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[会议论文 ] Crop Suitability Prediction Model for Malaysian Crop Diversification 进入全文
IEEE
Crop diversity is one of the important perspectives to be observed in agriculture. The crop diversity is significant for production stability as well as nutrition security. However, the crop diversity in Malaysia is inadequate as the agricultural activities are devoted to oil crop plantation. Therefore, this research aims to discover the suitable new tropical crops to be cultivatable in Malaysia for crop diversification. FAOSTAT was selected as data source, while Decision Tree, Random Forest and Artificial Neural Network were chosen for predictive model training. The Random Forest is having the highest accuracy among the modelling techniques. Therefore, Random Forest models were chosen as crop suitability predictive models to discover the suitable crop with Malaysian environmental data as input. There are nine tropical crops subjected to investigation. The crops are dates, sorghum, yams, avocados, kola nuts, chickpeas, lentils, sisal and fonio. Dates, sorghum, yams, avocados and kola nuts were predicted to be not suitable to the Malaysian environment. Whereas chickpeas, lentils, sisal and fonio were predicted to be cultivatable with the Malaysian environment. Unlike other crop diversification research that done on other countries, which are soybean cultivation in Europe, red kidney bean in Iraqi and Cassava in Thailand. This research investigated the potential of nine tropical crops besides soybean, red kidney bean and cassava. At the same time, the crop suitability was predicted with respect to Malaysian environment. Future works are suggested to investigate the procedure of new crop cultivation and the tactic to release the crop to the market.
[前沿资讯 ] 解锁黑土地上的丰产“密码”——吉林省大力推进高标准农田建设 进入全文
中国农网
耕地是粮食生产的命根子，要“牢牢把饭碗端在自己的手里”，要做好高标准农田改造这篇农业“大文章”，这是吉林省近几年来在推进现代农业发展中，一步一个脚印蹚出来的“实路子”。要把昔日的低产田,变成如今的“生态田”“高产田” 和“米袋子”。在吉林省大安市中科佰澳格霖农业土地整治现场，百余台大型机械齐上阵，一派热火朝天的施工景象。自接到复工指令后，迅速调运设备及人员，抢时间、赶进度，每天施工10个小时以上，表土剥离、土地平整、斗渠、毛渠等各项工程正在有序推进中。站在改造的田地边，望着面前正在平整土地、盐碱地改良的田野，附近的村民满怀希望。这让人们昔日望眼欲穿的“薄地”、靠天吃饭的“望天田”在不久后就将变成带领村民致富增收的“希望田”。
[会议论文 ] Wheat Crop Field and Yield Prediction using Remote Sensing and Machine Learning 进入全文
IEEE
Agriculture plays an important role in the growth of a country's economy. Crop area and yield predictions using machine learning are important investigation domains in current research fields. Wheat is the most important food crop in Pakistan which is cultivated in the Rabi season. Weather conditions, Remote Sensing (RS) data, and Machine learning (ML) technologies can be used to forecast wheat yield before actual harvesting to assist the management of wheat production, trade, and storage. In this paper, a supervised ML based framework is proposed that extracts features/Vegetation Indices (VIs) including Enhanced Vegetation Index (EVI), Normalized Difference Vegetation Index (NDVI), Red Edge Normalized Difference Vegetation Index (RENDVI), and Normalized Difference Moisture Index (NDMI) from Sentinel-2 Satellite images and contributes for: estimation of wheat area, and identification of most effective VIs in wheat area estimation, prediction of wheat yield, and identification of most effective VIs and meteorological parameters in wheat yield prediction. In the initial experimental setup, good performance output obtained using the Random Forest (RF) machine learning algorithm therefore in this framework RF machine learning algorithm is focused on wheat area estimation and generation of Land Use Land Cover (LULC) maps which is capable of estimating area with an accuracy of 84%, consumer's accuracy of 81 %, producer's accuracy of 83% and kappa statistics of 0.80. LULC maps are used for wheat yield prediction. Multivariate regression forward stepwise technique is applied for yield prediction and selection of effective VIs and meteorological parameters. The adjusted coefficient of determination (R2) between reported and predicted yield found 0.84 with an error of 46.14 Kg/ha for yield prediction.
[前沿资讯 ] 土地确权：承包地有了“身份证” 进入全文
农民日报
党的十八大以来，中国特色社会主义进入新时代。以习近平同志为核心的党中央统筹国内国际两个大局，推动党和国家事业取得历史性成就、发生历史性变革，中华民族伟大复兴进入不可逆转的历史进程。即日起，本报在“奋进新征程 建功新时代”栏目下开设“伟大变革”子栏目，从三农领域的变革性实践、突破性进展、标志性成果入手，回顾梳理党的十八大以来中央推进三农工作的战略考量、决策过程，通过三农领域的巨大变化反映党领导人民攻坚克难、推进变革的生动实践，展现人民踔厉奋发、笃行不怠的精神风貌。
[前沿资讯 ] 北大荒共青农场木本泥碳改良土壤效果明显 进入全文
中国农网
北大荒集团共青农场有限公司种养结合优化黑土地内在环境，使用了木本泥碳和土壤改良剂使耕地土壤有机质含量，作物产量和品质大幅提升。共青农场有限公司河北庄管理区种植户代淑清承包耕地180亩，2021年她在农场有限公司帮助下，与中国科学院南京土壤研究所进行为期三年的合作试验，通过以秸秆还田施入泥碳、有机肥施入泥碳、秸秆离田施入泥碳和常规种植施入泥碳等七种办法，不仅让她家耕地土壤有机质含量从2020年的26.32克提升至2021年的28.56克，同时也提高了作物产量，增加了经济效益。
[前沿资讯 ] 左右江革命老区——红土地上谋振兴 乡村处处换新颜 进入全文
农民日报
近年来，广西崇左市龙州县上龙乡充分挖掘红色旅游资源，着力打造“红军村”红色教育精品，经过多年的发展，乡村风貌焕然一新。眼下正值左右江畔桂芒挂果时。左右江革命老区广西百色市，如今已是全国最大的芒果生产基地，2021年全市芒果产量约占全国总量的24％，年产值超过50亿元，10余万农户从中受益。“高铁通过村，产业路修到家。”田东县林逢镇东养村党总支书记、村委会主任陆秀缎说，凭借气候、土壤等自然资源优势，当地将芒果打造成巩固拓展脱贫攻坚成果、实施乡村振兴战略的支柱产业之一。包括百色在内的左右江革命根据地，曾在中国革命战争史上留下浓墨重彩的一笔。2015年《左右江革命老区振兴规划》获得批复，2020年底，左右江革命老区230.3万建档立卡贫困人口全部脱贫，28个贫困县全部摘帽。党的十八大以来，老区各族人民赓续红色精神踔厉笃行，立足独特区位优势，围绕林果蔬畜糖等特色资源，打造出一批特色农业产业集群，持续推动脱贫安边、致富守边，昂首阔步迈向振兴新发展。
