Challenges and Solution for Identification of Plant Disease Using Machine Learning & IoT

Internet of Thing (IoT) is a groundbreaking technology that has been introduced in the field of agriculture to improve the quality and quantity of food production. As agriculture plays a vital role in feeding most of the world\u27s population, the increasing demand for food has led to a rise in food grain production. The identification of plant diseases is a critical task for farmers and agronomists as it enables them to take proactive measures to prevent the spread of diseases, protect crops, and maximize yields. Traditional methods of plant disease detection involve visual inspections by experts, which can be time-consuming and often subject to human error. However, with technological advancements, IoT and Machine Learning (ML) has emerged as promising solution for automating and improving plant disease identification. This paper explores the challenges and solutions for identifying plant diseases using IoT and ML. The challenges discussed include data collection, quality, scalability, and interpretability. The proposed solutions include using sensor networks, data pre-processing techniques, transfer learning, and explainable AI

Microbe-Based Strategy for Plant Nutrient Management

The rapid industrialization and urbanization of developing countries such as India have encroached on cultivable lands to meet the demands of an ever-increasing population. The altered land use patterns with increased fertilizer use has increased crop yields with leaching of major portion of the applied nutrients from the soil. Nitrates and phosphates are the agricultural pollutants that are discharged into aquifers due to anthropogenic reasons causing severe environmental and health problems. Production of these nutrients requires energy and finite resources (rock phosphate, which has gradually depleting reserves). An alternative management strategy would be to sequester excess nutrients within a biomass that is reused for agriculture. Two discrete enriched microbial consortia with the potential of simultaneous nitrate and phosphate sequestration upon application as biofertilizer restricted them within the plant root zone, ensuring prevention of eutrophication through leaching while making it available for uptake by plants. The nutrient accumulated biomass enhanced the crop yield by 21.88% during mung bean cultivation with maintained elemental content and other nutritional qualities. The major drawback of conventional biofertilizer application (slow release and action) could be overcome using this formulation leading to environmental protection, crop yield enhancement and soil fertility maintenance post-cultivation

Non-Hodgkin's lymphoma-associated pleural effusion misdiagnosed as tubercular pleural effusion

Adenosine deaminase (ADA) in the pleural fluid has high sensitivity and specificity for diagnosing tubercular pleuritis. ADA level of more than 40 IU/L in a lymphocytic and exudative effusion is suggestive of tubercular etiology in clinical practice. Antitubercular chemotherapy is often instituted without further histopathological or microbiological confirmation, especially in tuberculosis (TB)-endemic countries. Lymphoma is another important cause of elevated ADA levels in pleural fluid. Hence, in the absence of tissue diagnosis, lymphoma is often wrongly labeled as TB based on fluid characteristics. Here, we present a case of non-Hodgkin lymphoma with right-side pleural effusion who was initially misdiagnosed to have TB based on pleural fluid analysis

International Nosocomial Infection Control Consortiu (INICC) report, data summary of 43 countries for 2007-2012. Device-associated module

We report the results of an International Nosocomial Infection Control Consortium (INICC) surveillance study from January 2007-December 2012 in 503 intensive care units (ICUs) in Latin America, Asia, Africa, and Europe. During the 6-year study using the Centers for Disease Control and Prevention's (CDC) U.S. National Healthcare Safety Network (NHSN) definitions for device-associated health care–associated infection (DA-HAI), we collected prospective data from 605,310 patients hospitalized in the INICC's ICUs for an aggregate of 3,338,396 days. Although device utilization in the INICC's ICUs was similar to that reported from ICUs in the U.S. in the CDC's NHSN, rates of device-associated nosocomial infection were higher in the ICUs of the INICC hospitals: the pooled rate of central line–associated bloodstream infection in the INICC's ICUs, 4.9 per 1,000 central line days, is nearly 5-fold higher than the 0.9 per 1,000 central line days reported from comparable U.S. ICUs. The overall rate of ventilator-associated pneumonia was also higher (16.8 vs 1.1 per 1,000 ventilator days) as was the rate of catheter-associated urinary tract infection (5.5 vs 1.3 per 1,000 catheter days). Frequencies of resistance of Pseudomonas isolates to amikacin (42.8% vs 10%) and imipenem (42.4% vs 26.1%) and Klebsiella pneumoniae isolates to ceftazidime (71.2% vs 28.8%) and imipenem (19.6% vs 12.8%) were also higher in the INICC's ICUs compared with the ICUs of the CDC's NHSN