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Assessing the sustainable development of agriculture is a hot topic in global agricultural research and an important task of rural revitalization and agricultural upgrading in the new era. Reform and opening up promote the rapid development of the agricultural economy, but the conflict between agricultural development and agricultural resources and ecological environment is serious. Since the 18th National Congress of the CPC, the sustainable development of agriculture has been given more prominence. It is of great significance to study the evaluation of agricultural sustainable development. Firstly, this paper studies the relevant literature on agricultural sustainable development evaluation at home and abroad. Based on wavelet transform, support vector machine(SVM), genetic algorithm (GA)and ant colony optimization(ACO) algorithm, a combination evaluation method of wavelet and intelligent optimization support vector machine is proposed. Secondly, by referring to the existing evaluation index system and combining with the actual situation of China's agricultural development, the alternative index set of agricultural sustainable development evaluation is established. Using SPSS software, the significance and correlation of 150 primary indexes are analyzed, and an evaluation index system including 62 indexes is established. Thirdly, using one-dimensional discrete stationary wavelet analysis, data denoising processing, genetic algorithm, ant colony algorithm, optimize the parameters of support vector machine, get better penalty parameters, kernel function, insensitivity coefficient, and then train the support vector machine. Fourth, taking 31 provinces (municipalities) in China as an example, this paper evaluates the agricultural sustainable development by applying the wavelet-GASVM model and the wavelet-ACOSVM model, and using the GA-SVM model and the ACO-SVM model to evaluate the agricultural sustainable development of 31 provinces (municipalities) in China. Fifthly, the reliability of the wavelet intelligent optimization SVM method is verified by changing the number of test sets and conducting multiple tests. The evaluation and simulation results show that: 1) The mean square error of agricultural sustainable development evaluation of Wavelte-GASVM is 9.641×10-5, and the correlation coefficient is 0.980; however, under the same training set and test set, the mean square error and correlation coefficient obtained by GASVM are 0.006 and 0.979, respectively. 2)The mean square error of Wavelet-ACOSVM agricultural sustainable development evaluation was 9.318×10-5, and the correlation coefficient was 0.972; the mean square error MSE and correlation coefficient of ACO-SVM are 0.016 and 0.953, respectively, under the same training set and test set. 3) Change the number of test sets and perform several tests and compare the results of GASVM model and ACO-SVM model before and after wavelet denoising respectively. It can be seen that under the GASVM model, the mean square error of the running results after wavelet denoising is smaller than that before wavelet denoising, and the correlation coefficient is larger than that before wavelet denoising, and the running time is shorter. Under the ACOSVM model, the mean square error of the running result after wavelet denoising is also smaller than that before wavelet denoising, and the correlation coefficient is larger than that before wavelet denoising, and the running time is shorter. Conclusion: The prediction accuracy and convergence speed of agricultural sustainable development evaluation by wavelet-GASVM and wavelet-ACOSVM are better than GA-SVM and ACO-SVM, respectively, and the effect of agricultural sustainable development evaluation by wavelet-GASVM is more ideal. This study provides a method reference for agricultural sustainable development assessment. [ABSTRACT FROM AUTHOR]

Agricultural machinery purchase subsidy is an important agrarian policy, its policy effect has been widely concerned by scholars. However, very few studies have discussed the spatiotemporal difference, agricultural machinery types difference and endogeneity of subsidy’s policy effect. The purpose of the present study is to make policy effect evaluation more accurately, and analyze the spatiotemporal difference and agricultural machinery types difference of policy effect. Different from existing studies, the present study uses a large sample collected from 15 089 observations in 3 287 households at 18 provinces from 2008 to 2018 by China agriculture research system (rapeseed) farmer fixed observation point and employs unbalance panel fixed effect model, panel high-dimensional fixed effects model, Box-Cox model, quantile regression model to calculate the differential policy effects between different year, topographic regions and types of agricultural machinery purchase subsidy on farmer’s agricultural machinery self-investment. In addition, instrumental variables fixed-effects panel-data models, Tobit fixed-effects panel-data models and Heckman sample selection models were used for the robust test. The result showed that 1) On the whole, agricultural machinery purchase subsidy had an obvious incentive effect, effectively promote farmer’s agricultural machinery self-investment, the marginal effect of agricultural machinery purchase subsidy on farmer’s agricultural machinery self-investment was 2.530 8. 2) The effect of subsidies varies significantly between plain and non-plain areas. Subsidy’s marginal effect in plain county was 1.408 5, subsidy’s marginal effect in hill and mountain county was 3.108 2. Subsidy policy was more effective in hill and mountain areas. 3) Generally, subsidy’s incentive effect fluctuated significantly between the years, crowding-out effect was showed in some years. The number of years in which the policy effect declined from the previous year was equal to the number of years in which it rosed from the previous year. 4) On the whole, the subsidy effect was enhanced with the increase of the value of agricultural machinery, and the policy effect was higher for large and medium-sized agricultural machinery. Accordingly, this paper suggested that: 1) In the future, agricultural machinery purchase subsidy should continue to implement. 2) Agricultural machinery purchase subsidy should tilt appropriately to non-plain areas and large and medium-sized agricultural machinery continually. Appropriate R&D subsidies can be given to agricultural machinery production enterprises to research and develop large and advanced machines and suit machines which used in hilly and mountainous areas. Encourage local governments to include large and advanced machines and machines which was suitable used in hilly and mountainous areas into the new agricultural machinery subsidy pilot catalogue timely. Accelerate the transformation and application for new machine products. 3) Adjust or improve the subsidy mode according to the implementation situation and agricultural mechanization development situation. [ABSTRACT FROM AUTHOR]

As the basic means of agricultural production, cultivated land plays an irreplaceable role in ensuring food security and promoting social and economic development. With the enhancement of urban interactions in space, the land use conflicts between urban development and agricultural protection have been intensified due to the diversified land demands caused by population agglomeration, industrial restructuring and infrastructure construction. Exploring the impacts of urbanization on cultivated land change has become a hot issue in China at present. Most of current studies have paid increasing attentions to the relationship between the growth of individual cities and cultivated land occupation, and few of them attempted to reveal the driving factors of cultivated land change from the perspective of spatial interaction of cities. Urban agglomeration is the main form of new urbanization in China. It is crucial to identify the distribution of cultivated land change and its driving factors from the perspective of urban agglomeration. In this paper, we measured the spatial connection of urban agglomerations based on the gravity equation and the urban flow intensity model, and then explored influencing factors of cultivated land conversion at the scales of individual cities and urban agglomerations during the period of 2005-2015 using a multilevel linear regression model. The research results show that the area of cultivated land in the major urban agglomerations has dropped sharply by 17 572.8 square kilometers in the decade from 2005 to 2015. The situation of cultivated land protection is grim. Then it shows significant scale effects and regional heterogeneity of cultivated land change in urban agglomerations. At the urban scale, the change of cultivated land is positively correlated with agricultural population, industrial economy and agricultural science & technology development, whereas negatively correlated with the growth of foreign investment and the expansion of construction land. At the scale of urban agglomeration, both indicators of spatial connection have a negative correlation with cultivated land change. Moreover, remarkable regional differences of influencing factors of cultivated land change exist between coastal and inland China. Comparing the regional differentiation of the degree of influence of outward functional forces, it can be found that the spatial interaction of coastal urban agglomerations has a more positive effect on the protection of cultivated land than the inland urban agglomerations with relatively backward development, and the negative impact is also smaller than that of inland urban agglomerations. The comparison with other models verified the effectiveness of the multilevel linear regression approach to reveal the influencing mechanism of cultivated land change on different scales. And the result of null model has proved the necessity and rationality in the research perspective of spatial interactions between cities. As a word, the strengthening of spatial interaction in urban agglomerations under rough development will obstruct the protection of cultivated land. In this case, controlling industrialization and urbanization reasonably, concerning the scale effects and regional heterogeneity, improving laws and regulations, correcting the rough development path, and improving land use efficiency might be the critical roads to relieve conflicts between development of urban agglomerations and protection of cultivated land. [ABSTRACT FROM AUTHOR]