Comprehensive Evaluation of Soil Moisture Sensing Technology Applications Based on Analytic Hierarchy Process and Delphi

Yu, Limin; Tao, Shiquan; Ren, Yuanhang; Gao, Wanlin; Liu, Xinliang; Hu, Yaozhong; Shamshiri, Redmond R.

doi:10.3390/agriculture11111116

Cited by 5 publications

(3 citation statements)

References 33 publications

(37 reference statements)

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“…The leaf area reduction allows the plants to reduce water loss by transpiration. This is a typical stress-avoidance mechanism adopted by plants to overcome water stress condition [39][40][41][42][43][44][45][46][47][48][49][50][51][52][53][54][55]. In the dahlias watered in a controlled way, the visual symptoms were related to plant adaptation to water deficiency, but stomatal conductance was higher than in the plants watered in the standard way.…”

Section: Discussionmentioning

confidence: 99%

Development of an Algorithm to Indicate the Right Moment of Plant Watering Using the Analysis of Plant Biomasses Based on Dahlia × hybrida

et al. 2022

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Water management in agriculture and horticulture has a strong ecological importance related to the necessity of optimizing the use of water resources. To achieve sustainable water use, it is necessary to optimize the time, frequency and the methods of water application. In this study, we hypothesized that the right moment for watering may be established on the grounds of the observation of the physiological state of the plant (if the plant is still in turgor) and the biomass of plant and the substrate. The proper irrigation scheduling, that is, just before the plant loses turgor, which appears at ca. 73% of LRWC in dahlias, determined with the use of the proposed measurement and computing system, makes it possible to save ca. 30% of irrigation water, in comparison to standard watering. Controlled watering also affected plant growth parameters, such as the content of chlorophyll a and b and carotenoid, as well as total and reducing sugar content (ca. 7%, 9% and 23% more than in plants watered in a standard way, respectively). Plants watered in a controlled way were 12% more compact when compared with the ones watered in a standard way. The results clearly proved that the computing system connected to scales made it possible to save water used for irrigation without a negative impact on the parameters of plant growth.

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Section: Discussionmentioning

confidence: 99%

Development of an Algorithm to Indicate the Right Moment of Plant Watering Using the Analysis of Plant Biomasses Based on Dahlia × hybrida

et al. 2022

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“…Precise soil moisture measurements can be obtained with the gravimetric method, using tensiometers, neutron gauges, gamma-ray attenuation, and time-domain Orchard monitoring provides a smartphone message to target the tree where irrigation problems were detected. reflectometry (TDR) [40]. Neutron probes, TDR, and gamma-ray sensors are highly accurate but extremely expensive.…”

Section: Soil Moisture Detectorsmentioning

confidence: 99%

WSN System Warns Producer When Micro-Sprinklers Fail in Fruit Trees

Schlam¹,

Solís²

2023

Nut Crops - New Insights

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Salts in the irrigation water cause micro-sprinklers to clog. Farmers find it difficult to detect sprinkler clog due to the great number of trees grown in commercial orchards, causing a reduction in yield and timing problems. In this article, IoT can support farmers with daily soil moisture detection. A wireless sensor network, WSN was developed to warn the farmer from micro-sprinkling clogging. Trees were gathered into groups of 9 trees, where the central tree holds the master microcontroller and the other eight trees presented slave microcontrollers (nodes). The system uses BLE (Bluetooth Low Energy) to communicate between the master microcontroller by BLE. A second WSN using lasers was also tested but resulted to be a little more expensive. Soil moisture sensor performance against corrosion and current consumption was analyzed being the best sensors the V1.2 capacitance probe and the sprinkler-encoder one. When micro-sprinklers did not apply water to a tree, its number was transmitted via LoRa from the master to the producer\'s smartphone to warn him/her. A hexacopter was used to detect canopy stress from a height of 30 m, but only after 7 days of water removal did the NDVI indexes detect it.

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“…In intelligent surveys, each planted area had various criteria and could be measured from both quantity and quality. Some critical Criteria for Smart Farming, such as nutrients [12], soil [13], pests [14], irrigation [15] etc., determine the ability and suitability of certain types of crops. In most situations, different criteria usually exist in one crop field, let alone for the same crop growing on all available land for agriculture; because it requires a specific analysis of the location needed to map the production of plant products effectively and efficiently [16].…”

Section: Introductionmentioning

confidence: 99%

A Systematic Review of Current Trends in Artificial Intelligence for Smart Farming to Enhance Crop Yield

Widianto

Ardimansyah²,

Pohan³

et al. 2022

Journal of Robotics and Control

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Current technology has been widely applied for development, one of which has an Artificial Intelligence (AI) applied to Smart Farming. AI can give special capabilities to be programmed as needed. In cooperation with agricultural systems, AI is part of improving the quality of agriculture. This technology is no stranger to being applied in basic fields such as agriculture. This smart technology is needed to increase crop yields for various regions by utilizing the current trends paper. This is necessary because less land is available for agriculture, and there is a greater need for food sources. Therefore, this systematic review aims to collect the current trends in AI studies for Smart Farming papers using the latest year features from 2018-2022. This paper is handy for researchers and industry in looking for the latest papers on research to enhance crop yields. The authors utilized Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) of 534 articles from IEEE, ACM, MDPI, IAES, and ScienceDirect. After going through a careful process, 67 papers were found that were judged according to the criteria. After the authors got some of the current trends, the author has discussed several factors regarding the results obtained to enhance crop yields, such as Weather, Soil, Irrigation, Unmanned Aerial Vehicle (UAV), Pest Control, Weed Control, and Disease Control.

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Comprehensive Evaluation of Soil Moisture Sensing Technology Applications Based on Analytic Hierarchy Process and Delphi

Cited by 5 publications

References 33 publications

Development of an Algorithm to Indicate the Right Moment of Plant Watering Using the Analysis of Plant Biomasses Based on Dahlia × hybrida

Development of an Algorithm to Indicate the Right Moment of Plant Watering Using the Analysis of Plant Biomasses Based on Dahlia × hybrida

WSN System Warns Producer When Micro-Sprinklers Fail in Fruit Trees

A Systematic Review of Current Trends in Artificial Intelligence for Smart Farming to Enhance Crop Yield

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