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Granular grain can be stored into the warehouse in food industry. The high loading efficiency is often required to optimize the land use for the effective grain preservation. The crucial warehouse mode has emerged in the regions with limited land resources. The diverse grain varieties can be stored to promote the sustainable development. Currently, the granular grain warehouse normally employs a load-bearing system that constituted by a reinforced concrete frame structure. The vertical gravity load of the grain is supported by the well-beam floors and large-section frame columns, while the lateral pressure exerted by the grain is directly absorbed by reinforced concrete horizontal tie-up beams integrated within the warehouse walls. The structural integrity of granular grain warehouses can also depend on the dynamic lateral pressure exerted by the storage material on the warehouse wall during seismic events. In this study, a scaled-down 1:25 three-story warehouse was designed and then produced to explore the effect of granular grains on the dynamic lateral pressure. Shaking table tests were carried out to simulate the varying ground vibration levels under three seismic waves. The data was collected on the acceleration and the lateral pressure that exerted on its walls. Analysed the seismic response characteristics of the storage material. Furthermore, the overpressure coefficient was obtained from the patterns of dynamic lateral pressure on the walls. The dynamic lateral pressure on the warehouse walls was also calculated. Acorrelation analysis was conducted between the height of warehouse and the timing of the peak moment, when the dynamic lateral pressure was exerted on the warehouse walls. Specifically, there was a noticeable lag in the occurrence of this peak moment, as the height of the building increased. Moreover, the peak moment of dynamic lateral pressure on the warehouse wall was consistently lagged behind that of acceleration on the same wall, particularly with the elevation of the height. The dynamic lateral pressure on the warehouse walls escalated progressively with each ascending floor. In the given floor, this dynamic lateral pressure incrementally intensified along the vertical extent of the warehouse walls. Each floor was found with an average increase of approximately 29% per floor. The dynamic lateral pressure exerted on the upper and middle sections of the warehouse walls was 2.5 and 1.4 times greater than that on the lower sections within the same floor. Consequently, the structural design of granular grain warehouses should consider these variations across different floor levels. The overpressure coefficient of the warehouse wall increased with the elevation of the floor, indicating a higher overall overpressure at upper levels. Within a single floor, the overpressure coefficient peaks at the upper section of the warehouse wall, with the middle and lower sections exhibiting lower and closer. Specifically, the maximum overpressure coefficients were 2.9, 3.4, and 4.1, respectively, for the first, second, and third floors of the warehouse walls. The overpressure on the warehouse walls was of significant concern, when subjected to seismic activity. It is very necessary to consider the influence of the dynamic lateral pressure on the warehouse wall across various floors. The seismic response of the storage materials can be used to elucidate the distribution pattern of dynamic lateral pressure. The overpressure on the warehouse walls can be assessed to calculate the lateral pressure on these walls. The findings can offer a strong reference for the warehouses of granular grains under seismic conditions. [ABSTRACT FROM AUTHOR]

[Objectives] To discuss the possibility of the non-destructive prediction of the total viable count of bacteria in the polluted eggs, this paper explored a non-destructive method that using near infrared hyperspectral imaging to predict and visualize the total viable count of bacteria in eggs. [Methods] Egg samples were inoculated with the mixture solution of Escherichia coli and Pseudomonas aeruginosa, then the original hyperspectral information and the total viable count of bacteria of eggs in different pollution levels during storage were collected. After selecting the best pretreatment method in this experiment, the predicting model by partial least squares (PLS) and support vector machine (SVM) model were developed based on full wavelengths and the feature wavelengths via the successive projections algorithm (SPA). Finally, the relative best prediction model of the viable count of bacteria was selected and the visualization study of the bacteria was realized in eggs. [Results] The second derivative method was the relative best pretreatment method, the correlation index of cross validation (RCV) was 0.88, and the root mean square error of cross validation was 0.82 lg (CFU·g-1). The relative best prediction model was the SVM model which was based on the feature wavelengths, the correlation index of calibration (RC) and prediction (RP) was 0.88 and 0.84, and the root mean square error of calibration and prediction was 0.86 and 0.97 lg (CFU·g-1), respectively. The visualized images of the polluted levels in eggs were built based on the difference of the pollution levels and spectral characteristics. [Conclusions] The near infrared hyperspectral imaging technology, and multivariate statistical and image processing methods can realize the prediction and visualization of the total viable count of bacteria in eggs, and this technology can also provide the foundation for on-line detection of the egg security. [ABSTRACT FROM AUTHOR]

Aquaculture park is an important form to promote scale breeding, which has an important significance for the transformation of aquaculture production style and the structural reform of supply side. In this paper, we use the stochastic frontier approach to analyze the production efficiency of aquaculture park with large scale in Zhejiang Province and its influencing factors. The stochastic frontier analysis method is widely used in the studies on agricultural production, yet the research using this method to calculate the technology efficiency of aquaculture park and analyze its influencing factors is relatively few. The technical efficiency of tilapia culture in Guangxi and the technical efficiency of freshwater aquaculture in China have been studied by some scholars. However, most of these studies are limited to a single aquatic species or based on macro data, lacking the analysis of the operating efficiency of the micro main varieties. This paper chooses Zhejiang Province as the research area because of its developed aquaculture industry, typical park construction, standard breeding and industrial organization system. Based on previous studies, we investigate the technical efficiency of aquatic breeding park and its influencing factors, which aimed to provide reference for the healthy development of the aquaculture industry in China. The data of empirical analysis come from the Agriculture Department and the Financial Department of Zhejiang Province, which cover 116 modern fishery parks. Cross-sectional data of both before and after the construction of modern fishery park are collected. Statistical indicators mainly include the scale and efficiency (breeding area, total production, total output value, labor productivity per capita), capital investments (provincial capital investment, capital investment of owners), facilities and equipment investments (reservoir, cold storage preservation, supporting house for production, oxygen increasing machine, feeding machine), technology application and brand building (standardized production area, sewage purification treatment, disease prevention and treatment, aquatic products brand), and business entities (main operating company, cooperatives and farmers). Case data are discarded if key information is missing. At last, a total of 108 valid cases are obtained. In order to eliminate the impact of price changes, the output value of fishery park, the capital investments and other variables are divided by production price index. The results show that: (1) Scale production exerts a positive effect on the aquaculture production efficiency which has increased from 0.673 to 0.712 since the completion of the park; (2) The standardization level effectively improves the breeding technology efficiency of the park, with a regression coefficient of -0.0003; (3) Disease control equipment improves the technical inefficiency (the regression coefficient is 0.0033), which means that excessive investment in infrastructure will lead to idle equipment and hinder the improvement of technical efficiency; (4) Brand building positively influences the breeding technology efficiency of the park, with a regression coefficient of -0.0033; (5) Leading enterprises have the greatest positive effect on the level of technical efficiency, followed by the organization of fishery cooperation and the large professional farmers, with the regression coefficients of technical inefficiency being -0.0017, 0.0015 and -0.0008 respectively. But the regression coefficient of ordinary farmers is 0.0012, which implies no significant effect on the efficiency of aquaculture technology. Some policy implications can be drawn from the results of the empirical study. Increasing production of aquaculture park inputs, investing infrastructure following principle of moderate scale, paying attention to brand building and innovating the mode of fishery organization and so on may enhance the technical efficiency of aquaculture park. [ABSTRACT FROM AUTHOR]