AUGER CONVEYOR-DISTRIBUTER OF GRAIN

The construction of a solar dryer-grain storage facilities is described. The design of a auger conveyor-distributor of grain for its loading is offered. The dependence of the width of the discharge opening in the casing of the auger conveyor-distributor on its length is obtained. The results of laboratory tests of the auger conveyor-distributor of grain are presented. It is established that the minimum initial width of the drain opening for wheat grain should be not less than 9 mm. The conditions of uniform distribution of grain by the auger conveyor-distributor are justified: the filling factor of the auger interturn space in its loading zone – 0.35; the length of the discharge opening of the charging hopper should be equal to the doubled value of the auger pitch size. In this case, the uneven distribution of grain along the discharge opening will be no more than 5%.

The technological properties of winter wheat grain during long-term storage

In the world, the demand for quality and safe grain products is increasing. The need to preserve wheat in the event of a natural disaster requires the study of optimal storage times of grain without degrading technological indexes. The purpose of the work was to study the dynamics of technological properties of winter wheat grown after peas, clover, corn for silage and the industrial, ecological, biological growing systems during 1, 3, and 5 years of storage in the conditions of the ordinary granary. The absence of significant differences in the technological parameters of the grain of wheat grown at industrial and ecological systems, but significantly lower indicators at a biological growing system was found. The highest hectolitre weight obtained when wheat grain was grown after corn for silage, and vitreousness – after the clover. Significantly higher biochemical parameters of grain and alveographic properties of flour were for the cultivation of wheat after peas, which provided additional accumulation of protein substances. There are no significant changes in the indicator of hectolitre weight during the grain storage. Other indicators increased significantly after 1 year of storage (on average by 10 – 30%). For further storage, vitreousness growth was insignificant. After 5 years of storage, the falling number significantly increased (on 21% compared to the initial values and on 7% – after 3 years of storage). The content of protein, gluten in the grain, and alveographic properties of flour significantly decreased after 5 years of storage. The possibility of obtaining grain of wheat with high technological parameters for a more safe ecological growing system was established. It was also confirmed to need for grain storage up to 1 year to improve quality indicators and it was established that it safely stored for 3 years.

Automation of Control of Technological Process of Storage in a Granary with Horizontal Silos

Grain storage and processing is the most important component of the grain market infrastructure. The task of grain storage is to ensure complete safety of quantity and quality with minimal labor and money costs. In the laboratory of the M. Kozybayev North Kazakhstan University, a prototype of an innovative type of grain storage was developed using horizontal silos, designed to reduce the cost of construction and reconstruction of elevators while improving quality, increasing storage times and reducing current storage costs. The design feature makes it possible to automate most of the operations of the technological process of grain storage. This article proposes a method for the automated formation of control actions on grain storage equipment as a result of data analysis from temperature, humidity, carbon dioxide level sensors and 3D measurements of the grain surface. A project of an automated system for monitoring and controlling grain storage facilities with horizontal silos has been developed. A distinctive feature of the proposed automated system is the most complete set of conditions for the correct storage of grain in comparison with other control systems for the technological process of a granary. Automation of work is achieved through the developed method for generating control signals, as well as such computational algorithms as forecasting the completion time of loading based on the conditional filling rate of the grain storage section, forecasting the completion time of unloading based on the conditional grain release rate, calculating the grain volume in the section using 3D measurements. The logic of the functioning of the basic algorithms for an automated monitoring and control system for a granary with horizontal silos is based on the analysis of the parameters of temperature, humidity, carbon dioxide level and 3D measurements of the grain surface in the sections of the granary. In the presented project of an automated system, scientific knowledge and achievements in the field of grain storage and the theory of identification measurements were taken into account, which makes it possible to use the described algorithms in information systems for monitoring grain storage facilities of other types.

Nitrogen Fertilizer Regulated Grain Storage Protein Synthesis and Reduced Chalkiness of Rice Under Actual Field Warming

Our previous study has shown that nitrogen plays an important role in dealing with significantly increased chalkiness caused by elevated temperature. However, the role of nitrogen metabolites has not been given sufficient attention, and its regulatory mechanism is not clear. This study investigated the effects of high temperature and nitrogen fertilizer on the synthesis of grain storage protein and further explored the quality mechanism under the actual scenario of field warming. Results showed that increased temperature and nitrogen fertilizer could affect the activities of nitrogen metabolism enzymes, namely, glutamate synthetase, glutamine synthetase, glutamic pyruvic transaminase, and glutamic oxaloacetic transaminase, and the expressions of storage protein synthesis factor genes, namely, GluA and GluB, and subfamily genes, namely, pro14, BiP1, and PDIL1, which co-induced the changes of storage protein synthesis in rice grains. Furthermore, the increased temperature changed the balance of grain storage substances which may lead to the significantly increased chalky rate (197.67%) and chalkiness (532.92%). Moreover, there was a significant negative correlation between prolamin content and chalkiness, indicating that nitrogen fertilizer might regulate the formation of chalkiness by affecting the synthesis of prolamin. Results suggested that nitrogen application could regulate the related core factors involved in nitrogen metabolism pathways, which, in turn, affects the changes in the storage protein components in the grain and further affects quality. Therefore, as a conventional cultivation measure, nitrogen application would have a certain value in future rice production in response to climate warming.

Levels, Sources, and Health Damage of Dust in Grain Transportation and Storage: A Case Study of Chinese Grain Storage Companies

A large amount of mixed dust exists in grain, which can easily stimulate the respiratory system and cause diseases. This study explored contamination levels and health effects of this grain dust. A total of 616 dust samples from different stages and types of grain were collected in China—in Hefei (Anhui), Shenzhen (Guangdong), Chengdu (Sichuan), Changchun (Jilin), and Shunyi (Beijing)—and analyzed using the filter membrane method and a laser particle size analyzer. A probabilistic risk assessment model was developed to explore the health effects of grain dust on workers in the grain storage industry based on the United States Environmental Protection Agency risk assessment model and the Monte Carlo simulation method. Sensitivity analysis methods were used to analyze the various exposure parameters and influencing factors that affect the health risk assessment results. This assessment model was applied to translate health risks into disability-adjusted life years (DALY). The results revealed that the concentration of dust ranged from 25 to 70 mg/m3, which followed normal distribution and the proportion of dust with a particle size of less than 10 μm exceeded 10%. Workers in the transporting stage were exposed to the largest health risk, which followed a lognormal distribution. The average health risks for workers in the entering and exiting zones were slightly below 2.5 × 10−5. The sensitivity analysis indicated that average time, exposure duration, inhalation rate, and dust concentration made great contributions to dust health risk. Workers in the grain storage and transportation stage had the health damage, and the average DALY exceeded 0.4 years.

How to Guarantee Food Safety via Grain Storage? An Approach to Improve Management Effectiveness by Machine Learning Algorithms

The purpose of grain storage management is to dynamically analyze the quality change of the reserved grains, adopt scientific and effective management methods to delay the speed of the quality deterioration, and reduce the loss rate during storage. At present, the supervision of the grain quality in the reserve mainly depends on the periodic measurements of the quality of the grains and the milled products. The data obtained by the above approach is accurate and reliable, but the workload is too large while the frequency is high. The obtained conclusions are also limited to the studied area and not applicable to be extended into other scenarios. Therefore, there is an urgent need of a general method that can quickly predict the quality of grains given different species, regions and storage periods based on historical data. In this study, we introduced Back-Propagation (BP) neural network algorithm and support vector machine algorithm into the quality prediction of the reserved grains. We used quality index, temperature and humidity data to build both an intertemporal prediction model and a synchronous prediction model. The results show that the BP neural network based on the storage characters from the first three periods can accurately predict the key storage characters intertemporally. The support vector machine can provide precise predictions of the key storage characters synchronously. The average predictive error for each of wheat, rice and corn is less than 15%, while the one for soybean is about 20%, all of which can meet the practical demands. In conclusion, the machine learning algorithms are helpful to improve the management effectiveness of grain storage.

Effect of Temperature Gradient of Grain Storage on Migration and Distribution of Three Pests

Temperature gradients were set at the opposite sides of the grain storage: 25°C-30°C, 20°C-30°C, 20°C-35°C, 30°C-30°C. The migration and distribution of imago of Sitophilus oryzae, Rhizopertha dominica and Tribolium castaneum in the grain storage were observed. The results showed significant differences that the distribution trends of imago of Sitophilus oryzae, Rhizopertha dominica and Tribolium castaneum within a certain grain storage temperature gradient (p < 0.05). The temperature gradient of grain storage is 25°C-30°C. Tribolium castaneum tends to gather in the 30°C side area of grain storage, while Sitophilus oryzae has no obvious trend, while Rhizopertha dominica tends to gather in the 25°C. The temperature gradient of grain storage is 20°C-30°C. Both Tribolium castaneum and Sitophilus oryzae tend to gather in the 30°C side area of grain storage, while Rhizopertha dominica tends to gather in the 20°C. The temperature gradient of grain storage is 20°C-35°C. Tribolium castaneum, Sitophilus oryzae and Rhizopertha dominica all tend to gather in the area on the side of grain storage at 35°C. The temperature gradient of grain storage is 30°C-30°C, and there is no obvious trend for Tribolium castaneum. Rhizopertha dominica tends to gather in the 30°C area on the left side of grain storage, while Sitophilus oryzae tends to gather in the 30°C area on the right side of grain storage. After cooling down, it was found that Sitophilus oryzae tended to gather in the center of the grain storage, while the Tribolium castaneum had no obvious trend, and the Rhizopertha dominica tended to gather in the peripheral area of the grain storage.