Under field conditions, various fungicide molecules were validated for their effectiveness on barley (Hordeum vulgare L.) stripe rust Puccinia striiformis f. sp. consecutively for three years under artificial field epiphytotic conditions. Seven fungicides viz., propiconazole 25%EC (tilt @ 0.1%), tebuconazole 25.9% m/m EC (folicur @ 0.1%), triademefon 25%WP (bayleton @ 0.1%), propiconazole 25%EC (tilt @ 0.05%), tebuconazole 25.9% m/m EC (folicur @ 0.05%), triademefon 25%WP (bayleton@ 0.05%), and mancozeb 75%WP (dithane M45 @ 0.2%) with various concentrations were tested for their effectiveness in controlling barley stripe rust severity. All fungicide applications resulted in lower disease severity and higher grain yields than untreated check plots. All the fungicides @ 0.1% concentrations reduced disease severity ranging from 87.8% to 95.6% except Mancozeb @ 0.2% (34.4%). Significant higher yield was obtained with Propiconazole @ 0.1% (26.7 q/ha) followed by Tebuconazole @ 0.1% (25.2 q/ha) and Triademefon @ 0.1% (24.5 q/ha). The present study revealed propiconazole as the most effective fungicide for the control of stripe rust of barley under epiphytotic conditions.
In recent years, as hospitals utilize the internet of medical things (IoMT) for medical applications, edge computing has played an important role in distant healthcare systems. Human life has gotten smarter in the era of pervasive computing, thanks to the newest breakthroughs in IoMT, wearable sensors, and communication technologies to give smart healthcare services. IoMT can completely transform the healthcare business. IoMT uses software and information and communication technology (ICT) to connect wearable sensors, patients, healthcare professionals, and carers. Patients are given extensive supportive information to help them get through their recoveries. In this chapter, the authors aim to propose an IoMT-based healthcare framework called prenatal healthcare system of remote mother and fetal surveillance through IoMT. The data collected through the IoMT devices will be transmitted to server and will be analyzed through AI/ML module. On the signal of any abnormality, the central system will alarm attending doctors about the individual mother and fetus to take necessary action.
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