Search
7 articles for “early blight”
-
Antifungal Potential of Plant Extracts against Alternaria solani, causing Early Blight of Tomato
Abstract: AbstractAqueous extracts of five plants with anti-microbial properties were evaluated for suppression of growth of Alternaria solani in laboratory conditions. At low concentration of 2%, four extracts including (Azadirachta indica) failed to suppress the growth. One extract (Putranjiva roxburghii) showed significant suppression of pathogen growth at low concentration, according to Analysis of variance, Tukey’s post-test. Some extracts (Melia azedarach and Tabernaemontana divaricata) on the contrary promoted the growth significantly more …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 7, Issue 1, 2018 · pp. 22–26 Read article
-
Transformative Breakthroughs: Revolutionizing Potato Disease Detection Through Machine Learning
Abstract: Advancements in agricultural technology and the integration of artificial intelligence for diagnosing plant and leaf diseases are crucial for sustainable agricultural development. Conditions like early blight and late blight exert a notable influence on both the quality and quantity of potato harvests. Identifying these leaf diseases manually demands significant labor and a considerable level of expertise. Therefore, efficient, and automated methods for disease detection are essential to improve potato production. …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 1, 2024 · pp. 54–62 Read article
-
Role of Fungicides in Food and Crop Health Security for Better Tomorrow
Abstract: AbstractFungicides are absolutely essential for prevention of plant diseases and improving crop yield, which is otherwise lost due to diseases. Their role has assumed importance where desirable host resistance against diseases is lacking. For many of the destructive diseases such as those caused by the members of oomycetes, against which effective host resistance is not available or when the host resistance is easily broken by new pathogen races, fungicides serve …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 2, Issue 1, 2013 · pp. 11–19 Read article
-
A Review of Automated Pomegranate Disease Detection and Classification Using Machine Learning
Abstract: The abstract outlines a research study focused on developing an automated system for detecting and classifying diseases that affect pomegranate fruits. Pomegranates, like many other crops, are vulnerable to several types of diseases that appear as visible colored spots on the fruit’s surface. These visible symptoms, such as lesions or discoloration, can significantly impact the fruit’s quality, market value, and yield. Therefore, timely and accurate identification of such diseases is …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 13, Issue 1, 2026 · pp. 01–13 Read article
-
Farmers’ Awareness of Bean Ascochyta Blight and Evaluation of Constraints of Bean Production in Rwanda.
Abstract: The awareness and perceptions of ascochyta blight by farmers is an important factor that affects the type of bean genotype adopted. Although farmers in Rwanda prefer large-seeded bean genotypes both for consumption and for market, these genotypes are susceptible to ascochyta blight. It was observed that farmers are abandoning large-seeded bean genotypes in preference for smaller seeded genotypes which seem to be more resistant. Therefore, the objective of this study …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 12, Issue 1, 2023 · pp. 16–29 Read article
-
Participatory Evaluation of Bean Ascochyta Blight [Phoma exigua var. diversispora (Bubak) Boerema] and Constraints of Bean Production in Rwanda
Abstract: AbstractThe awareness and perception of ascochyta blight by farmers is an important factor that affects the type of bean genotype adopted. Although farmers in Rwanda prefer large-seeded bean genotypes, both for consumption and for market, these genotypes are susceptible to ascochyta blight. It has been observed that farmers are abandoning large-seeded bean genotypes, in preference for smaller seeded genotypes, which seem to be more resistant. Therefore, the objective of this …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 6, Issue 2, 2017 · pp. 25–37 Read article
-
Crop Disease Prediction by Machine Learning
Abstract: The classification of Crop can be classified into several methods. The data set of crop leaf illnesses, notably Bacterial Leaf Blight disease (BLB), a crop leaf disease with significant outbreaks throughout Thailand, and Brown Spot Crop disease (BSR), is classified employing image classification in this study. Additionally, image processing technology is used for identifying different types of crop leaf disease. These algorithms include the Random Forest, Decision Tree, Gradient Boost, …
Published in Trends in Machine design · Vol. 11, Issue 2, 2024 · pp. 21–25 Read article