Crop leaf disease detection and classification using machine learning and deep learning algorithms by visual symptoms: a review

<span lang="EN-US">A Quick and precise crop leaf disease detection is important to increasing agricultural yield in a sustainable manner. We present a comprehensive overview of recent research in the field of crop leaf disease prediction using image processing (IP), machine learning (ML) and deep learning (DL) techniques in this paper. Using these techniques, crop leaf disease prediction made it possible to get notable accuracies. This article presents a survey of research papers that presented the various methodologies, analyzes them in terms of the dataset, number of images, number of classes, algorithms used, convolutional neural networks (CNN) models employed, and overall performance achieved. Then, suggestions are prepared on the most appropriate algorithms to deploy in standard, mobile/embedded systems, Drones, Robots and unmanned aerial vehicles (UAV). We discussed the performance measures used and listed some of the limitations and future works that requires to be focus on, to extend real time automated crop leaf disease detection system.</span>

Plant Nutrition under Climate Change and Soil Carbon Sequestration

The climate is one of the key elements impacting several cycles connected to soil and plant systems, as well as plant production, soil quality, and environmental quality. Due to heightened human activity, the rate of CO2 is rising in the atmosphere. Changing climatic conditions (such as temperature, CO2, and precipitation) influence plant nutrition in a range of ways, comprising mineralization, decomposition, leaching, and losing nutrients in the soil. Soil carbon sequestration plays an essential function—not only in climate change mitigation but also in plant nutrient accessibility and soil fertility. As a result, there is a significant interest globally in soil carbon capture from atmospheric CO2 and sequestration in the soil via plants. Adopting effective management methods and increasing soil carbon inputs over outputs will consequently play a crucial role in soil carbon sequestration (SCseq) and plant nutrition. As a result, boosting agricultural yield is necessary for food security, notoriously in developing countries. Several unanswered problems remain regarding climate change and its impacts on plant nutrition and global food output, which will be elucidated over time. This review provides several remarkable pieces of information about the influence of changing climatic variables on plant nutrients (availability and uptake). Additionally, it addresses the effect of soil carbon sequestration, as one of climate change mitigations, on plant nutrition and how relevant management practices can positively influence this.

Agrotech: Advanced Field Control

Agriculture in most countries is largely dependent on the environmental conditions and climate. Real-time remote monitoring of field conditions allows for early detection of unfavorable conditions developing in the field that is generally a laborious task taken up by the farmers themselves. Additionally, with the rapid shift in climatic conditions and issues pertaining to global warming, the rainfall dependent agricultural yield is promptly affected. In this paper, we present a wireless system using nRF24L01 RF modules to monitor the farm environment conditions and operate the final control element aimed at implementing drip irrigation. The proposed system is designed to be economical and having a capacity for further expansion, allowing the widespread devices across the farm to be controlled. The soil sogginess level is measured by a self-made soil moisture sensor. A ball valve is actuated based on the levels of soil moisture, temperature and humidity checked against a set of predefined levels. The collected data is then pushed onto a cloud platform for future study or use. Keywords: Wireless sensor network, real-time monitoring, nRF24L01 RF module, highly economical and efficient system

A Review on Agriculture Crop Prediction Techniques Using Machine Learning

Machine learning is a useful decision-making tool for predicting crop yields, as well as for deciding what crops to plant and what to do during the crop's growth season. To aid agricultural yield prediction studies, a number of machine learning techniques have been used. We employed a Systematic Literature Review (SLR) to extract and synthesize the algorithms and features used in crop production prediction research in this investigation This paper provides a comprehensive overview of the most recent machine learning applications in agriculture, with a focus on pre-harvesting, harvesting, and post-harvesting issues The papers have been studied in depth, analysed the methodology and features employed, and made recommendations for future study. Temperature, rainfall, and soil type are the most commonly utilised features, according to our data, while Artificial Neural Networks are the most commonly employed method in these models.

Detection of pesticides in environmental and food matrix: A review

The Pesticides are widely used as the key to increase the agricultural yield in the world. Pesticides are used incautiously and in uncontrolled manner to compensate shortage of food due to ever increase in population and rapid urbanization. Because of this, concentration of pesticides in environment and food matrix is increased which causes difficulties in maintaining healthy lifestyle and becomes a root cause of multiple diseases. Hence, strict rules and regulations are made which are followed by government and are bound to regularly monitor these compounds. With time, numerous traditional to conventional methods are developed for extraction and detection of these compounds from environmental and food matrix. The present study explains overview of all-inclusive traditional to advanced methods for pre-treatment and detection of pesticides with its residues from environmental and food matrix. Also discussed about comparisons between these methods with applicability, advantages and disadvantages over one another.

Protective forest plantations and treatment methods influence on agrophysical properties of chestnut soil and agricultural yield

The article presents the results of many years research on the complex effect of basic tillage and shelterbelts methods on the content of macroelements in the soil, the conditions of water supply and the formation of the spring barley yield on zonal light-chestnut soils.

Identification of plant diseases and distinct approaches for their management

Background Globally in the agricultural industry the major loss faced by is due to plant diseases. Various pathogens are responsible for causing plant bacterial and viral diseases, the treatment of them is very important in order to bring out the best quality and quantity of the agricultural yield. Before Technology came into practice the plant disease were identified by visual examination, the main symptoms such as curling of leaves and change of colour were observed. With advancements in science the microscopic examination for more clarity regarding diseases came into existence. Main body The distinct methods involve use of nucleic acids and serological assays were implemented to study bacterial and viral characteristics of the infecting pathogen. Traditionally, seed coating and mulching techniques were more common among farmers to generate better quality of the crops and prevent plants from any disease but currently new innovative methods are used. Microbial bio control agents are now one of the widely used approach in which microbial species are used to eliminate or inhibit the growth of pathogens in order to reduce the severity of the infection. Similarly, like microbial agent’s different chemicals are present in order to kill the pathogens. These chemicals are classified as bactericides, fungicides and nematicides which suppress the plant infection caused by bacteria, fungal and nematodes, respectively. Conclusions In the forthcoming years, the development of more innovative agricultural-related techniques is prime that will help in increase of the yield and provides resistance to plants. Some of them are developed earlier but there is still need to develop more pathogen-resistant species for example in case of silencing of genes with insertion of a viral segment.