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Improving Irrigation Management Practices for Agricultural Production

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A special issue of Agronomy (ISSN 2073-4395). This special issue belongs to the section "Water Use and Irrigation".

Deadline for manuscript submissions: 20 May 2024 | Viewed by 8528

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Special Issue Editors

Dr. Lili Zhangzhong

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Guest Editor

National Engineering Research Center for Intelligent Equipment in Agriculture, Beijing 100097, China
Interests: agricultural irrigation

Dr. Wengang Zheng

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Guest Editor

National Engineering Research Center for Intelligent Equipment in Agriculture, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China
Interests: smart irrigation

Dr. Linlin Xu

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Guest Editor

1. School of Land Science and Technology, China University of Geosciences, Beijing 100083, China
2. Department of Systems Design Engineering, University of Waterloo, Waterloo, ON N2L 3G1, Canada
Interests: spatial statistics; satellite remote sensing; hyperspectral imaging; computational geography; deep learning; machine learning

Special Issue Information

Dear Colleagues,

The escalation of the global population is leading to rising demand for food production.

Concurrently, facing the problem of an excessive shortage of water resources, the highly water-consuming farmland irrigation industry needs to further improve the water-use efficiency of agricultural production and ensure food security.

How to achieve efficient irrigation is a major challenge faced by the agricultural community. In order to cope with this challenge, an improvement in irrigation technology/method/mode or management is required, such as improving the management and control strategy with new technologies.

In this Special Issue, we aim to exchange knowledge on any aspect related to irrigation management practices for agricultural production, thus promoting the improvement of efficient irrigation technology and improving the water-use efficiency of agricultural production on the premise of ensuring crop yield.

Dr. Lili Zhangzhong
Dr. Wengang Zheng
Dr. Linlin Xu
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Agronomy is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

new irrigation method
agronomy
drought
yield
water-use efficiency
smart irrigation
irrigation scheduling
model predictive control
precision agriculture

Published Papers (7 papers)

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Research

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13 pages, 1415 KiB

Open AccessArticle

Evaluation of AquaCrop’s Ability to Simulate Water Stress Based on 2-Year Case Study of Maize Crop

by Ding Zhou, Hui Wang, Xiangxiang Wang, Fangfang Wang, Jiabao Zhang and Donghao Ma

Agronomy 2024, 14(2), 354; https://doi.org/10.3390/agronomy14020354 - 09 Feb 2024

Viewed by 909

Abstract

To apply AquaCrop to the study of agricultural soil moisture in the North China Plain, a water-treatment experiment on summer maize was carried out at the Fengqiu experimental station of the Chinese Academy of Sciences from 2017 to 2018. A water treatment was used to achieve field water capacities of 20 (W1), 40 (W2), and 60 (W3) cm soil layers under irrigation, and a rain-fed treatment (W0) was added. The model parameters were calibrated using the measured data in 2017. Then, they were applied to 2018 to verify the ability of the model to simulate water stress. The results showed that the variation trends for crop yield, canopy coverage, total soil water content, and the curve in the growth cycle simulated via AquaCrop were consistent with the actual observations; the results of a discrete analysis showed that the values of b (regression coefficient), R² (determination coefficient), and EF (efficiency) were close to 1, and the values of the RMSE (root mean square error) were close to 0, which proved that the model could simulate dynamic changes in summer maize yield, canopy coverage, and total soil water content well. AquaCrop had good applicability in the North China Plain and could be applied to the study of agricultural water consumption and water-use efficiency in this area. The simulated values obtained can serve as an easily obtainable source of long-term experimental data in areas with frequent non-extreme weather events. Full article

(This article belongs to the Special Issue Improving Irrigation Management Practices for Agricultural Production)

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19 pages, 2583 KiB

Open AccessArticle

Improving Irrigation Performance by Using Adaptive Border Irrigation System

by Kaihua Liu, Xiyun Jiao, Weihua Guo, Zhe Gu and Jiang Li

Agronomy 2023, 13(12), 2907; https://doi.org/10.3390/agronomy13122907 - 27 Nov 2023

Viewed by 599

Abstract

Shortages of water resources and labor make it urgent to improve irrigation efficiency and automation. To respond to this need, this study demonstrates the development of an adaptive border irrigation system. The inflow is adjusted based on the functional relationship between the advance time deviation and the optimal adjustment inflow rate, thereby avoiding the real-time calculation of infiltration parameters required by traditional real-time control irrigation systems. During the irrigation process, the inflow rate is automatically adjusted based only on the advance time deviation of the observation points. The proposed system greatly simplifies the calculation and reduces the requirements for field computing equipment compared with traditional real-time control irrigation systems. Field validation experiments show that the proposed system provides high-quality irrigation by improving the application efficiency, distribution uniformity, and comprehensive irrigation performance by 11.3%, 10.7%, and 11.0%, respectively. A sensitivity analysis indicates that the proposed system maintains a satisfactory irrigation performance for all scenarios of variations in natural parameters, flow rates, and border length. Due to its satisfactory irrigation performance, robustness, facile operation, and economical merit compared with traditional real-time control irrigation systems, the proposed system has the potential to be widely applied. Full article

(This article belongs to the Special Issue Improving Irrigation Management Practices for Agricultural Production)

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17 pages, 4189 KiB

Open AccessArticle

Using Soil Water Status Sensors to Optimize Water and Nutrient Use in Melon under Semi-Arid Conditions

by Susana Zapata-García, Abdelmalek Temnani, Pablo Berríos, Pedro J. Espinosa, Claudia Monllor and Alejandro Pérez-Pastor

Agronomy 2023, 13(10), 2652; https://doi.org/10.3390/agronomy13102652 - 22 Oct 2023

Viewed by 929

Abstract

Nowadays, agriculture must satisfy the growing demand for food, and increasing its sustainability, from an environmental, economic, and social point of view, is the only way to achieve this. The objective of this study was to increase the water and nutrient use efficiency of a melon crop during two consecutive seasons under commercial conditions, growing under semi-arid area. For this purpose, two treatments were studied: (i) a farmer treatment (FRM), fertigated at ~100% of crop evapotranspiration (ET_c) during the whole growing season; and (ii) a precision irrigation treatment (PI), irrigated by adjusting, between flowering and ripening, the weekly farmer irrigation to minimize the leaching below the root system. The threshold for allowable soil water depletion in the active root uptake zone was set at 20–30%. The cumulative water savings in each year relative to the FRM treatment ranged between 30 and 27% for 2020 and 2021, respectively. Yield was not negatively affected, with no differences in fruit load (fruit per m) or fruit weight (kg) between irrigation treatments, although higher yields were obtained in the second year due to seasonal changes. The crop water status indicators evaluated (stem water potential, net photosynthesis, and stomatal conductance) were not affected by the irrigation treatments. Water and nitrogen productivity, on average, increased by 45.5 and 54.4% during the experimental period, respectively; the average PI ascorbic acid content increased by 33.4%. Full article

(This article belongs to the Special Issue Improving Irrigation Management Practices for Agricultural Production)

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16 pages, 5170 KiB

Open AccessArticle

The Study of Structural Optimization on Hydraulic Performance and Anti-Clogging Performance of Labyrinth Drip Irrigation Emitters

by Tianyu Xu, Sanlin Bao, Zonglei Li, Qiuyue Yu and Ennan Zheng

Agronomy 2023, 13(10), 2496; https://doi.org/10.3390/agronomy13102496 - 27 Sep 2023

Viewed by 768

Abstract

The core component of a properly functioning drip irrigation system is the drip irrigation emitter. Irrigation water containing impurities and sand particles can easily lead to clogging of the drip irrigation emitter, reducing the efficiency of the drip irrigation system. In this paper, orthogonal tests were used to optimize the flow channel structure, combined with the computational fluid dynamics–discrete element method (CFD-DEM) to analyze the flow index and sand particle motion characteristics. Clear water tests and short-cycle anticlogging tests were used to validate the results of the numerical simulation, and the relationship between the hydraulic performance and anti-clogging performance was revealed via linear regression. The results showed that the structural parameters of drip irrigation emitters were important factors affecting the flow index and sand movement characteristics. The order from largest to smallest was the turning angle, amount of interdental reference, flow channel depth, flow channel width, and width of the top base. The sand passage rate and the percentage decrease in velocity can be used as important indicators of anti-clogging performance, and there was a negative correlation between the two indicators. The flow channel with a 65° turning angle had the lowest flow index, and the sand passage rate can reach up to 91.48%; the reason was that the main flow region velocity was higher, the vortex region and the sand energy loss were small, which was not easy to clog. The equation for the relationship between flow index and sand passage rate was a negative correlation for drip irrigation emitters between a 65° and 75° turning angle. The drip irrigation emitter with a 65° turning angle had better hydraulic performance and anti-clogging performance. Full article

(This article belongs to the Special Issue Improving Irrigation Management Practices for Agricultural Production)

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18 pages, 4021 KiB

Open AccessArticle

A Hybrid Prediction Model for CatBoost Tomato Transpiration Rate Based on Feature Extraction

by Zhaoyang Tong, Shirui Zhang, Jingxin Yu, Xiaolong Zhang, Baijuan Wang and Wengang Zheng

Agronomy 2023, 13(9), 2371; https://doi.org/10.3390/agronomy13092371 - 12 Sep 2023

Cited by 1 | Viewed by 906

Abstract

The growth and yield of crops are highly dependent on irrigation. Implementing irrigation plans that are tailored to the specific water requirements of crops can enhance crop yield and improve the quality of tomatoes. The mastery and prediction of transpiration rate (T_r) is of great significance for greenhouse crop water management. However, due to the influence of multiple environmental factors and the mutual coupling between environmental factors, it is challenging to construct accurate prediction models. This study focuses on greenhouse tomatoes and proposes a data-driven model configuration based on the Competitive adaptive reweighted sampling (CARS) algorithm, using greenhouse environmental sensors that collect six parameters, such as air temperature, relative humidity, solar radiation, substrate temperature, light intensity, and CO₂ concentration. In response to the differences in crop transpiration changes at different growth stages and time stages, the t-Distributed Stochastic Neighbor Embedding (t-SNE) algorithm was used to identify three characteristic intervals: florescence stage, fruiting stage daytime, and fruiting stage night-time. Based on this, a greenhouse tomato T_r prediction model (CARS-CatBoost model) based on the CatBoost machine learning algorithm was constructed. The experimental verification shows that the coefficient of determination (R²) of the constructed CARS-CatBoost single model for the whole growth stage is 0.92, which is higher than the prediction accuracy of the traditional single crop coefficient model (R² = 0.54). Among them, the prediction accuracy at night during the fruiting stage is the highest, and the Root Mean Square Error (RMSE) drops to 0.427 g·m⁻²·h⁻¹. This study provides an intelligent prediction method based on the zonal modeling of crop growth characteristics, which can be used to support precise irrigation regulation of greenhouse tomatoes. Full article

(This article belongs to the Special Issue Improving Irrigation Management Practices for Agricultural Production)

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21 pages, 7237 KiB

Open AccessArticle

Ensemble Learning Simulation Method for Hydraulic Characteristic Parameters of Emitters Driven by Limited Data

by Jingxin Yu, Lili Zhangzhong, Renping Lan, Xin Zhang, Linlin Xu and Jingjing Li

Agronomy 2023, 13(4), 986; https://doi.org/10.3390/agronomy13040986 - 27 Mar 2023

Cited by 2 | Viewed by 1160

Abstract

The emitter is one of the most critical components in drip irrigation. The flow path geometry parameters have a significant effect on the emitter’s hydraulic performance and have a direct impact on the emitter’s irrigation uniformity and lifetime. The hydraulic characteristics of the emitter are the key indicators of its performance. However, obtaining the hydraulic characteristics of the emitter is complex. Typically, only a small number of calibrations are performed for specific equipment models, making it difficult to obtain the parameter. Therefore, limited data corresponding to the morphological parameters and the flow rate were simulated using the FLUENT software, and the influence of the characteristics was analyzeanalyzed, based on which a flow rate prediction model was constructed using the ensemble learning (CatBoost) model. The extended data set was generated by stochastic simulation and parameter fitting. The flow index and flow coefficient prediction model were built and evaluated using the CatBoost model again with the augmented data set as a benchmark. The results show that the significant correlation between the geometric structure and the flow index and flow coefficient provides the basis for the correlation model. CatBoost can fit the complex nonlinear relationships between the parameters well, achieving excellent simulation accuracy for the flow rate (R² = 0.9987), flow index (R² = 0.9961), and flow coefficient (R² = 0.9946), where the path width has the highest importance score in the model construction for the flow index (score = 55.97) and flow coefficient (score = 45.2). Furthermore, the CatBoost models used in this study achieved the best prediction results compared to seven typical models (XGBoost, Bagging, Random Forest, Tree, Adaboost, and KNN). Full article

(This article belongs to the Special Issue Improving Irrigation Management Practices for Agricultural Production)

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Review

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24 pages, 2923 KiB

Open AccessReview

Advances in Sprinkler Irrigation: A Review in the Context of Precision Irrigation for Crop Production

by Junaid Nawaz Chauhdary, Hong Li, Yue Jiang, Xuwei Pan, Zawar Hussain, Maria Javaid and Muhammad Rizwan

Agronomy 2024, 14(1), 47; https://doi.org/10.3390/agronomy14010047 - 23 Dec 2023

Viewed by 2305

Abstract

The non-judicious use of water at the farm level in traditional irrigation application methods is a present-day concern across the world that can be resolved by enhancing application efficiency through the adoption of advanced irrigation techniques. Sprinkler irrigation is a method that has high application efficiency, which can be further increased when coupled with automation toward precision irrigation. The objectives of this review are to summarize the main aspects of sprinkler and precision irrigation and their development, scope, and future prospects specifically in Asian countries. In this paper, a modified methodology, inspired by PRISMA guidelines, was used to explore the available literature to summarize the existing knowledge in the field. Regarding the technological aspects of the analyzed works, it became evident that sprinkler systems are an efficient method to not only irrigate crops (with 39% water saving) but also for the application of fertilizers with higher efficiency (>35%) and water productivity (>14.1%) compared with gravity irrigation systems. Moreover, this paper highlights the prominent features of precision irrigation for maximizing agricultural productivity. The use of sprinkler irrigation with precision applications using automation with a sensor-based mechanism for field data collection, data transformation, data analysis, and operation of IoT-based automatic solenoid valves can save 20–30% more irrigation water and increase crop yield by 20–27%. An analytical understanding and knowledge of the field were used to draw conclusions that are thought-provoking for scientists, researchers, and other stakeholders. Full article

(This article belongs to the Special Issue Improving Irrigation Management Practices for Agricultural Production)

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