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IoT-Based Intelligent System for Identification of Plant Stress in Sustainable Agriculture
| Content Provider | Scilit |
|---|---|
| Author | Mazumder, Debarshi Nandy, Sudarshan Chatterjee, Sudip |
| Copyright Year | 2019 |
| Description | Book Name: Emerging Trends in Disruptive Technology Management for Sustainable Development |
| Abstract | The increasing global population demands quality food while maintaining the food quantity and the environment. It is estimated that the global population will be approximately 9 billion by 2050 and hence food production should increase by 70 per cent [1]. In developed and underdeveloped countries, the demand for the food is completed from 2agriculture-based products. Sustainable agriculture has a remarkable prospect in the field of agricultural production to fulfil the food requirements of the global population by maintaining the environmental ecology. In sustainable agriculture, advanced technologies are incorporated to detect plant stress, which has a direct impact on the quality and quantity of the agriculture product [2]. The growth of a plant in an unsatisfactory environment may be the cause behind the plant stresses. The effects of stresses can lead to deficiencies in growth, permanent damage, or death of plant; this reduces the quality as well as the quantity of the food production [3]. Plant stress factors are generally divided into two sets: biotic (includes living biological factors such as fungi, bacteria, virus, insects, parasites, weeds, etc.) and abiotic (includes non-living environmental factors such as light, water, temperature, drought, flood, nutrient deficiency, and other environmental factors) [4,5]. In agriculture, environmental and biological factors play an important role in the growth, development, and productivity of the plant. Every plant gives good productivity if stress factors are within appropriate limits. Any unexpected changes in environmental and biological factors can cause deficiencies or damages in plant productivity and these changes may affect several parts of the plant, such as root, leaf, etc. [6]. It is observed that every biotic and abiotic stress consists of threshold values for the plant, and under this threshold value, good productivity can be expected [3,7]. These unexpected or critical changes in the environmental or biological factors can exceed the threshold levels and it is then the main cause behind the deficiencies in productivity [8]. Usually, the identification and monitoring of the plant stresses are done by farmers with the naked eye, but nowadays detection of plant stresses due to biotic factors is also done using an Internet of Things (IoT)-based intelligent system [9,10]. In this respect, IoT-based intelligent systems in sustainable agriculture is the most significant way to identify plant stresses as quickly as possible, and it is possible to decide correct and accurate amount of pesticide or another remedy [11–13]. |
| Related Links | https://content.taylorfrancis.com/books/download?dac=C2019-0-98438-5&isbn=9780429298288&doi=10.1201/9780429298288-1&format=pdf |
| DOI | 10.1201/9780429298288-1 |
| Language | English |
| Publisher | Informa UK Limited |
| Publisher Date | 2019-11-05 |
| Access Restriction | Open |
| Subject Keyword | Book Name: Emerging Trends in Disruptive Technology Management for Sustainable Development Identification Agriculture Threshold Food Production Detection of Plant Plant Stresses Iot Based Intelligent Detect Plant Stress |
| Content Type | Text |
| Resource Type | Chapter |
