Interactions of Mutiple Biological Fields in Stored Grain Ecosystems

Analysis of the impact of drying on common wheat quality and safety

Mycotoxin contamination in grain has been an ongoing concern in the world. Wheat, as a staple crop in China, is particularly notable for its mycotoxin contamination. The main mycotoxins in wheat include deoxynivalenol (DON) and its derivates, zearalenone (ZEN) and aflatoxin B1 (AFB1). After harvest, drying process is an effective technique and a necessary step to ensure the long-term safe storage of wheat. In this study, the moisture content, the concentrations of total fungi and main mycotoxins in post-harvest wheat of three wheat growing areas in the North China Plain were examined, and the effect of different drying methods on wheat quality was evaluated. The results showed that 87.5% of wheat samples were simultaneously contaminated with two or more mycotoxins. Due to the pre-harvest heavy rainfall, the moisture content, the levels of total fungi and mycotoxins in wheat samples of Liaocheng city were significantly higher compared to other regions. Moreover, the effects of different drying methods on the starch gelatinization and viscosity properties of wheat were investigated. The results showed that both natural air drying and dryer drying altered the crystal structure within starch particles and affected the gelatinization and viscosity properties of wheat starch. However, there is no significant difference between the wheat samples treated with two drying methods.

Occurrence of Mycotoxins in Foods: Unraveling the Knowledge Gaps on Their Persistence in Food Production Systems

In this review, the intricate issue about the occurrence levels of mycotoxins in foods is discussed aiming to underline the main knowledge gaps on the persistence of these toxicants in the food production system. Mycotoxins have been a key challenge to the food industry, economic growth, and consumers' health. Despite a breadth of studies over the past decades, the persistence of mycotoxins in foods remain an overlooked concern that urges exploration. Therefore, we aimed to concisely underline the matter and provide possible biochemical and metabolic details that can be relevant to the food sector and overall public health. We also stress the application of computational modeling, high-throughput omics, and high-resolution imaging approaches, which can provide insights into the structural and physicochemical characteristics and the metabolic activities which occur in a stored cereal grain's embryo and endosperm and their relationship with storage fungi and mycotoxins on a cellular level. In addition, there is a need for extensive collaborative network and funding, which will play a key role in finding effective solutions against the persistence of mycotoxins at the genetic and molecular to metabolic levels in the food system.

Compression and Fungal Heat Production in Maize Bulk Considering Kernel Breakage

Breakage in maize kernels and vertical pressure in grains lead to the uneven distribution of grain bulk density, which easily causes undesired problems in terms of grain storage. The objective of this study was, therefore, to determine the compression and heat production of the whole kernel (WK) and half kernel (HK) under two different loadings, i.e., 50 and 150 kPa, in maize bulk. An easy-to-use element testing system was developed by modification of an oedometer, and an empirical–analytical–numerical method was established to evaluate fungal heat production, considering kernel breakage and vertical pressure. Based on the experimental results, it was found that breakage induced larger compression; the compression of HK was 62% and 58% higher than that of WK at 50 kPa and 150 kPa, respectively. The creep model of the Hooke spring–Kelvin model in series can be used to accurately describe the creep behavior of maize bulk. Fungi and aerobic plate counting (APC) were affected significantly by the breakage and vertical pressure. APC in HK was 19 and 15 times that of WK under 150 and 50 kPa, respectively. The heat released by the development of fungi was found to be directly related to the APC results. The average temperatures of WK and HK under 150 and 50 kPa were 11.1%, 9.7%, 7.9%, and 7.6% higher than the room temperature, respectively. A numerical method was established to simulate the temperature increase due to fungi development. Based on the numerical results, heat production (Q) by fungi was estimated, and the results showed that the Q in HK was 1.29 and 1.32 times that of WK on average under 150 and 50 kPa. Additionally, the heat production results agreed very well with the APC results.

Control and Real-Time Data Acquisition of an Experimental Platform for Stored Grain Aeration Study

Aeration is one of the most important methods to keep stored grain safe and maintain its quality. Experimental platforms are used for stored grain aeration study in a laboratory-scale. The purpose of this paper was to provide the real-time data acquisition and control system design of a new experimental platform with multifunction for stored grain study. Requirements of the aeration experiments were analyzed, and multi running modes were designed. The aeration inlet air conditions were designed to be adjustable and multi variables need to be controlled simultaneously, which was a key problem to be solved for the platform. An ON/OFF-PID based multivariable cooperative control method was proposed, and two control loops were formed where inlet air temperature and humidity were considered separately while could be controlled simultaneously with a logic judgement strategy. Real-time data needed to be monitored was acquired with different sensors and displayed intuitively. Experiments were carried out to test the static and dynamic characteristics of the control method and three inlet air flow rates of 0.03, 0.08 and 0.13 m·s⁻¹were used. Performance of the data acquisition system was also tested. The results showed that, the inlet air conditions control error was within ±1 °C and 10% for temperature and relative humidity, respectively. The real-time data acquisition of multi parameters during aeration process was realized. The experimental platform can be used for studies of different aeration objectives.

Estimation of Free Fatty Acids in Stored Paddy Rice Using Multiple-Kernel Support Vector Regression

Grain quality changes during the storage period, and an important grain quality indictor is the free fatty acid (FFA) content. Understanding real-time change of FFA content in stored grain is significant for grain storage safety. However, the FFA content requires manual detection with time-consuming and complex procedures. Thus, this paper is dedicated to developing a method to estimate FFA content in stored grain accurately. We proposed a machine learning approach—multiple-kernel support vector regression—to complete this goal, which improved the accuracy and robustness of the FFA estimation. The effectiveness of the proposed approach was validated by the grain storage data collected from northeast China. To show the merits of the proposed method, several prevailing prediction methods, such as single-kernel support vector regression, multiple linear regression, and back propagation neural network, were introduced for comparative purposes, and several quantitative statistical indexes were adopted to evaluate the performance of different models. The results showed that the proposed approach can achieve a high accuracy with mean absolute error of 0.341 mg KOH/100 g, root mean square error of 0.442 mg KOH/100 g, and mean absolute percentage error of 2.026%. Among the four models tested, the multiple-kernel support vector regression model performed best and made the most robust forecasts of FFA content in stored grain.