Daily Archives: October 2, 2024

Abstract-CRISPR-Cas technology has revolutionized the field of crop biotechnology, offering precise and efficient tools for enhancing the nutritional value of plants. This review highlights the current applications of CRISPR-Cas in biofortifying staple crops to combat global malnutrition. By editing specific genes, researchers have been able to increase essential nutrients such as vitamins, minerals, and proteins. However, challenges remain, including off-target effects, regulatory and biosafety concerns, and ethical considerations. Future directions point toward innovations in precision editing, multiplex gene editing for complex traits, and integration with synthetic biology and traditional breeding. Additionally, harmonizing global regulatory frameworks and ensuring equitable access to CRISPR technologies will be essential for realizing its potential to improve food security. This review underscores the transformative potential of CRISPR-Cas to address global nutritional deficiencies and enhance crop resilience in the face of climate change, ultimately contributing to a sustainable and food-secure future.

Abstract-This research aims to address critical challenges in agricultural sustainability by proposing a multifaceted approach to the detection and prediction of diseases affecting cotton plants. The objectives of this study are threefold. Firstly, the research focuses on the classification of cotton plant leaves, essential for accurate disease diagnosis. Through dataset analysis, normalization techniques, and feature extraction using Local Binary Patterns (LBP), cotton plant leaves are effectively differentiated from other foliage. Classification is accomplished utilizing Lightweight Convolutional Neural Networks (CNN), with performance parameters rigorously evaluated to ensure efficacy. Secondly, the study extends its scope to the classification of diseases affecting tomato plant leaves, offering insights into disease identification methodologies applicable to cotton plants. Leveraging the Coral Reef Optimization approach for feature extraction and a hybrid classifier comprising ResNet50 and VGG16 architectures, the system achieves precise disease classification. Lastly, the research addresses the critical need for predictive analytics in disease management by forecasting the occurrence of diseases in cotton plants. Utilizing historical time series weather data, machine learning and deep learning models, specifically Quantile Regression Forests coupled with Long Short-Term Memory (LSTM) algorithms, predict temperature and relative humidity parameters crucial for disease occurrence. By integrating these objectives, this study endeavors to provide a comprehensive framework for proactive disease management in cotton cultivation, thereby contributing to sustainable agricultural practices and food security.

Abstract-Late blight, caused by Phytophthora infestans, continues to pose a significant threat to potato production globally. While traditional breeding methods have been used to create resistant cultivars, these methods can be slow and often face limitations due to the availability of genetic resources. Marker-assisted selection (MAS) provides a more efficient and accurate approach by using molecular markers to identify plants that possess resistance genes. This review offers a thorough overview of MAS for late blight resistance in potatoes, discussing its historical development, genetic foundations, molecular markers, and the steps involved in its application. Key topics include the identification of resistance genes and their corresponding markers, the establishment of PCR conditions for marker amplification, and the combination of MAS with traditional breeding techniques. The review also addresses the challenges and future directions of MAS, emphasizing the importance of ongoing marker development, maintaining genetic diversity, and adapting to changing pathogens. In summary, MAS is a valuable tool for improving late blight resistance in potatoes. By integrating MAS with traditional breeding methods and tackling its challenges, breeders can create cultivars that are more resilient to this destructive disease, thereby supporting sustainable potato production.

Abstract-Bioethanol is generated by fermenting sugars obtained from biomass such as crops, agricultural waste, and organic refuse, and is a sustainable and eco-friendly energy option. It provides a long-term solution to fossil fuels, which has the capacity to decrease greenhouse gas emissions and combat climate change. Potato peel waste (PPW) is one of the many feedstocks that shows potential for bioethanol production because of its high starch content. PPW is a waste product from the potato processing sector, commonly thrown away or utilized for less valuable purposes. This study investigates the possibility of using PPW as a productive raw material for bioethanol manufacturing, specifically examining its preparation, breakdown, conversion, and purification stages. Even though bioethanol from PPW shows potential, economic and technical limitations arise due to high moisture levels, composition variability, and the requirement for substantial pre-treatment processes. However, the use of PPW for bioethanol production is in line with worldwide initiatives for sustainable energy, waste reduction, and the circular economy.

Abstract-India’s water sector is crucial for economic growth, public health, and environmental sustainability. With a population exceeding 1.4 billion, the water demand has risen sharply due to urbanisation, agriculture, and industrialization. However, the sector faces significant challenges, including water scarcity, pollution, and inadequate infrastructure. With 18% of the world’s population but only 4% of the world’s water sources, India grapples with water scarcity in many regions. India is the world’s largest user of groundwater that extracts more than any other country in the world and accounts for nearly 25 percent of the world’s extracted groundwater. With an estimated $250 billion investment requirement over the next 20 years, the Indian water sector offers immense opportunities for both domestic and international investors. This report highlights the structure of the water value chain in India, identifies investment opportunities, and names the key players and beneficiaries in the ecosystem.