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Journal of Integrative Agriculture 2023年第2期22卷 611-622页

作者： GUO Shi-juan Lü Xin-ye HU Xiang-dong institute of agricultural Economics and Development Chinese Academy of Agricultural SciencesBeijing 100081P.R.China institute of agricultural information and economy Shandong Academy of Agricultural SciencesJinan 250000P.R.China

This paper aims to optimize the culling compensation policy from a micro perspective through scenario *** on an investigation of 273 pig farms in eight regions,four typical pig farms were constructed according to farm size and breeding mode,representing the swine producers in ***,a decision objective function of pig farms facing suspected African swine fever(ASF)outbreaks was *** study used a mathematical programming model to design and simulate scenarios based on compensation standards and local implementation levels,aiming to incentivize pig farms to report *** results show that the optimal decisions on epidemic reports differed among typical farms and by herd daily *** results suggest the following adjustments for optimizing culling compensation policies:(1)to set culling compensation standards based on the market value and(2)to maintain a high level of epidemic surveillance capability in the animal husbandry and veterinary sector.

关键词： culling compensation African swine fever epidemic report mathematical programming model

Identification of tomato leaf diseases using convolutional neural network with multi-scale and feature reuse

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International Journal of agricultural and Biological Engineering 2023年第6期16卷 226-235页

作者： Peng Li Nan Zhong Wei Dong Meng Zhang Dantong Yang College of Engineering South China Agricultural UniversityGuangzhou 510642China agricultural economy and information Research institute Anhui Academy of Agricultural SciencesHefei 230031China

Various diseases seriously affect the quality and yield of tomatoes. Fast and accurate identification of disease types is of great significance for the development of smart agriculture. Many Convolution Neural Network (CNN) models have been applied to the identification of tomato leaf diseases and achieved good results. However, some of these are executed at the cost of large calculation time and huge storage space. This study proposed a lightweight CNN model named MFRCNN, which is established by the multi-scale and feature reuse structure rather than simply stacking convolution layer by layer. To examine the model performances, two types of tomato leaf disease datasets were collected. One is the laboratory-based dataset, including one healthy and nine diseases, and the other is the field-based dataset, including five kinds of diseases. Afterward, the proposed MFRCNN and some popular CNN models (AlexNet, SqueezeNet, VGG16, ResNet18, and GoogLeNet) were tested on the two datasets. The results showed that compared to traditional models, the MFRCNN achieved the optimal performance, with an accuracy of 99.01% and 98.75% in laboratory and field datasets, respectively. The MFRCNN not only had the highest accuracy but also had relatively less computing time and few training parameters. Especially in terms of storage space, the MFRCNN model only needs 2.7 MB of space. Therefore, this work provides a novel solution for plant disease diagnosis, which is of great importance for the development of plant disease diagnosis systems on low-performance terminals.

关键词： tomato diseases convolutional neural network confusion matrix multi-scale feature reuse

China Internet Industry State Analysis and Prosperity Indexes

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China Communications 2016年第10期13卷 245-252页

作者： Xiaojie Tu Mingzhu Wang Ke Sun Chunfei Zhang Li Zhang China Academy of information and Communications Technology Institute of Economy & Policy Research

With the background of China's fast growing economy, Internet has become a key factor to keep the economy go steadily. It is important to quantitatively analyze the whole Internet industry and hence master its development direction clearly, which will provide regulators with reference for industry analysis, policy formulation, and policy evaluation. This article re-constructs the calculation method of traditional Prosperity Indexes, and builds up a new indicators portfolio for Internet Industry Prosperity Indexes. By calculation, the Internet Industry Coincidence Index value is 105.9. And the Leading Index and Coincidence Index are all within the up-going range, which suggests that China's Internet Industry is likely to remain in its usual fast growing state.

关键词： prosperity analysis internet industry research HP filtering trend adjust coincidence index leading index

Estimating Rice Yield by HJ-1A Satellite Images

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Rice science 2011年第2期18卷 142-147页

作者： LI Wei-guo LI Hua ZHAO Li-hua institute of economy and information Jiangsu Academy of Agricultural Sciences Nanjing 210014 China Anhui agricultural University Hefei 230036 China

As illustrated by the case of Xuyi County, Jinhu County and Hongze County in Jiangsu Province, China, monitoring and forecasting of rice production were carried out by using HJ-1A satellite remote sensing images. The handhold GPS machines were used to measure the geographical position and some other information of these samples such as area shape. The GPS data and the interpretation marks were used to correct H J-1 image, assist human-computer interactive interpretation, and other operations. The test data had been participated in the whole classification process. The accuracy of interpreted information on rice planting area was more than 90% By using the leaf area index from the normalized difference vegetation index inversion, the biomass from the ratio vegetation index inversion, and combined with the rice yield estimation model, the rice yield was estimated. Further, the thematic map of rice production classification was made based on the rice yield data. According to the comparison results between measured and fitted values of yields and areas of sampling sites, the accuracy of the yield estimation was more than 85%. The results suggest that HJ-A/B images could basically meet the demand of rice growth monitoring and yield forecasting, and could be widely applied to rice production monitoring.

关键词： rice yield satellite remote sensing image estimation model

Assessment of Flood Catastrophe Risk for Grain Production at the Provincial Scale in China Based on the BMM Method

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Journal of Integrative Agriculture 2013年第12期12卷 2310-2320页

作者： XU Lei ZHANG Qiao ZHOU Ai-lian HUO Ran agricultural information institute Chinese Academy of Agricultural Sciences Key Laboratory of Agri-information Service Technology Ministry of Agriculture

Flood catastrophe risk assessment is imperative for the steady development of agriculture under the context of global climate change,and meanwhile,it is an urgent scientific issue need to be solved in agricultural risk assessment *** paper developed the methodology of flood catastrophe risk assessment,which can be shown as the standard process of crop loss calculation,Monte Carlo simulation,the generalized extreme value distribution（GEV） fitting,and risk *** on crop loss were collected based on hectares covered by natural disasters,hectares affected by natural disasters,and hectares destroyed by natural disasters using the standard *** Carlo simulation based on appropriate distribution was used to expand sample size to overcome the insufficiency of crop loss *** maxima model（BMM） approach based on the extreme value theory was for modeling the generalized extreme value distribution（GEV） of flood catastrophe loss,and then flood catastrophe risk at the provincial scale in China was *** Type III Extreme distribution（Weibull） has a weighted advantage of modeling flood catastrophe risk for grain *** impact of flood catastrophe to grain production in China was significantly serious,and high or very high risk of flood catastrophe mainly concentrates on the central and eastern regions of *** the scenario of suffering once-in-a-century flood disaster,for majority of the major-producing provinces,the probability of 10% reduction of grain output is more than 90%.Especially,the probabilities of more than 15% decline in grain production reach up to 99.99,99.86,99.69,and 91.60% respectively in Anhui,Jilin,Liaoning,and *** catastrophe assessment can provide multifaceted information about flood catastrophe risk that can help to guide management of flood catastrophe.

关键词： flood catastrophe risk assessment block maxima model(BMM) provincial scale China

Prediction Model of Weekly Retail Price for Eggs Based on Chaotic Neural Network

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Journal of Integrative Agriculture 2013年第12期12卷 2292-2299页

作者： LI Zhe-min CUI Li-guo XU Shi-wei WENG Ling-yun DONG Xiao-xia LI Gan-qiong YU Hai-peng agricultural information institute Chinese Academy of Agricultural Sciences/Key Laboratory of Agri-Information Service TechnologyMinistry of Agriculture

This paper establishes a short-term prediction model of weekly retail prices for eggs based on chaotic neural network with the weekly retail prices of eggs from January 2008 to December 2012 in *** the process of determining the structure of the chaotic neural network,the number of input layer nodes of the network is calculated by reconstructing phase space and computing its saturated embedding dimension,and then the number of hidden layer nodes is estimated by trial and ***,this model is applied to predict the retail prices of eggs and compared with *** result shows that the chaotic neural network has better nonlinear fitting ability and higher precision in the prediction of weekly retail price of *** empirical result also shows that the chaotic neural network can be widely used in the field of short-term prediction of agricultural prices.

关键词： chaos theory chaotic neural network neural network technology short-term prediction weekly retail price of eggs

China agricultural outlook for 2015–2024 based on China agricultural Monitoring and Early-warning System(CAMES)

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Journal of Integrative Agriculture 2015年第9期14卷 1889-1902页

作者： XU Shi-wei LI Gan-qiong LI Zhe-min agricultural information institute Chinese Academy of Agricultural Sciences Key Laboratory of agricultural information Service Technology Key Laboratory of Digital agricultural Early-warning Technology and System Chinese Academy of Agricultural Sciences

The primary goal of Chinese agricultural development is to guarantee national food security and supply of major agricultural products. Hence, the scientiifc work on agricultural monitoring and early warning as wel as agricultural outlook must be strengthened. In this study, we develop the China agricultural Monitoring and Early-warning System (CAMES) on the basis of a comparative study of domestic and international agricultural outlook models. The system is a dynamic and multi-market partial equilibrium model that integrates biological mechanisms with economic mechanisms. This system, which includes 11 categories of 953 kinds of agricultural products, could dynamical y project agricultural market supply and demand, assess food security, and conduct scenario analysis at different spatial levels, time scale levels, and macro-micro levels. Based on the CAMES, the production, consumption, and trade of the major agricultural products in China over the next decade are projected. The fol owing conclusions are drawn:i) The production of major agricultural products wil continue to grow steadily, mainly because of the increase in yield. i ) The growth of agricultural consumption wil be slightly higher than that of agricultural production. Meanwhile, a high self-sufifciency rate is expected for cereals such as rice, wheat, and maize, with the rate being stable at around 97%. i i) agricultural trade wil continue to thrive. The growth of soybean and milk im-ports wil slow down, but the growth of traditional agricultural exports such as vegetables and fruits is expected to continue.

关键词： agricultural outlook projection China agricultural Monitoring and Early-warning System(CAMES) agriculture of China

Price Transmission in China's Swine Industry with an Application of MCM

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Journal of Integrative Agriculture 2012年第12期11卷 2097-2106页

作者： XU Shi-wei LI Zhe-min CUI Li-guo DONG Xiao-xia KONG Fan-tao LI Gan-qiong agricultural information institute Chinese Academy of Agricultural Sciences (CAAS) Key Laboratory of Agri-information Service Technology Ministry of Agriculture

The paper studies the relationship, adjustment ability, path, efficiency and intensity of price transmission in the swine industry chain in China, which consists of the prices of corn, compound feed for fattening pig, piglet, pig and pork. Monthly prices covering a period of 18 yr （1994-2011） are analyzed using a Market-Chain Cooperated Model （MCM）. The empirical results show that there exists a stable long-term cointegration and short-term dynamic relationship in the price system. First, the adjustment speed of each price series is very slow and the transmission path is top-down and one-way significantly. Second, the price from upstream to downstream lags about 2 mort, while there is no lag in price transmission from midstream to downstream. Third, in terms of price transmission intensity, the price of pig impacted greatly on pork price, not only in the current period but also through the whole period. Besides, the price of corn has the largest lagged effects on pork price. According to the above empirical results, we suggest that government should strengthen monitoring and early warning of the swine industry chain, especially the upstream and midstream, attach great importance to the timely adjustment of feed prices and perfect the measures of price subsidy.

关键词： price transmission Market-Chain Cooperated Model swine industry chain

Soil Moisture Monitoring Based on Land Surface Temperature-Vegetation Index Space Derived from MODIS Data

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Pedosphere 2014年第4期24卷 450-460页

作者： ZHANG Feng ZHANG Li-Wen SHI Jing-Jing HUANG Jing-Feng institute of agricultural Remote Sensing and information Technology Zhejiang University

Soil moisture has been considered as one of the main indicators that are widely used in the fields of hydrology, climate, ecology and others. The land surface temperature-vegetation index （LST-VI） space has comprehensive information of the sensor from the visible to thermal infrared band and can well reflect the regional soil moisture conditions. In this study, 9 pairs of moderate-resolution imaging spectroradiometer （MODIS） products （MOD09A1 and MODllA2）, covering 5 provinces in Southwest China, were chosen to construct the LST-VI space, and then the spatial distribution of soil moisture in 5 provinces of Southwest China was monitored by the temperature vegetation dryness index （TVDI）. Three LST-VI spaces were constructed by normalized difference vegetation index （NDVI）, enhanced vegetation index （EVI）, and modified soil-adjusted vegetation index （MSAVI）, respectively. The correlations between the soil moisture data from 98 sites and the 3 TVDIs calculated by LST-NDVI, LST-EVI and LST-MSAVI, respectively, were analyzed. The results showed that TVDI was a useful parameter for soil surface moisture conditions. The TVDI calculated from the LST-EVI space （TVDIE） revealed a better correlation with soil moisture than those calculated from the LST-NDVI and LST-MSAVI spaces. From the different stages of the TVDIE space, it is concluded that TVDIE can effectively show the temporal and spatial differences of soil moisture, and is an effective approach to monitor soil moisture condition.

关键词： enhanced vegetation index modified soil-adjusted vegetation index normalized difference vegetation index temperature vegetation dryness indices

Is the “One Province One Rate” premium policy reasonable for Chinese crop insurance? The case in Jilin Province

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Journal of Integrative Agriculture 2018年第8期17卷 1900-1911页

作者： ZHOU Xian-hua LIAO Pu WANG Ke China institute for Actuarial Science Central University of Finance and Economics agricultural information institute Chinese Academy of Agricultural Sciences

Crop insurance in China is currently adopting the premium pricing strategy of "One Province One Rate", which appears to be in line with the systematic risk characteristics within crop insurance. This research aims to investigate the theoretical rationalization of this pricing strategy and its implications using the spatial lag model and the county-level data from the 45 corn plant counties of Jilin Province, China. Results corroborate that:(1) the spatial spillover effect of the corn yield risk is significant in Jilin but decreases rapidly when the risk unit includes more than eight counties; and(2) separating Jilin Province into eight risk zones for corn insurance will significantly reduce the high cross-subsidy phenomenon arising from the "One Province One Rate" strategy and shall benefit poor peasants in the region as well. This paper not only proves the existence of a systematic risk of crop insurance but also reveals that the spatial correlation and systemic features of the crop yield risk do not create a solid foundation for the current pricing strategy of "One Province One Rate". These conclusions will undoubtedly provide important references and empirical evidence for the role of China’s crop insurance in poverty alleviation.

关键词： crop insurance premium spatial correlation spatial lag model