Center Pivot Research Articles

Water distribution characteristics of deflector plates used in center pivot irrigation systems

Water distribution characteristics of deflector plates used in center pivot irrigation systems

REPORT OF PRACTICAL CLASS IN AGRICULTURAL AREA WITH THE BACHELOR CLASS IN AGRONOMY IN THE MUNICIPALITY OF TRACUATEUA-PA

Cassava (Manihot esculenta Crantz) is a highly consumed root and a significant source of carbohydrates in Brazil and around the world. In the state of Pará, cassava is vital to the local economy, especially in the municipality of Tracuateua. The culture involves family farmers and serves as an important source of income and subsistence. Different cultivars are used, such as BRS Tapioqueira and BRS Verdinha, which exceed 70 thousand kg/ha with good management. Adequate fertilization, pest control and weed management are essential for high productivity. Irrigation can significantly increase production. On the property of Mr. Benedito Dutra, member of the RENIVA project, the production of seed cassava and cowpea is highlighted. It uses cultivars developed by Embrapa, such as BRS Kiriris, BRS Formosa and BRS Novo Horizonte, which are recommended for industrial use. Dutra also grows cowpeas, using varieties such as BRS Guirá and BRS Natalina, which are highly productive and adapted to local conditions. The property has an irrigated area of ​​23 hectares per central pivot, ensuring crop hydration during dry periods. During the field visit, several areas of experimentation were observed. The experimental plots of cassava and cowpea showed good performance, with a high survival rate and resistance to pests. The integration of advanced soil management, pest control and irrigation practices highlighted the property as an example of innovative agriculture. The experience on Mr. Dutra’s property demonstrated the importance of innovation and adoption of advanced agricultural practices for sustainable and productive agricultural production.

Joint modeling of longitudinal and survival data for the evaluation of the impact of irrigation systems on the time until the occurrence of phoma leaf spot in Arabica coffee plants.

The coffee crop is prominent in Brazilian agriculture, making the country a global power in this area. One of the main concerns in the coffee sector is disease, which can affect coffee productivity and quality. Thus, it is important to evaluate the factors that may affect coffee quality and thus enhance the development of strategies to reduce coffee losses and costs and optimize production. This study evaluated the influence of the type of irrigation (self-propelled, drip, and center pivot) on the time until the occurrence of phoma leaf spot on Arabica coffee plants, considering the intensity of the disease. Additionally, the association between longitudinal incidence and the time until an event of interest was assessed based on the joint modeling of longitudinal and survival data. The results of this study identify the effectiveness of drip irrigation system compared with other systems; the use of such systems was associated with an ~46.5% reduction in the risk of leaf spot disease compared with the use of a self-propelled irrigation system. The use of a center pivot system increased the risk of disease progression compared with a self-propelled system. An association between the longitudinal and survival processes was also observed. The findings demonstrate the superior performance of the drip irrigation system in controlling phoma leaf spot disease in Arabica coffee plants compared with self-propelled and center pivot systems. This research highlights the potential of using drip irrigation to establish more effective agricultural practices in coffee cultivation, contributing to better disease management and improved crop quality. © 2024 Society of Chemical Industry.

Remote detection of water stress in cotton using a center pivot irrigation system-mounted sensor package.

Much research has been invested in infrared temperature (IRT)-based methods for cotton (Gossypium hirsutism L.) water stress detection using in-field sensors, but adoption of these is low, perhaps due to logistical challenges. Alternatively, the Water Deficit Index (WDI) was developed for crop water stress assessment using remote sensors not embedded in the canopy. The objective of this research was to evaluate the performance of a sensor package-including modern IRT and normalized difference vegetation index (NDVI) sensors facing downward at 45˚, and a mini weather station-attached unintrusively to a center pivot irrigation system for detecting cotton water stress using WDI. Sensor packages were evaluated in a two-year field study that included four irrigation treatments (0, 30, 60, and 90% ET replacement) and in two production cotton fields. Overall, the tested system was effective at distinguishing crop water stress among irrigation rates. Comparison of the results to a ground-based station and simulations indicated that WDI overestimated water stress at the highest irrigation rate, but performed well otherwise. Accuracy of the system could be improved by measuring canopy coverage (Fc) from the same vantage point as the IRT and NDVI sensors (from the pivot, downward at a 45˚ angle).

ECBoA-OFS: An Ensemble Classification Model for Botnet Attacks based on Optimal Feature Selection using CPR in IoT

The rapid growth of the Internet of Things (IoT) has indeed introduced new security challenges, and the proliferation of compromised IoT devices has become a significant concern. Botnet attacks, where multiple corrupted devices are managed by a particular object, have become a widespread threat in IoT environments. These are used for a variety of malicious activities, including distributed DDoS attacks, data breaches, and malware distribution. However, detecting IoT botnets poses several challenges due to the resource constraints inherent in many IoT devices. The limitations in computation, storage, and communication capabilities make it challenging to deploy complex ML and deep learning models directly on these devices. This paper proposes an ensemble classification model ECBoA-OFS (Ensemble Classification for Botnet Attack Prediction using Optimal Feature Selection). It focuses on enhancing the accuracy of botnet attack prediction through the integration of ensemble methods and optimal feature selection. It describes a method for optimal feature selection in the context of analyzing the behavior of BoA and malicious traffic flow features in a network using Central Pivot Ranges (CPR). Feature selection is an important step in machine learning and data analysis because it supports to identification of the most important features for a given problem, thereby improving model performance and interpretation. The extracted features are used for model training and ensemble classification for prediction. To evaluate ECBoA-OFS, the N-BaIoT-2021 dataset consisting of regular IoT network traffic and BoA traffic records of corrupted IoT devices is utilized, considering detection precision, sensitivity, specificity, accuracy, and F1-score. Although all ensemble classifier models achieved better detection accuracy through optimal feature selection, the proposed ECBA-OFS shows better results compared to other ensemble classifier results.

Effect of some design parameters on the performance of side access nozzle and grooved plate of centre pivot sprinkler

This research evaluates the effect of various heights, pressures, nozzle size and groove numbers on the uniformity distribution of a developed pivot sprinkler. The experiment was set up at an open space in Niger State College of Agriculture Mokwa. The wind speed and temperature during the experiment were at an average of 2.2mph and 25°C. A nozzle of size 6mm, and deflection plate of 6 curved grooves were used in a centre pivot spray unit. In evaluating the performance of the spray unit components i.e. the nozzle and deflection plate, three different pressures of 5, 10, and 15 Psi and heights of 1, 1.2, and 1.5mm were used. The support structure for the experiment is an inverted U-shaped frame designed to support a spray sprinkler at different heights. The water source was a reservoir with a capacity of 3m3and a 1.5hp electric centrifugal pump was used. The volumetric or bucket method was used to measure flow rate. The application rate was measured using catch can method. The duration of each test was approximately 30min. The data obtained from the measurements were statistically analyzed with line graphs using Excel. Relationships were also established between discharge and pressure. The highest index of jet break up was 4.89 at 15Psi and 3.74 at 10Psi. The result shows that as the pressure increases with height the CU also increases. The highest uniformity of 79.4% was obtained at 1.5m height and 15Psi.

Development of a Fuzzy Variable Rate Irrigation Control System Based on Remote Sensing Data to Fully Automate Center Pivots

Development of a Fuzzy Variable Rate Irrigation Control System Based on Remote Sensing Data to Fully Automate Center Pivots

Establishing the water resources implications for closing the land and water productivity gaps using remote sensing – A case study of sugarcane

ContextTwo of the key limitations for sustainably increasing agricultural production are the scarcity of land and fresh water resources. Establishing land and water productivity gaps is, therefore, essential for measuring how efficiently these resources are being utilised and assessing the scope for increasing feed and food production. Monitoring the productivity gaps at large scales or over time using field data is challenging and expensive. Remote sensing offers an alternative data source to reveal spatial and temporal variations in productivity. ObjectiveThis paper presents a framework that integrates remote sensing derived data and field data to assess (1) land and water productivity gaps, (2) bright spots – fields exhibiting land- and water productivity equal to or higher than the target, and (3) net irrigation water demand for increasing production. MethodsThe framework is developed and applied to the Xinavane sugarcane estate in Mozambique, demonstrating its practical application through systematic evaluation on a 6637 ha section of the estate divided by different irrigation application methods. ResultsThe results reveal that the productivity gap is the highest on fields irrigated by furrow (13.1 tonnes (ton) per ha), followed by sprinkler (12.6 ton/ha) and centre pivot (9.4 ton/ha). Bridging the productivity gap on the same cropland results in an increased sugarcane production of 12.5 % requiring 8.5 % additional irrigation water, whereas achieving the same production increase through irrigation expansion requires more blue water. ConclusionsThe analyses show that remote sensing provides a viable source of information to diagnose the productivity constraints and how bright spots can provide insights into the best field management practices to overcome them. The framework demonstrates its usefulness for policy makers and stakeholders to make informed decisions on the scarce blue water allocation for enhancing agricultural production.

Optimizing Irrigation Systems for Water Efficiency and Groundwater Sustainability in the Coastal Nile Delta

This study investigates the replacement of traditional surface irrigation methods with modern irrigation systems (MIS) including horizontal sprinkler, central pivot, surface drip, and subsurface drip aimed at improving water efficiency in the Nile Delta, Egypt. The primary objectives were to determine the optimal agricultural area for implementing MIS and to assess the effects of these systems on groundwater quantity and quality in the region. To achieve this, the LINDO software was employed to optimize land allocation for each irrigation method. At the same time, the SEAWAT code was utilized to simulate saltwater intrusion (SWI) in the Nile Delta aquifer. The transition from traditional surface irrigation to MIS resulted in significant water savings, reaching 2.15 × 10^9 m³. However, groundwater modeling indicated a decrease in groundwater levels, leading to an 8 % increase in aquifer salinity due to reduced infiltration of recharge water. These findings underscore the urgent need to revise outdated irrigation practices and enhance water management strategies in the Nile Delta to mitigate salinity issues in coastal aquifers. This research's outcomes are crucial for decision-makers and stakeholders in selecting appropriate irrigation methods, particularly in arid and semi-arid regions, to ensure sustainable water use and agricultural productivity.

Spectral indices with different spatial resolutions in recognizing soybean phenology.

The aim of the present research was to evaluate the efficiency of different vegetation indices (VI) obtained from satellites with varying spatial resolutions in discriminating the phenological stages of soybean crops. The experiment was carried out in a soybean cultivation area irrigated by central pivot, in Balsas, MA, Brazil, where weekly assessments of phenology and leaf area index were carried out. Throughout the crop cycle, spectral data from the study area were collected from sensors, onboard the Sentinel-2 and Amazônia-1 satellites. The images obtained were processed to obtain the VI based on NIR (NDVI, NDWI and SAVI) and RGB (VARI, IV GREEN and GLI), for the different phenological stages of the crop. The efficiency in identifying phenological stages by VI was determined through discriminant analysis and the Algorithm Neural Network-ANN, where the best classifications presented an Apparent Error Rate (APER) equal to zero. The APER for the discriminant analysis varied between 53.4% and 70.4% while, for the ANN, it was between 47.4% and 73.9%, making it not possible to identify which of the two analysis techniques is more appropriate. The study results demonstrated that the difference in sensors spatial resolution is not a determining factor in the correct identification of soybean phenological stages. Although no VI, obtained from the Amazônia-1 and Sentinel-2 sensor systems, was 100% effective in identifying all phenological stages, specific indices can be used to identify some key phenological stages of soybean crops, such as: flowering (R1 and R2); pod development (R4); grain development (R5.1); and plant physiological maturity (R8). Therefore, VI obtained from orbital sensors are effective in identifying soybean phenological stages quickly and cheaply.

Determinants of pivot kinematics in posterior stabilized total knee arthroplasty

BackgroundRestoring medial knee pivot kinematics post-total knee arthroplasty is widely recognized to enhance patient satisfaction. Our study investigates the kinematics of patients who received posterior stabilized implants via robotic-arm assisted surgery, specifically analyzing effects of implant alignment and soft tissue balance on pivot location. MethodsTwelve high-functioning patients with unilateral posterior stabilizing knee implants underwent CT-guided robotic-arm assisted surgery. We then evaluated their knee kinematics using stereo radiography during gait, stair descent, lunge, seated knee extension and leg press. Femoral low-point condylar kinematics were used to calculate the transverse center of rotation, or pivot, using principal component analysis. Linear mixed effects regression was used to identify surgical parameters that influence pivot location across a flexion range. FindingsAcross all five activities a central pivot pattern emerged as the primary pivot location (40 %) followed by medial (25 %), no pivot (22 %) and lateral (14 %). Tibial medial resection depth and Tibial implant flexion-extension placement were significantly associated with shifting the pivot location laterally prior to cam-post engagement. Femoral implant external-internal implant placement, and medial compartment laxity in extension were significantly associated with shifting the pivot location laterally during the cam-post engagement, while femoral distal-lateral resection depth was associated with a medial shift. InterpretationCentral and medial pivot locations are predominant in patients with posterior stabilized total knee arthroplasty, facilitated by robotic-arm assisted surgery. Despite significant associations between surgical parameters such as tibial medial resection depth and lateral compartment laxity with medial pivot, these variables explained a small portion of the variability in pivot location. This suggests that while surgical precision influences pivot kinematics, individual patient factors may play a more critical role, suggesting a need for further research into patient-specific biomechanics to optimize post-surgical outcomes.

Evaluation of three irrigation application systems for watermelon production in the Texas High Plains

AbstractAbout 90% of the Texas High Plains area depends on the water supply from the Ogallala aquifer. The decline of the Ogallala water table raises a concern for the sustainability of producing the traditional irrigated field crops due to their high water demand. Thus, diversifying cropping systems may be a solution. However, about 70% of the irrigated cropland uses center pivots that may negatively impact specialty crop quality. Thus, a 3‐year experiment was conducted to assess the potential of using mobile drip irrigation (MDI) to produce fresh watermelon compared to center pivot sprinkler irrigation using low‐elevation spray application (LESA), and surface drip irrigation with plastic mulch (DI). The study evaluated the effects of irrigation systems on crop yield, fruit quality, physiological responses, water use efficiency (WUE), and irrigation use efficiency (IUE). On average, plants under MDI had higher yields (106 Mg ha−1) than those under DI (70 Mg ha−1) and LESA (68 Mg ha−1). Plants under MDI and DI also had more fruits per plant (1.9) than those under LESA (1.4). The higher yield was associated with higher biomass and photosynthetic function. In general, fruit quality was not affected by irrigation system. In addition, plants under MDI system showed a higher WUE and IUE, and less water stress than those under LESA and DI systems. Results of this study suggest that irrigating under an MDI system is a good alternative for growers in the Texas High Plains that aim to diversify their cropping system with high‐value vegetable crops such as watermelon (Citrullus lanatus).

Detecting Defect in Central Pivot Irrigation System using YOLOv7 Algorithms

Central Pivot Irrigation System (CPIS) is a significant method for intelligent irrigation used in global agriculture. It is used to cultivate important crops like wheat, which contribute to global food security. However, the CPIS encounters technical issues that result in malfunctions in its automatic control system, leading to damage to the primary pipes and towers. This can result in significant material losses for farmers and their crops. Repairing the system is also a time-consuming process. To address this issue, a study was conducted using YOLO algorithm which contains several models, and this study used the Yolov7 models to detect defects in the CPIS machine accurately. The study used a dataset gathered from agricultural areas in Salah al-Din Governorate. The models were used to determine whether the CPIS was in a safe or dangerous state. The RGB color system with Yolov7x achieved a 95% detection rate with an accuracy, F1-score, and precision values of 0.798 and 0.954. Similarly, Yolov7x achieved a 93% detection rate with accuracy, F1-score, and precision values of 0.77 and 0.932 in the Grayscale color system. Based on the outcome, this study can conclude that the yolov7x model with RGB Color System accurately detects the CPIS in both its safe and dangerous states. This makes them useful in real-time systems for CPIS defect monitoring and control.

Spatio-Temporal Dynamics of Center Pivot Irrigation Systems in the Brazilian Tropical Savanna (1985–2020)

The 204-million-hectare Brazilian tropical savanna (Cerrado biome), located in the central part of Brazil, constitutes the main region of food and natural fiber production in the country. An important part of this production is based on center pivot irrigation. Existing studies evaluating the spatio-temporal dynamics of center pivots in Brazil do not consider their retraction. This study aimed to evaluate the expansion and retraction of center pivots in the Cerrado biome in the period 1985–2020. We relied on the data produced by the MapBiomas Irriga project. In this period, the area occupied by center pivots increased from 47 thousand hectares in 1985 to 1.2 million hectares in 2020, mostly concentrated in the states of Minas Gerais, Goiás, São Paulo, and Bahia, confirming previous reports available in the literature. Among the 13 irrigation poles recognized by the National Water Agency (ANA), the Oeste Baiano (Bahia State) and the São Marcos (Goiás State) presented the largest areas of center pivots (173,048 ha and 101,725 ha, respectively). We also found that 76% of the center pivots are concentrated in the regions with low water availability (0.01–0.45 mm day−1). Within this 16-year period (2005–2020), more than 10% of center pivots found in 2005 were either abandoned or converted into rain-fed crop production. The results of this study can provide an important foundation for public policies directed toward the sustainable use of water resources by different consumers.

Wheat Crop Management and growth stage monitoring in some gypsiferous soil units using remote sensing

The study used remote sensing to manage and monitor wheat crop health in some gypsiferous soil units. Five sites cultivated with wheat and irrigated by a central pivot irrigation system were selected within gypsiferous soil units in some agricultural lands. Soil and plant samples were collected at the best spectral and vegetative growth stage (grain filling stage) from each site. Three samples of the plant and soil were collected with three replicates, resulting in a total of (5 × 3 × 3 = 45 samples for both soil and plant). Samples were prepared for conducting laboratory analyses Satellite imagery of the OLI type from the Landsat 8 satellite, acquired on 24/2/2020, was used to calculate the following spectral indices: NDVI, SAVI, OSAVI, GOSAVI, GDVI, NDMI, CMFI, LAI. The results showed a variation in the concentration of fertile elements in the soil and plants between the study sites, with the third site relatively outperforming the other sites. On the other hand, we observed a variation in the values of spectral indices between the study sites for all the spectral indices and an increase in values with the progress and increase in the size of the canopy cover to reach the best spectral growth stage at the stage of ear fullness, which is the stage of spectral stability and appropriate for monitoring crop productivity and assessing plant health. The results also concluded that NDVI and LAI are among the most important pieces of evidence that have a strong relationship with plant density and estimation of its general condition, as the relationship was strong logarithmic and linear with nitrogen, as the values of R2 reached 0.91 and 0.88, respectively, and the value of the coefficient of determination R2 reached with The phosphorus concentration was 0.67 and 0.67, respectively. Also, the use of spectral indices depends on the spectral bands that fall at the wavelength of 0.6-0.7 micrometers, which is the region where a high absorption process occurs if the vegetation cover is intact and healthy, especially the NDVI index.

Review of Integrated Management of Cereal Cyst Nematode Heterodera avenae on Wheat Crop under Centre Pivot Irrigation System

Review of Integrated Management of Cereal Cyst Nematode Heterodera avenae on Wheat Crop under Centre Pivot Irrigation System

Water-energy-food-greenhouse gas nexus: An approach to solutions for water scarcity in agriculture of a semi-arid region

CONTEXTAgricultural systems involve intricate interdependencies among water, energy, and food. Increasing understanding of these linkages, along with implications for greenhouse gas (GHG) emissions and developing new assessment approaches are critical for achieving key sustainability goals. OBJECTIVES1) Evaluation of the impacts of tillage, irrigation and residue management practices on water and energy consumption, and GHG emission in the cultivation of irrigated wheat and rapeseed, 2) Developing a novel Water-Energy-Food-Greenhouse gas (WEFG) nexus index to provide a holistic assessment of the linkages among water, energy, food, and GHG emissions in agriculture, and 3) Assessing the sustainability of irrigated wheat and rapeseed cultivation under different methods of tillage, irrigation and residue management applying the WEFG nexus index. METHODSThis study formulated a new WEFG nexus index applying eight indicators of water and energy consumption, CO2-eq (CO2 equivalent) emission, water and energy mass productivity, water, energy and CO2-eq economic productivity to evaluate the sustainability of wheat and rapeseed cultivation under two field management practices: 1) furrow irrigation with conventional tillage (FICT), and 2) center pivot irrigation with no-tillage (CPNT), within a semi-arid region in northeastern Iran. Irrigation in both systems was done by applying a deficit irrigation approach. RESULTS AND CONCLUSIONSCPNT resulted on average in 46% and 53% energy consumption reductions from water and diesel usage, respectively, compared to FICT. The mean CO2-eq emission under CPNT was 26% lower than that recorded under FICT. Furthermore, the WEFG nexus index score for wheat and rapeseed under CPNT was 0.91 and 0.73, respectively, out of 1, compared to 0.18 and 0.12 for FICT. These scores suggest that the CPNT approach is a more appropriate strategy than FICT, as it effectively reduced water and energy consumption while aligning better with long-term environmental and economic aims. SIGNIFICANCEThe study applies more accurate GHG emission-based indicators to introduce a new WEFG nexus index, and it uses these for evaluation of different field management at the farm level to reduce the uncertainties in the large-scale studies. The proposed methodology for assessing multiple aspects of the WEFG nexus can change previous perceptions about agricultural management in other regions confronting multiple resources and environmental crises.

Economic Evaluation of Water Management Alternatives in the Upper Green River Basin of Wyoming

Water use efficiency measures are generally recommended to reduce water use. Yet, flood irrigation practices in high-elevation mountain valleys of the Colorado River Basin headwaters generate return flows, which support late-season streamflow and groundwater recharge. Return flows support the ecosystem and provide recreational benefits. This study provides a framework for quantifying how land-use changes and associated return flow patterns affect the economic value of water across uses in a hydrologically connected, shallow alluvial aquifer system. This study first investigates how return flow patterns could change under three alternatives to flood irrigation: an increased use of center pivots, increased residential development, and conversion to pasture. The brown trout was used as an indicator species to track eco-hydrology, return flow, and capacity for recreational activities under each alternative. Estimates from the non-market valuation literature coupled with predicted changes in brown trout productivity approximate associated changes to recreational angler value. Recreational angler values are highest under the flood irrigation alternative. The inclusion of recreational angler values with agricultural values alters the magnitude of returns but not the rankings. These results highlight the potential heterogeneity of conclusions to be drawn regarding water use efficiency, depending on the economic value of water in different uses and the degree of hydrologic connectivity. This study also highlights data gaps and modeling needs for conducting similar future analyses.

Study of Temperature Drop Region in Transitional Region in Fluid-Film Thrust Bearings

Abstract A thrust bearing is a type of rotary bearing that permits rotation between parts and is designed to support a load parallel to the axis of rotation. There is a temperature drop region with the increase in speed. However, previous researchers mainly showed such temperature drop experimentally, and the physics causing such temperature drop is not understood. A full fluid–solid computational fluid dynamics (CFD) model was developed for a center pivot, tilting pad, and fluid-film thrust-bearing experimental model to study the physics of temperature drop in the transitional region. A novel physics of causing temperature drop in the transitional region was proposed, analyzed, and verified.

No increase of soil wind erosion with the establishment of center pivot irrigation system in Mu-Us sandy land

Center Pivot Irrigation system (CPIs) is widely used in newly exploited arable land in sandy lands. These sandy lands are currently stable because of climate change and ecological restoration efforts since the beginning of the 21st century in northern China. The exploitation of these fixed sandy lands to arable land with CPIs may affect the soil wind erosion, yet it remains unknown. The temporal changes of CPIs and its effect on wind erosion module were analyzed and modeled from 2000 to 2020 in Mu-Us sandy land using satellite images and Revised Wind Erosion Equation (RWEQ). The establishment of CPIs started from 2010, boomed in 2015 and peaked in 2020. They were mainly transformed from woodland, grassland, and barren land near rivers in east and southeast, and from cropland in inter-dunes in west and southwest of Mu-Us sandy land. The temporal and spatial pattern of CPIs well aligns with the land consolidation and requisition-compensation balance policies. In most of the Mu-Us sandy land, the annual erosion module is <25 t ha−1 a−1. Despite great variation, the annual, Winter and Spring erosion module of the Mu-Us sandy land or in Otog Qian and Yuyang, the CPIs concentrated counties, all decreased during 2000–2019. Although, wind erosion module in CPIs was lower than the surrounding area, it increased in 2019 given the same climate conditions as in 2010. Our results suggest 1) the establishment of CPIs in Mu-Us sandy land greatly depends on the local policy and natural endowment, and 2) although the set-up of CPIs showed no impact on the wind erosion with CPIs accounting for <1 % of Mu-Us sandy land, post-harvest of CPIs should be carefully concerned to prevent soil wind erosion.