scholarly journals Irrigation Management Scale and Water Application Method to Improve Yield and Water Productivity of Field-Grown Strawberries

Agronomy ◽  
2019 ◽  
Vol 9 (6) ◽  
pp. 286 ◽  
Author(s):  
Guillaume Létourneau ◽  
Jean Caron
Keyword(s):  
Spatial Variability ◽  
Soil Properties ◽  
Water Productivity ◽  
Irrigation Management ◽  
Richards Equation ◽  
Water Application ◽  
Experimental Site ◽  
Management Zones ◽  
Rock Fragments ◽  
Application Method

Improvements in water productivity are of primary importance for maintaining agricultural productivity and sustainability. Water potential-based irrigation management has proven effective for this purpose with many different crops, including strawberries. However, problems related to spatial variability of soil properties and irrigation efficiency were reported when applying this management method to strawberries in soils with rock fragments. In this study, a field-scale experiment was performed to evaluate the impacts of three irrigation management scales and a pulsed water application method on strawberry yield and water productivity. An analytical solution to Richards’ equation was also used to establish critical soil water potentials for this crop and evaluate the effects of the variability in the soil properties. Results showed that spatial variability of soil properties at the experimental site was important but not enough to influence crop response to irrigation practices. The studied properties did not present any spatial structure that could allow establishing specific management zones. A four-fold reduction in the size of the irrigation management zones had no effect on yield and increased the water applications. Pulsed application led to significant yield (22%) and water productivity (36%) increases compared with the standard water application method used by the producer at the experimental site.

scholarly journals Delineation of irrigation management zones in a Quartzipsamment of the Brazilian semiarid region

2016 ◽  
Vol 51 (9) ◽  
pp. 1283-1294 ◽  
Author(s):  
Henrique Oldoni ◽  
Luís Henrique Bassoi
Keyword(s):  
Soil Properties ◽  
Clustering Algorithm ◽  
Irrigation Management ◽  
Optimal Number ◽  
Semiarid Region ◽  
Management Zones ◽  
Distribution Maps ◽  
Management Zone ◽  
Brazilian Semiarid ◽  
Fuzzy C Means Clustering

Abstract The objective of this work was to delineate irrigation management zones using geostatistics and multivariate analysis in different combinations of physical and hydraulic soil properties, as well as to determine the optimal number of management zones in order to avoid overlaping. A field experiment was carried out in a Quartzipsamment, for two years, in an irrigated orchard of table grape, in the Senador Nilo Coelho Irrigation Scheme, in the municipality of Petrolina, in the state of Pernanbuco, Brazil. Soil samples were collected for the determination of soil physico-hydraulic properties. A portable meter was used to measure soil apparent electrical conductivity. Spatial distribution maps were generated using ordinary kriging. Management zones for five different combinations of soil properties were defined using the fuzzy c-means clustering algorithm, and two indexes were applied to determine the optimal number of management zones. Two combinations of soil properties can be used in the management zone planning in order to monitor soil moisture.

scholarly journals Zoning of a Newly-Planted Vineyard: Spatial Variability of Physico-Chemical Soil Properties

Soil Systems ◽  
2020 ◽  
Vol 4 (4) ◽  
pp. 62 ◽  
Author(s):  
José Manuel Mirás-Avalos ◽  
María Fandiño ◽  
Benjamín J. Rey ◽  
Jorge Dafonte ◽  
Javier J. Cancela
Keyword(s):  
Spatial Variability ◽  
Soil Properties ◽  
Low Cost ◽  
Irrigation Management ◽  
Chemical Properties ◽  
Exchange Capacity ◽  
Physico Chemical ◽  
Spatio Temporal ◽  
Different Origins ◽  
Two Sectors

Soil properties show a high spatio-temporal variability, affecting productivity and crop quality within a given field. In new vineyard plantations, with changes in the initial topographic profile, this variability is exacerbated due to the incorporation of soil from different origins and qualities. The aim of the current study was to characterize the variability of soil properties in a newly established vineyard, and delineating zones for site-specific management of fertilization. For this purpose, the soil apparent electrical conductivity (ECa) in the first 150 cm was measured with an electromagnetic induction sensor. A soil sampling was performed following a regular grid (35 × 35 m, 149 samples), collecting samples down to 40 cm depth for determining soil chemical properties. Spatial variability was assessed through semivariogram calculation and ordinary kriging. The soil properties that better represent the variability in this newly established vineyard were pH, effective cation exchange capacity (ECEC), carbon content, clay and ECa. The ECa was homogeneous all over the vineyard, except for the area closer to the river where a greater human intervention had occurred, with contributions of external soil at a greater depth. Soil properties showed a great spatial variability. Interpolated maps allowed for detecting areas with a lack of nutrients in which a differential fertilization could be performed in search of a sustainable and balanced production. The information provided by the maps of pH, ECEC and carbon and potassium contents allow for performing a differential management of the vineyard in terms of fertilization. In addition, the results obtained suggest that the vineyard should be divided into two sectors for a differential irrigation management. The ECa was not significantly correlated to most of the soil properties determined in the current study; however, it allowed for a low-cost mapping of the vineyard soil and established large areas of management within the vineyard.

scholarly journals Soil Properties Spatial Variability and Delineation of Site-Specific Management Zones Based on Soil Fertility Using Fuzzy Clustering in a Hilly Field in Jianyang, Sichuan, China

2019 ◽  
Vol 11 (24) ◽  
pp. 7084 ◽  
Author(s):  
Mohamed S. Metwally ◽  
Sameh M. Shaddad ◽  
Manqiang Liu ◽  
Rong-Jiang Yao ◽  
Ahmed I. Abdo ◽  
...  
Keyword(s):  
Spatial Variability ◽  
Soil Properties ◽  
Soil Degradation ◽  
Crop Production ◽  
Nutrient Management ◽  
Soil Nutrient ◽  
Available Phosphorus ◽  
Site Specific ◽  
Management Zones ◽  
Nutrient Contents

Avoiding soil degradation and improving crop productivity could be achieved by performing sustainable soil nutrient management with an appropriate understanding of soil properties’ spatial variability. The present fertilizer recommendations for the region where the study area is located are typically symmetric for large regions. This leads to the under-application of fertilizers in zones with low nutrient contents and over-application in zones with high nutrient contents. Therefore, this study was conducted to assess soil management zones (MZs) in the study area for effective soil nutrient management and to evaluate soil properties’ spatial variability. A total of 100 geo-referenced soil samples were collected at a depth of 0–20 cm, processed and analyzed for pH, available nitrogen (AN), available phosphorus (AP), available potassium (AK), soil organic carbon (SOC), total nitrogen (TN) and total phosphorous (TP), while C:N, C:P and N:P ratios were calculated. Soil properties’ coefficients of variation (CVs) widely varied from low (1.132%) to moderate (45.748%). Ordinary kriging and semi-variogram analysis showed differed spatial variability patterns for the studied soil properties with spatial dependence ranged from weak to strong. MZs were delineated by performing principal component analysis (PCA) and fuzzy K-means clustering. Four PCs with eigen values more than 1 dominated 84.44% of the total variance, so they were retained for clustering analysis. Three MZs were delineated based on the two criteria modified partition entropy (MPE) and fuzzy performance index (FPI). The studied soil properties differed significantly among MZs. Thus, the methodology used for MZ delineation could be used effectively for soil site-specific nutrient management for avoiding soil degradation concurrently with maximizing crop production in the study area.

scholarly journals Spatial variability of apparent electrical conductivity and soil properties in a coffee production field

2014 ◽  
Vol 34 (6) ◽  
pp. 1224-1233 ◽  
Author(s):  
Domingos S. M. Valente ◽  
Daniel M. de Queiroz ◽  
Francisco de A. de C. Pinto ◽  
Fábio L. Santos ◽  
Nerilson T. Santos
Keyword(s):  
Electrical Conductivity ◽  
Spatial Variability ◽  
Soil Properties ◽  
Precision Agriculture ◽  
Chemical Properties ◽  
Coffee Production ◽  
Management Zones ◽  
Apparent Electrical Conductivity ◽  
The Relationship ◽  
Dense Sampling

Precision agriculture based on the physical and chemical properties of soil requires dense sampling to determine the spatial variability of these properties. This dense sampling is often expensive and time-consuming. One technique used to reduce sample numbers involves defining management zones based on information collected in the field. Some researchers have demonstrated the importance of soil electrical variables in defining management zones. The objective of this study was to evaluate the relationship between the spatial variability of the apparent electrical conductivity and the soil properties in the coffee production of mountain regions. Spatial variability maps were generated using a geostatistical method. Based on the spatial variability results, a correlation analysis, using bivariate Moran's index, was done to evaluate the relationship between the apparent electrical conductivity and soil properties. The maps of potassium (K) and remaining phosphorus (P-rem) were the closest to the spatial variability pattern of the apparent electrical conductivity.

Appropriateness of Management Zones for Characterizing Spatial Variability of Soil Properties and Irrigated Corn Yields across Years

2004 ◽  
Vol 96 (1) ◽  
pp. 195 ◽  
Author(s):  
Aaron R. Schepers ◽  
John F. Shanahan ◽  
Mark A. Liebig ◽  
James S. Schepers ◽  
Sven H. Johnson ◽  
...  
Keyword(s):  
Spatial Variability ◽  
Soil Properties ◽  
Management Zones

scholarly journals Spatial variability studies in São Paulo, Brazil along the last twenty five years

Bragantia ◽  
2010 ◽  
Vol 69 (suppl) ◽  
pp. 53-66 ◽  
Author(s):  
Sidney Rosa Vieira ◽  
Sonia Carmela Falci Dechen
Keyword(s):  
Data Analysis ◽  
Spatial Variability ◽  
Physical Properties ◽  
Soil Properties ◽  
Crop Yields ◽  
Soil Physical Properties ◽  
Sao Paulo ◽  
No Tillage ◽  
Management Zones ◽  
Sampling Points

Soil properties vary in space due to many causes. For this reason it is wise to know the magnitude and behaviour of the variability for adequate data analysis and decision making. Our work on spatial variability of soil properties in São Paulo, Brazil began in 1982 with a very simple soil sampling in a small field. Much progress has been made since then on sampling designs, field equipment and methods, and mostly on computation equipment and softwares. This paper reports the results corresponding to some aspects of this progress, as far as the field, analysis and computation work are concerned. The objective of this study was to illustrate the use of geostatistics in data analysis for three sampling conditions on long term no-tillage system. The analysis is done on a wide range of field scales, variables, sampling schemes as well as repeating sampling scheme for the same variable in different years. Semivariograms are compared for the same variables in different scales and sampling dates and depths as to provide a guide for sampling spacing and number of samples. Normalized crop yield parameters for many years are used in the discussion of time variability and on the use of yield maps to locate management zones. The time of the year in which measurements of soil physical properties are made affected the results both in terms of descriptive statistical and spatial dependence parameters. Crop yields changed (soybean decrease and maize increase) with time of no-tillage but the real cause was not identified. The length of time with no-tillage affected the range of dependence for the main crops (increased for soybean, maize and oats) and therefore increased the size of the homogeneous management zones. The evolution of the sampling grid from 20 m with 63 sampling points to 10 m with 302 sampling points allowed for a much better knowledge of the spatial variability of crop yields but it had the reverse effect on the spatial variability of soil physical properties.

scholarly journals Using Satellite Thermal-Based Evapotranspiration Time Series for Defining Management Zones and Spatial Association to Local Attributes in a Vineyard

2020 ◽  
Vol 12 (15) ◽  
pp. 2436
Author(s):  
Noa Ohana-Levi ◽  
Kyle Knipper ◽  
William P. Kustas ◽  
Martha C. Anderson ◽  
Yishai Netzer ◽  
...  
Keyword(s):  
Time Series ◽  
Spatial Variability ◽  
Soil Type ◽  
Irrigation Management ◽  
Spatial Association ◽  
Environmental Modeling ◽  
Topographic Wetness Index ◽  
Modeling Framework ◽  
Error Matrix ◽  
Management Zones

A well-planned irrigation management strategy is crucial for successful wine grape production and is highly dependent on accurate assessments of water stress. Precision irrigation practices may benefit from the quantification of within-field spatial variability and temporal patterns of evapotranspiration (ET). A spatiotemporal modeling framework is proposed to delineate the vineyard into homogeneous areas (i.e., management zones) according to their ET patterns. The dataset for this study relied on ET retrievals from multiple satellite platforms, generating estimates at high spatial (30 m) and temporal (daily) resolutions for a Vitis vinifera Pinot noir vineyard in the Central Valley of California during the growing seasons of 2015-2018. Time-series decomposition was used to deconstruct the time series of each pixel into three components: long-term trend, seasonality, and remainder, which indicates daily fluctuations. For each time-series component, a time-series clustering (TSC) algorithm was applied to partition the time series of all pixels into homogeneous groups and generate TSC maps. The TSC maps were compared for spatial similarities using the V-measure statistic. A random forest (RF) classification algorithm was used for each TSC map against six environmental variables (elevation, slope, northness, lithology, topographic wetness index, and soil type) to check for spatial association between ET-TSC maps and the local characteristics in the vineyard. Finally, the TSC maps were used as independent variables against yield (ton ha-1) using analysis of variance (ANOVA) to assess whether the TSC maps explained yield variability. The trend and seasonality TSC maps had a moderate spatial association (V = 0.49), while the remainder showed dissimilar spatial patterns to seasonality and trend. The RF model showed high error matrix-based prediction accuracy levels ranging between 86% and 90%. For the trend and seasonality models, the most important predictor was soil type, followed by elevation, while the remainder TSC was strongly linked with northness spatial variability. The yield levels corresponding to the two clusters in all TSC were significantly different. These findings enabled spatial quantification of ET time series at different temporal scales that may benefit within-season decision-making regarding the amounts, timing, intervals, and location of irrigation. The proposed framework may be applicable to other cases in both agricultural systems and environmental modeling.

Spatial variability of some chemical properties of a Cambisol soil with cocoa (Theobroma cacao L.) cultivation

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Sergio Salgado García ◽  
Joana Acopa Colorado ◽  
Sergio Salgado-Velázquez ◽  
Samuel Córdova Sánchez ◽  
David Palma López ◽  
...  
Keyword(s):  
Spatial Variability ◽  
Soil Properties ◽  
Spatial Dependence ◽  
Chemical Properties ◽  
Kriging Interpolation ◽  
Management Zones ◽  
Agronomic Management ◽  
Management Area ◽  
Theobroma Cacao L ◽  
Exchangeable P

Objective: To evaluate the spatial variability of some chemical properties of a Cambisolsoil, in order to establish specific agronomic management zones for cocoa cultivation.Methodology: A sampling of 42 georeferenced points equidistant at 40 m was carriedout. Geostatistical variability maps were made with the results of the chemical analysisof the soil properties, using the ordinary Kriging interpolation technique.Results: It was found that the percentage of saturation of acidity (PSA), acidity and H+showed high variability; P-Olsen and interchangeable K, Ca and Mg displayed mediumvariability, and pH, MO, CIC and Al presented low variability. Soil properties pH, PSA;Exchangeable P-Olsen, Ca and Mg showed high spatial dependence (<25%) and OM,exchangeable K and CIC moderate spatial dependence (25-75%).Study limitations / Implications: The generated maps allowed the identification ofpartial areas with different variability, as well as the direction of greatest variability of theproperty as a function of distance.Conclusions: With the maps, it was possible to make recommendations for agronomicmanagement depending on each specific management area.

Spatial Variability of Measured Soil Properties across Site-Specific Management Zones

2005 ◽  
Vol 69 (5) ◽  
pp. 1572-1579 ◽  
Author(s):  
M. Mzuku ◽  
R. Khosla ◽  
R. Reich ◽  
D. Inman ◽  
F. Smith ◽  
...  
Keyword(s):  
Spatial Variability ◽  
Soil Properties ◽  
Site Specific ◽  
Management Zones ◽  
Specific Management
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