3894.57 kJ kg-1), i.e., the isosteric heat of desorption necessary to perform the process. Drying air temperature and different initial moisture contents affected the quality of soybean along the drying time (electrical conductivity of 540.35 µS cm-1g-1); however, not affect the final yield of the oil extracted from soybean grains (15.69%)