ABSTRACT
The Internet of Things (IoT) has gained significance in agriculture, using remote sensing and machine learning to help farmers make high-precision management decisions. This technology can be applied in viticulture, making it possible to monitor disease occurrence and prevent them automatically. The study aims to achieve an intelligent grapevine disease detection method, using an IoT sensor network that collects environmental and plant-related data. The focus of this study is the identification of the main parameters which provide early information regarding the grapevine's health. An overview of the sensor network, architecture, and components is provided in this paper. The IoT sensors system is deployed in the experimental plots located within the plantations of the Research Station for Viticulture and Enology (SDV) in Murfatlar, Romania. Classical methods for disease identification are applied in the field as well, in order to compare them with the sensor data, thus improving the algorithm for grapevine disease identification. The data from the sensors are analyzed using Machine Learning (ML) algorithms and correlated with the results obtained using classical methods in order to identify and predict grapevine diseases. The results of the disease occurrence are presented along with the corresponding environmental parameters. The error of the classification system, which uses a feedforward neural network, is 0.05. This study will be continued with the results obtained from the IoT sensors tested in vineyards located in other regions.
ABSTRACT
Lonicera caerulaea L. and Aronia melanocarpa (Michx.) Elliot fruits are frequently used for their health benefits as they are rich in bioactive compounds. They are recognized as a source of natural and valuable phytonutrients, which makes them a superfood. L. caerulea presents antioxidant activity three to five times higher than other berries which are more commonly consumed, such as blackberries or strawberries. In addition, their ascorbic acid level is the highest among fruits. The species A. melanocarpa is considered one of the richest known sources of antioxidants, surpassing currants, cranberries, blueberries, elderberries, and gooseberries, and contains one of the highest amounts of sorbitol. The non-edible leaves of genus Aronia became more extensively analyzed as a byproduct or waste material due to their high polyphenol, flavonoid, and phenolic acid content, along with a small amount of anthocyanins, which are used as ingredients in nutraceuticals, herbal teas, bio-cosmetics, cosmeceuticals, food and by the pharmaceutical industry. These plants are a rich source of vitamins, tocopherols, folic acid, and carotenoids. However, they remain outside of mainstream fruit consumption, being well known only to a small audience. This review aims to shed light on L. caerulaea and A. melanocarpa and their bioactive compounds as healthy superfoods with antioxidant, anti-inflammatory, antitumor, antimicrobial, and anti-diabetic effects, and hepato-, cardio-, and neuro-protective potential. In this view, we hope to promote their cultivation and processing, increase their commercial availability, and also highlight the ability of these species to be used as potential nutraceutical sources, helpful for human health.
