Performance of Autonomous Irrigation Unit via Mobile Application for Arugula Yield

Abstract

Due to the increase in water and energy tariffs, in addition to the limited amount of these resources, the automation of irrigation can help farmers to increase the production of agricultural crops. Therefore, the objective of this research was to evaluate different irrigation managements between manual and automatic in the production of arugula in a protected environment, in order to determine the productive potential in the cultivation of vegetables. The experiment was conducted in randomized blocks with four irrigation management strategies, divided into automatic and manual managements: automatic irrigation management via soil (IAS); automatic irrigation management via climate (IAC); manual irrigation management via soil (IMS) and manual irrigation management via climate (IMC). The treatments were applied to the arugula (Eruca Sativa L.) crop during two production cycles, and their effect on biophysical aspects of plants and irrigation water productivity was evaluated. For the fresh mass variable, the IAC (17.75 g plant -1 ), IAS (12.38 g plant -1 ), and IMC (8.63 g plant -1 ) treatments, in the 1 st cycle, were statistically similar to each other, whereas in the 2 nd cycle, only the IAC (16.29 g plant -1 ) and IAS (19.80 g plant -1 ) treatments had this statistical similarity. Automatic managements can be recommended based on this research, however, considering the financial difficulties of the small farmer, IMC may be a desirable option in unfavorable economic conditions.

An automatic classification grading of spinach seedlings water stress based on N-MobileNetXt

“…It is not accurate to judge water shortage by measuring the environmental information such as air temperature, air humidity and light intensity [10,11], or by manual inspection. Detecting soil moisture content by sensors directly has advantage in accuracy [12][13][14], while it is cumbersome in the process of deploying equipment and has strict requirement for terrain. Both of them are not the best methods for detecting soil water deficiency.…”