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The supervision of grain reserves is a major event of national food security. China has built the largest grain internet of things in the world. Although there are still have some problems such as low data quality, low utilization rate, and serious information islands, it still provides a basis for conducting digital supervision on grain reserves. On the basis of studying the multi-fields coupling and biological theory in stored grain ecosystems, the author team proposed the continuity, periodicity and coordination principles of the digital supervision of grain reserves, and further proposed 7 intelligent strategies using the big data analysis of grain situation and the intelligent analysis method of 10 modes of grain storage in the granary. In combination with the application cases of 10 provinces that participated in the policy oriented inventory check of grain reserves organized in 2018, this paper analyzes the principle of digital supervision of grain reserves and 7 intelligent methods, which will accelerate the transformation and large-scale promotion of relevant technological achievements, and accelerating the construction of a high-quality technical system for grain reserves supervision. This digital intelligence method will promote the transformation of grain reserve management from “human management" to "technology management”, and let data play its due role in grain reserve decision-making and management.

Compared with the advanced and sophisticated industrial production, agriculture and food production appear backward and sloppy, and agricultural production management methods are lacking. The fourth industrial revolution, represented by information technologies such as intelligent perception, Internet of Things, block chain, big data and artificial intelligence, has empowered traditional industries, and agriculture has stepped into a new digital, intelligence and even wisdom, which could provide a new opportunity to improve agricultural production management. Existing agricultural production management research is mostly limited to the study of concept definition, applicable theory and other issues. The development of information technology has built up a low-level Internet of Things with certain coverage, which brings some convenience, but cannot effectively support agricultural management and decision-making due to data silos, data waste, data abuse, data falsification and other thorny issues. From the perspective of top-level design and system management, this paper addressed the problems in the development of smart agriculture, conceptualized the characteristics of the event and natural event chains in the agricultural industry chain. This paper also proposed for the first time an event-correlation management approach and its wisdom strategy. The implementation of the event-correlation method included five aspects, including goal alignment, index systematization, asset linkage, process linkage and effect traceability. The application of the event-correlation management approach and its wisdom in the 5T management standard designation for Jilin rice brand building and the “six-step fresh rice precision control technology” innovation system of Wilmar rice industry have shown that it can improve the culture of rice cultivation, and systematically reduce losses to improve quality and increase economic benefits.

The influence of science and technology on cognitive change has a long history, which lead to forming philosophy of science and philosophy of technology respectively. The development of grain storage technology in China has gone through three stages: the initial exploration before the reform and opening up, the construction of intellingence in the past 10 years modern granaries in 30 years after the reform and opening up, and the creation of digital. The scientific and technological progress of grain storage in China has been witnessed by all, including building a modern granary with "four in one" new grain storage technology, to forming the world's largest grain and food networking with information technology, original multi-field coupling and bio-field theory, and realizing the dynamic supervision of grain reserves with grain cloud image scanning technology. In the new era, the political and economic situations have not changed significantly in the past century, and the new requirements of China's second centenary goal for food security and the impact of the fourth industrial revolution have made the trend of food science and technology becoming more and more intelligent. Based on the accumulation of scientific and technological achievements in grain storage practice for more than 40 years in China, combined with the team's research on multi-field coupling and bio-field theory of grain storage, dynamic supervision of cloud image of grain reserves, 5T information management of natural block chain for grain storage, and intelligent EAT window measurement and control methods for grain drying, this paper attempted to take the basic idea of "one divides into two, two divides into three, and three generates changes" on the basis of deconstructing the micro and macro ternary microstructure of grain storage system. Taking the joint driving of mechanism and data as the intelligent strategy, the granary philosophy is introduced to improve the recognition of existing scientific and technological achievements. The granary philosophy also guided the exploration of grain storage technology in the new era, and provided support for building a high-quality intelligent food system. The granary philosophy is a deep reflection on the practical situation of grain storage, and has certain universality, which originates from grain storage practice, but is not limited to grain storage practice.

In order to improve the information and intelligent technology level of the national policy grain inventory, the portable grain inventory measurement equipment was developed by comprehensive application of modern technologies such as photoelectric detection, integrated circuit, software development, and mathematical modeling. On the basis of functional requirement analysis, the overall technical route of equipment research and development is formulated. The key problems and solutions such as high-precision measuring equipment and integrated control program, adaptive grain pile volume measurement scheme and algorithm and management software are focused. The application of equipment is briefly introduced. The equipment is advanced in technology, easy to carry, rich in functions and easy to operate. It provides a new measuring technology for the national grain clearance check.

Dynamic monitoring technology of grain inventory quantity has become a new technical demand of grain storage management. On the basis of the current situation of static monitoring technology of grain stock quantity, the difficulties of dynamic monitoring technology were analyzed and put forward. This paper mainly introduced the research progress and application of dynamic inventory quantity monitoring in the development of three-dimensional measuring device, data acquisition and fusion technology of multi- measuring stations of super large grain piles, high precision volume algorithm of irregular grain piles, average density evaluation method of complex heterogeneous grain piles, integrated management software platform and so on. The measurement error of the developed dynamic monitoring system for grain inventory quantity was less than 2%, which meet the application requirements. This new technology provides the technical support for the information management and digital transformation development of grain storage business.

Based on the implementing grain security projects and instituting other relevant grain security policies, China has promoted the process of digitalization and intelligence of grain storage and built the world's largest grain Internet of Things, since the 18th National Congress of the Communist Party of China. But, the resulting large amount of grain data, mainly based on temperature, can not effectively support decision-making and management on grain storage. Based on the study of the multi-field coupling theory of grain pile ecosystem, our research team further extracted the continuity principle, periodicity principle, and coordination principle of digital supervision of grain reserves, and proposed a series of intelligent strategies such as AID, ABC, 6R, SIN, CAE, O, and U. However, the application of these strategies directly faces the original data, which has some problems such as low efficiency and large error. To apply the intelligent strategies efficiently and correctly, the basic data manual of intelligent analysis of grain condition has been developed, according to the original grain condition data of typical granaries and main grain varieties in different grain storage ecological regions in China. The development of this manual is expected to consolidate the foundation of intelligent analysis of grain situation, which could promote the digital monitoring of grain storage quantity and quality, and realize the transformation from "manual defense" to “technical defense”.

The stored grain can be regarded as a complex ecosystem, which exist a complex multi-field coupling interaction among the abiotic factors, the biotic factors, and the surrounding environment. In this system, only a few parameters such as temperature can be accurately detected, which causes the system to operate like a “black box” to the outside world. To truly and accurately detect various grain pile parameters, and further study the multi-field coupling interaction in grain piles, a graphical detection system for multi-filed interaction in grain storage based on NMR has been developed. The system consists of an NMR imaging analyzer, a test grain bin, and a data acquisition and processing system, which can accurately detect the grain pile temperature, humidity, and moisture simultaneously, and intuitively and vividly present the cloud map of the temperature field, humidity field, and moisture field in the grain pile through the cloud map drawing software. In this system, the NMR imaging technology was applied to the research field of multi-field coupling interaction in grain piles for the first time, which can provide a new technical means to find out the complex coupling relationship of stored grain ecosystem and further confirm the correctness of relevant theoretical research. The development of this system will be helpful in deepening the theory of multi-field coupling and biological field of grain piles, developed by the industry.

The grain storage process could be affected by many aspects such as biological field and non biological field, which will lead to the phenomenon of heating, mildew, dewing and pest damage in the grain storage process. It is urgent to develop convenient, fast, multi-functional and high-precision on-site detection tools. According to the requirements of actual grain storage management, the multi-functional grain storage safety on-site rapid detection analyzer could calculate the stored grain moisture, water activity, absolute humidity, accumulated temperature, accumulated humidity, J/Q value and absolute water potential with models and algorithms on the basis of multi-point high-precision detection of temperature, humidity and CO2 concentration, and could graphically expresse the calculated results to assist in the determination of stored grain conditions such as safety, condensation, heat, mildew, etc, which will have mechanical ventilation operation parameter selection and intelligent control. The preliminary application of the instrument shows that it can provide effective technical support for granary management and has a good application prospect.

Artificial intelligence technology has shown incomparable advantages in solving traditional agricultural problems. At present, the determination of moisture content and grade of high moisture corn in grain purchase is still mainly based on artificial sensory detection. There are many problems such as heavy workload, low efficiency, poor repeatability, and strong subjectivity, which will cause the loss of grain quantity and quality, and this problems even affect the benefits of enterprises and farmers. Aiming at the technical difficulties in rapid detection of high moisture maize, this study obtains enlightenment from the experience of front line personnel in visual measurement of moisture. Based on mining the rich information in corn kernel images, a new bionic image rapid nondestructive measurement method using the mutual information entropy as the coupling degree evaluation index, were studied then a intelligent purchase grading system of high moisture corn were developed and tested. The test results show that on the basis of realization of the bionic intelligent algorithm of ‘watching moisture by machine’, the purchase of high moisture corn is a technical path worth exploring.

Hot air drying is the key link of bulk grain and agricultural product processing. Because of the adjustment of national environmental protection and energy utilization policies in the new era, it is required to research and develop the energy saving technology of hot air drying for agricultural product. The current research is mostly limited to practical work tracking and empirical design, and there are also numerical calculations by heat and mass transfer theory. However these approaches have some limitations. Physical simulation is an effective potential method. In the process of studying the condensation increasing efficiency and energy saving technology, this paper has developed a test system which can simulate the actual hot air drying recycling energy. It has multi-parameter adjustable, graphical display drying state, energy consumption monitoring and other functions, and it can also provide effective means to study energy saving technology of hot air drying of agricultural product. The corn drying test for this system showed that energy recycling energy-saving drying could save energy 32%~56% when compared with ordinary open hot air drying.

Research on process parameter optimization and process intelligent control is an important element in the design and development of grain drying equipment. Existing methods mostly use simulation, device experiments or field experiments to obtain data, which have large differences with the actual drying results or the experimental process is time-consuming and vulnerable to interference. In this study, with reference to the process and structure of large continuous grain drying production equipment, a continuous grain drying simulation experimental system was developed and designed, including grain feeding equipment, dryer main body, grain discharge equipment, waste heat recovery, condensing device, hot air equipment and measurement and control system, which can simulate the grain drying operation process. This system can also optimize the drying process parameters, and carry out indoor grain drying quality change law, energy consumption law and production efficiency. The system can be used as the first-line staff post. The system could be used as the pre-service training for the workers on the production line, the experimental teaching of related majors in universities and colleges and the experimental research system of scientific research institutions.

Based on the theory of grain storage ecosystem, multi-field coupling and ventilation window, the dynamic analysis software of grain condition cloud map is researched and developed by WU model,sinusoidal model of grain temperature change, heat and mass transfer model and related empirical model.By drawing visual dynamic cloud maps of grain condition, combining with the warehouse types, grain storage characteristics and regional environment, the state and change of grain storage can be analyzed and predicted,then the quantity and quality can be distinguished.In addition, the software system has been applied and improved in the national warehouse inventory in 2018 and 2019.It provides effective technical support and tool services for the realization of the whole process of grain storage quantity and quality safety management.

Based on the linear correlation between grain moisture content and radio frequency(RF) signal,a new granary detection device was developed.A new RF detection circuit was designed to redesign the detection structure.Through the special detection circuit and detection structure,the accuracy of real-time online detection of grain moisture in the granary was improved,which provided a reliable hardware foundation for grain detection and monitoring.

In a search for novel nonsugar α‐glucosidase inhibitors for diabetes treatment, a series of N‐(phenylsulfonyl)thiazole‐2‐carboxamide derivatives were designed and synthesized, the α‐glucosidase inhibitory activities were then evaluated. Several compounds with promising α‐glucosidase inhibitory effects were identified. Among these, compound W24 which shows low cytotoxicity and good α‐glucosidase inhibitory activity with an IC50 value of 53.0 ± 7.7 μM, is more competitive compared with the commercially available drug acarbose (IC50 = 228.3 ± 9.2 μM). W24 was identified as a promising candidate in the development of α‐glucosidase inhibitors. Molecular docking studies and molecular dynamics simulation were also performed to reveal the binding pattern of the active compound to α‐glucosidase, and the binding free energy of the best compound W24 was 36.3403 ± 3.91 kcal/mol. [ABSTRACT FROM AUTHOR]

Research on a method for fast selecting feature wavelengths from the nitrogen spectral information is necessary, which can determine the nitrogen content of crops. Based on the uniformity of uniform design, the present paper proposed an improved particle swarm optimization (PSO) method. The method can choose the initial particle swarm uniformly and describe the optimization space well by fewer sample points, which is helpful to avoiding the local optimum and accelerate the convergence. Then, the method was applied to fast select the nitrogen spectral wavelengths of soybean, cotton and maize. Calibration models based on the partial least square (PLS) method and selected wavelengths were constructed. The results illustrate that compared with the original wavelengths, the number of selected wavelengths decreases about 93%, which means the computation is simplified. Also, the precision of PLS prediction mode based on the selected wavelengths improves by 34% at least, and the prediction ability of calibration model increases greatly. Therefore, the proposed method is both correct and effective.