集成cropiify -作物和肥料推荐系统与叶片病害预测

K. Devi Priya, A. S. Samyogitha, A. K. Krishna Reddy, B. Divya Sri
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引用次数: 1

摘要

在印度,务农是最受欢迎的职业。它对印度经济产生了重大影响,并为印度人提供了大量的就业前景。如今,农民并不会针对每种土壤类型选择最好的作物。农业产量受到直接影响。该地区的农民因此遭受了严重的经济损失。现在,在特定类型的土壤上种植特定类型的作物需要考虑很多因素。在选择最佳作物种植时,要考虑许多土壤变量。这种创新的意见挖掘方法将考虑土壤含水量、压力和温度等因素。为了估计理想的产量,这个预测模型实际上会使用机器学习算法。根据土壤湿度、pH值、温度和与作物有关的环境条件,还将建议最佳肥料。利用这一创新的肥料推荐系统,将建议最佳肥料,以获得最佳收成。这个应用程序使用深度神经网络来预测叶片疾病。为了确定系统中的叶片图像是否含有病害,正在对测试集进行检查。如果叶子没有任何疾病,就说它是正常的。否则,叶片被感染,并及时建议作物病害治疗。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
ENSEMBLED CROPIFY – Crop & Fertilizer Recommender System with Leaf Disease Prediction
In India, farming is the most popular occupation. It has a significant impact on the Indian economy and offers plenty of employment prospects to Indians. Nowadays, farmers do not choose the best crop for each soil type. The yields from agriculture are directly impacted. Farmers in the area are suffering severe financial losses as a result. There are now a lot of considerations to consider while cultivating a specific sort of crop on a specific type of soil. Numerous soil variables are considered to choose the best crop to grow. This innovative opinion mining approach will take factors like soil moisture content, pressure, and temperature. To estimate the ideal crop, this prediction model would in fact use machine learning algorithms. The optimal fertilizer will also be suggested based on the soil moisture levels, pH value, temperature, and crop-related environmental circumstances. The best fertilizer will be suggested using this innovative system for fertilizer recommendations in order to produce the best harvests. This application uses deep neural networks to forecast leaf disease. To determine whether leaf image in the system contains diseases, the test set is being examined. If leaf does not have any disease it is said to be normal. Otherwise, the leaf is infected, and crop disease treatment is promptly advised.
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