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Ge W.,Heilongjiang Bayi Agricultural University | Zhao C.,Beijing Research Center for Information Technology in Agriculture | Zhao C.,Key Laboratory of Information Technology in Agriculture
Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery | Year: 2014

Agricultural internet of things (Ag-IoT) is the highly integrated and comprehensive application of the new generation of information technology in agricultural field. Ag-IoT is playing an important leading role in the agricultural informationization of China. It has changed the traditional agricultural production mode, and it is also promoting the transformation from the traditional agriculture to intelligent and precision agriculture. The concept of Ag-IoT and its technical system framework were firstly introduced. Then the research status and advances of sensing technologies, communicating technologies and key application technologies used in Ag-IoT were reviewed in detail. The challenges and problems existing in the development of Ag-IoT in China were further analyzed. Based on the analysis, countermeasures for the applications and development of Ag-IoT of China in many aspects were proposed, such as research priorities, development layout, advancing directions, application models and mechanisms for sustainable development.


Sun C.-H.,National Engineering Research Center | Sun C.-H.,Key Laboratory of Information Technology in Agriculture | Sun C.-H.,China Agricultural University | Li W.-Y.,National Engineering Research Center | And 7 more authors.
Computers and Electronics in Agriculture | Year: 2013

With the increased attention given to geographical labeling and the increased awareness of enterprise brands in many countries, anti-counterfeit systems for identifying the origin of agricultural products are important for limiting the production of fake goods and improving the competitiveness of agricultural products. An anti-counterfeit system for identifying the origin of agricultural products based on GPS and encrypted Chinese-sensible Code was designed. The anti-counterfeit system used the LPC1768 microprocessor of the Coretex-M3 series as its core controller, and the system was programmed with the C language. The system could collect and process the weight and location of the agricultural products, encrypt and encode the Chinese-sensible Code based on an AES (Advanced Encryption Standard) algorithm with a different cipher each time, and then print the anti-counterfeit label. The application results showed that the system runs reliably and stably, 98% anti-counterfeit labels were correctly identified and used to trace the origin of the products. Additionally, the system accomplished the task of providing precise positioning and location accuracy is about 10. m scope and unique identification information about the origin of agricultural products and achieved the aim of developing an anti-counterfeiting system. © 2013 Elsevier B.V.


Wang Y.-C.,Shandong University of Science and Technology | Wang Y.-C.,Chinese National Engineering Research Center for Information Technology in Agriculture | Wang Y.-C.,Key Laboratory of Information Technology in Agriculture | Gu X.-H.,Chinese National Engineering Research Center for Information Technology in Agriculture | And 5 more authors.
Guang Pu Xue Yu Guang Pu Fen Xi/Spectroscopy and Spectral Analysis | Year: 2014

The present study aims to assess the feasibility of multi-spectral data in monitoring soil organic matter content. The data source comes from hyperspectral measured under laboratory condition, and simulated multi-spectral data from the hyperspectral. According to the reflectance response functions of Landsat TM and HJ-CCD (the Environment and Disaster Reduction Small Satellites, HJ), the hyperspectra were resampled for the corresponding bands of multi-spectral sensors. The correlation between hyperspectral, simulated reflectance spectra and organic matter content was calculated, and used to extract the sensitive bands of the organic matter in the north fluvo-aquic soil. The partial least square regression (PLSR) method was used to establish experiential models to estimate soil organic matter content. Both root mean squared error (RMSE) and coefficient of the determination (R2) were introduced to test the precision and stability of the modes. Results demonstrate that compared with the hyperspectral data, the best model established by simulated multi-spectral data gives a good result for organic matter content, with R2=0.586, and RMSE=0.280. Therefore, using multi-spectral data to predict tide soil organic matter content is feasible.


Cheng X.-J.,Shandong University of Science and Technology | Cheng X.-J.,Chinese National Engineering Research Center for Information Technology in Agriculture | Cheng X.-J.,Key Laboratory of Information Technology in Agriculture | Xu X.-G.,Chinese National Engineering Research Center for Information Technology in Agriculture | And 5 more authors.
Guang Pu Xue Yu Guang Pu Fen Xi/Spectroscopy and Spectral Analysis | Year: 2014

Moisture content is an important index of crop water stress condition, timely and effective monitoring of crop water content is of great significance for evaluating crop water deficit balance and guiding agriculture irrigation. The present paper was trying to build a new crop water index for winter wheat vegetation water content based on NIR-Red spectral space. Firstly, canopy spectrums of winter wheat with narrow-band were resampled according to relative spectral response function of HJ-CCD and ZY-3. Then, a new index (PWI) was set up to estimate vegetation water content of winter wheat by improveing PDI (perpendicular drought index) and PVI (perpendicular vegetation index) based on NIR-Red spectral feature space. The results showed that the relationship between PWI and VWC(vegetation water content) was stable based on simulation of wide-band multispectral data HJ-CCD and ZY-3 with R2 being 0.684 and 0.683, respectively. And then VWC was estimated by using PWI with the R2 and RMSE being 0.764 and 0.764, 3.837% and 3.840%, respectively. The results indicated that PWI has certain feasibility to estimate crop water content. At the same time, it provides a new method for monitoring crop water content using remote sensing data HJ-CCD and ZY-3.


Xing B.,Beijing Academy of Agriculture and Forestry Sciences | Xing B.,Key Laboratory of Information Technology in Agriculture | Yang X.,Beijing Academy of Agriculture and Forestry Sciences | Yang X.,Key Laboratory of Information Technology in Agriculture | And 3 more authors.
Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering | Year: 2011

With the development of agricultural products delivery, increasing the efficiency of the agri-food enterprises in distribution and reducing the logistics cost become more and more important. Therefore, in order to improve loading rate and loading cost, the three dimension bin packing problem (3BPP) for agricultural products was studied. With analyzing the features of agricultural products, considering the restrains of vehicle load, package size and bearing capacity, the putting sequence and directions of boxes were optimized by the GA algorithm for 3BPP. The algorithm was implemented by Java language which is an object oriented program language. Ten groups of experiments were carried out using the packing data acquired from an agricultural food production and distribution company, and the data were applied to test the algorithm. The results showed that the average running time was 37 947 ms, and the average value of objective function which can describe loading rate and loading cost was improved from 72.72% to 81.14%.

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