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Summary: Endoplasmic reticulum (ER) bodies are ER‐derived structures that contain a large amount of PYK10 myrosinase, which hydrolyzes tryptophan (Trp)‐derived indole glucosinolates (IGs). Given the well‐described role of IGs in root–microbe interactions, we hypothesized that ER bodies in roots are important for interaction with soil‐borne microbes at the root–soil interface.We used mutants impaired in ER bodies (nai1), ER body‐resident myrosinases (pyk10bglu21), IG biosynthesis (myb34/51/122), and Trp specialized metabolism (cyp79b2b3) to profile their root microbiota community in natural soil, evaluate the impact of axenically collected root exudates on soil or synthetic microbial communities, and test their response to fungal endophytes in a mono‐association setup.Tested mutants exhibited altered bacterial and fungal communities in rhizoplane and endosphere, respectively. Natural soils and bacterial synthetic communities treated with mutant root exudates exhibited distinctive microbial profiles from those treated with wild‐type (WT) exudates. Most tested endophytes severely restricted the growth of cyp79b2b3, a part of which also impaired the growth of pyk10bglu21.Our results suggest that root ER bodies and their resident myrosinases modulate the profile of root‐secreted metabolites and thereby influence root–microbiota interactions. [ABSTRACT FROM AUTHOR]

In this paper we propose a smart irrigation system which is an advanced solution for weather monitoring that uses artificial intelligence and IoT. This system makes the irrigation system smart. With the increasing depletion of the underground water a smart irrigation system that will help farmer to irrigate his farm is designed. In this system depending on the weather conditions and the soil moisture content the smart system with the help of AI tries to decision whether the irrigation system will be switched on or not. The AI system will decide based on the input from sensors like temperature, humidity, moisture content of soil, light intensity which are connected over IoT. So this system makes decision making of the farmer easy. Each of the system is trained as per the requirement of the field over which the system is implemented, like tea garden, or paddy field or any organised farm. [ABSTRACT FROM AUTHOR]