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[前沿资讯 ] 当好维护国家粮食安全“压舱石” 争当农业现代化建设排头兵 进入全文
中国农网
的十八大以来，习近平总书记先后两次到黑龙江考察调研，为新形势下黑龙江振兴发展指明了方向。在党的二十大即将召开、实施“十四五”规划承上启下、乡村振兴全面展开之年，面对世纪疫情和百年变局，黑龙江牢牢把握当好维护国家粮食安全“压舱石”、争当农业现代化建设排头兵战略定位，在粮食生产、黑土地保护、种业科技等方面取得重大成就。近日，黑龙江省人民政府与大北农集团签订全面战略合作协议，未来十年，大北农集团开展“龙江十年千亿投资计划”，助推黑龙江打造生物硅谷，由此本报记者采访了国际农业教育科学院院士、联合国粮农组织全球土壤伙伴关系国际黑土研究院主席、黑龙江省农业科学院原院长韩贵清研究员，围绕黑龙江农业重要地位、现代农业发展成就和当前面临的机遇挑战以及未来在发展科技农业、绿色农业、质量农业、品牌农业等方面内容，全面解读黑龙江在维护好国家粮食安全“压舱石”、保障农产品供给安全“主力军”、国家粮食统筹调剂可靠“供应地”等方面发挥的重要作用，全景展示黑龙江加速推进农业高质量发展的振兴之路。
[会议论文 ] Automated Irrigation Management System using IoT 进入全文
IEEE
Agriculture spread to a great extent in the Indian economy above 60%, as the population is increasing, which also increases the need for modern technology for the increased production of crops. The Stereotyped methods of irrigation like sprinkler and inflow types are not much effective. As they out-turn in water loss and fungus-related issues because of overwatering. In the future, there may be a situation of demanding more water resources for agriculture. These circumstances can be avoided by using an Automated Irrigation System using IoT. IoT is a highly emerging technology that lets objects communicate through Internet, IoT has been used in a large set of applications like traffic management, smart cities, etc. The major application of IoT is a smart irrigation system, through this smart irrigation there is an advantage of the increase in crop production and decreased use of fertilizers. Using this smart irrigation, the condition of soil like humidity and moisture can be determined by fixing different sensors and these aspects increase the crop and this precise agriculture benefits the farmer. The data from the sensors is wirelessly transmitted to the server database. When the field's moisture and temperature are reduced, the irrigation will be automated. Periodically, the farmer receives information about the field's status by mobile.
[会议论文 ] Soil NPK Prediction Using Multiple Linear Regression 进入全文
IEEE
—Soil nutrients are the important parameter which contributes a major role in healthy plant growth. In soil, the presence of three macro nutrients namely Nitrogen (N), Phosphorus (P), and Potassium (K) are essential for proper crop growth. Without having adequate knowledge about nutrient levels present in soil, farmers apply large quantity of fertilizers in their field. This leads to depletion or enhancement of nutrient content in the soil and it degrades the soil fertility. Laboratory soil test is time consuming and it involves addition of many chemical reagents. Hence in this paper, the soil macronutrients are predicted using Multiple Linear Regression (MLR) technique. It is a statistical method where several independent or explanatory variables are used to predict the dependent or response variable. MLR technique is formulated to determine a mathematical relationship among several parameters. It shows the relationship between dependent and independent variables. In this technique, soil parameters like nitrogen, phosphorus, potassium, pH and electrical conductivity are used to sketch the relationship among these parameters and predict the values of NPK. The predicted NPK data shows an accuracy of approximately 80% when compared with the actual dataset. These results improve the decision-making capabilities of farmers in applying right quantity of fertilizers and increase crop production.
[学术文献 ] 不同改良材料对苏打盐碱化耕地甜菜叶片光合特性、干物质积累和分配的影响 进入全文
生态学杂志
针对苏打盐碱化耕地作物生长受抑制、产量低的生产现状，选取应用较广泛的3种改良材料——有机硅肥（SF）、腐植酸肥（HF）和微生物菌肥（MF），以不施用改良材料（CK）为对照，探讨不同改良材料对甜菜光合特性、干物质积累和分配的影响，以期筛选出适宜内蒙古西辽河平原区苏打盐碱化耕地的改良材料。结果表明：3种改良材料不同程度改善苏打盐碱化耕地甜菜光合特性。与对照相比，有机硅肥在全生育时期表现出显著调控效果，腐植酸肥在叶丛快速生长期后表现显著，微生物菌肥则在生育前期表现显著，有机硅肥调控效果显著优于腐植酸肥和微生物菌肥；与CK相比，处理SF净光合速率(Pn)、胞间CO2浓度(Ci)、蒸腾速率(Tr)、气孔导度(Gs)和叶片SPAD值分别提高10.32%～21.77%、9.08%～19.62%、23.14%～43.35%、17.44%～40.93%和23.15%～28.87%；处理HF分别提高5.63%～12.33%、2.37%～13.60%、4.22%～31.01%、14.65%～32.79%和7.93%～20.06%；处理MF分别提高3.82%～10.36%、4.51%～10.14%、1.46%～26.54%、6.72%～20.45%和5.54%～18.18%。3种改良材料通过对光合特性的调控，促进甜菜单株干物质积累，以有机硅肥效果优于腐植酸肥和微生物菌肥；与CK相比，处理SF、MF和HF甜菜单株干物质积累量全生育时期分别提高12.20%～58.06%、3.15%～13.06%和5.91%～20.96%。与对照相比，仅有机硅肥具有调节干物质在不同器官分配的显著效果，叶丛快速生长期促进干物质从叶片向叶柄转运，块根及糖分增长期后促进干物质由叶片、叶柄向块根转运；与CK相比，叶丛快速生长期至收获期，处理SF叶片干物质比例降低4.01%～17.43%、叶柄干物质比例降低7.40%～15.87%、块根干物质比例提高3.34%～5.01%，块根及糖分增长期后甜菜根冠比显著提高，提高幅度10.88%～23.34%。甜菜叶片光合特性指标、不同器官干物质分配比例与甜菜产量和含糖率之间均存在着显著（P<0.05）或极显著（P<0.01）相关关系，改良材料的施用可以通过调节光合特性、改善干物质积累和分配实现甜菜产质量的提升，其中以有机硅肥表现最优。
[会议论文 ] Smart Hydroponic System Using Fuzzy Logic control 进入全文
IEEE
Hydroponic plant plays a critical role in the agriculture field, which is put forward as a solution to combat climate change. The paper aims to provide automatic monitoring and controlling of hydroponic plants in the greenhouse via smartphones in real-time, to reduce the problems that appear in the greenhouse system and help the farmers in the agriculture process as they still do it manually. The paper will use the nutrient film technique (NFT), the nutrient solution is diluted with the water until getting the concentration for the cultivated plant, and then the excess solution is returned to the tank and watered the plant again. The proposed model will do activities such as measuring the temperature, humidity, and water level in the plant. The system design is based on fuzzy logic, the main objective of using fuzzy logic is to develop automated precise control of the fan and water pump. The proposed model hardware is an Arduino microcontroller, DHT11 sensor, PH sensor, LDR, esp8266 Wi-Fi module, MQ135, water level, fan with 5V, micro-DC water pump, and buzzer. The back end’s main functions are to control actuators, provide real-time notifications of the sensor values, and user authentication. The test result of the proposed model is displaying the status of the plant and doing an action, such as controlling fan levels, water pump, and determining the amount of PH needed for the plant. The paper will be organized as the following: first, the background, then related work that is based on the same idea, a proposed model that includes hardware, backend, user interface, and the fuzzy logic system, the paper will end with results of practical work and the conclusion of the paper.
[会议论文 ] An Optimized Soil Moisture Prediction Model for Smart Agriculture Using Gaussian Process Regression 进入全文
IEEE
An accurate soil moisture model is critical in the design and implementation of a smart agriculture system. Accurate soil moisture prediction allows an efficient water resources allocation. This paper presented a soil moisture model using different environmental parameters such as humidity, temperature, light intensity, and rain occurrence as inputs or predictor variables. Gaussian process regression algorithm, a non-parametric machine learning algorithm, was used to develop the model. The most effective kernel function was also determined by developing four different GPR models using a different kernel function. In terms of RMSE, the rational quadratic function obtained the lowest value. To further improve the accuracy of the GPR model, an automated hyperparameter tuning was done using a Bayesian optimization algorithm. Three hyperparameters were tuned using the Bayesian optimization algorithm, which improved the GPR model's performance. The optimized GPR model achieved the lowest RMSE and MAE of 3.596 and 1.176, respectively.
