A Critical Implementation Strategy of Various Diseases of Banana Plant based on Deficiencies of Minerals in the Soil

The period now occurring era, the agriculture scenarios generally contribute to 6.4% of the entire world's economic production. At least nine nations around the world have agriculture as their primary economic sector. As well giving billions of people access to fuel, agriculture also gives a lot of people job opportunities. This paper mainly focusses on identifying diseases of banana plant based on the deficiencies of minerals in the soil. First, we gathered the information about diverse categories of diseases occurs in banana plant such as Panama wilt, Mycosphaerella leaf spots, yellow sigatoka, black sigatoka etc… Also collected details of minerals in the soil. And categorized them into macro nutrients and micronutrients. We made the comparative analysis of minerals based on the types of soils. In this paper, we aim to researched about the diseases of banana plant

Internet of Things Applications in Precision Agriculture: A Review

The goal of this paper is to review the implementation of an Internet of Things (IoT)-based system in the precision agriculture sector. Each year, farmers suffer enormous losses as a result of insect infestations and a lack of equipment to manage the farm effectively. The selected article summarises the recommended systematic equipment and approach for implementing an IoT in smart farming. This review's purpose is to identify and discuss the significant devices, cloud platforms, communication protocols, and data processing methodologies. This review highlights an updated technology for agricultural smart management by revising every area, such as crop field data and application utilization. By customizing their technology spending decisions, agriculture stakeholders can better protect the environment and increase food production in a way that meets future global demand. Last but not least, the contribution of this research is that the use of IoT in the agricultural sector helps to improve sensing and monitoring of production, including farm resource usage, animal behavior, crop growth, and food processing. Also, it provides a better understanding of the individual agricultural circumstances, such as environmental and weather conditions, the growth of weeds, pests, and diseases

Morphological analysis for banana disease detection in close range hyperspectral remote sensing images

Early detection of banana disease can limit the spread of disease, as well as reduce the treatment costs. However, the disease symptoms are so unapparent in the earlier stage that makes the labeled samples acquisition difficult and expensive. Meanwhile, it is much easier to obtain labeled samples at the late stage where the disease symptoms are obvious. In this paper, we exploit machine learning methods to use labeled samples from the late stage to train the model, then detect the banana disease in the earlier stage. Morphological openings and closings are utilized to extract the spectral-spatial features from banana leaves at both earlier and late stages, initial experimental results demonstrate significant improvements over using only spectral information