Delineation of site specific nutrient management zones for a paddy cultivated area based on soil fertility using fuzzy clustering

Geoderma ◽  
2012 ◽  
Vol 173-174 ◽  
pp. 111-118 ◽  
Author(s):  
N. Davatgar ◽  
M.R. Neishabouri ◽  
A.R. Sepaskhah
Keyword(s):  
Soil Fertility ◽  
Fuzzy Clustering ◽  
Nutrient Management ◽  
Site Specific ◽  
Management Zones

scholarly journals Delineation of Soil Fertility Management Zones for Site-specific Nutrient Management in the Maize Belt Region of Nigeria

2020 ◽  
Vol 12 (21) ◽  
pp. 9010
Author(s):  
Kamaluddin T. Aliyu ◽  
Alpha Y. Kamara ◽  
Jibrin M. Jibrin ◽  
Jeroen E. Huising ◽  
Bello M. Shehu ◽  
...  
Keyword(s):  
Spatial Variability ◽  
Soil Fertility ◽  
Crop Production ◽  
Nutrient Management ◽  
Available P ◽  
Soil Fertility Management ◽  
Extrinsic Factors ◽  
Total N ◽  
Site Specific ◽  
Management Zones

Site-specific nutrient management can reduce soil degradation and crop production risks related to undesirable timing, amount, and type of fertilizer application. This study was conducted to understand the spatial variability of soil properties and delineate spatially homogenous nutrient management zones (MZs) in the maize belt region of Nigeria. Soil samples (n = 3387) were collected across the area using multistage and random sampling techniques, and samples were analyzed for pH, soil organic carbon (SOC), macronutrients (N, P, K, S, Ca and Mg), micronutrients (S, B, Zn, Mn and Fe) content, and effective cation exchange capacity (ECEC). Spatial distribution and variability of these parameters were assessed using geostatistics and ordinary kriging, while principal component analysis (PCA) and multivariate K-means cluster analysis were used to delineate nutrient management zones. Results show that spatial variation of macronutrients (total N, available P, and K) was largely influenced by intrinsic factors, while that of S, Ca, ECEC, and most micronutrients was influenced by both intrinsic and extrinsic factors with moderate to high spatial variability. Four distinct management zones, namely, MZ1, MZ2, MZ3, and MZ4, were identified and delineated in the area. MZ1 and MZ4 have the highest contents of most soil fertility indicators. MZ4 has a higher content of available P, Zn, and pH than MZ1. MZ2 and MZ3, which constitute the larger part of the area, have smaller contents of the soil fertility indicators. The delineated MZs offer a more feasible option for developing and implementing site-specific nutrient management in the maize belt region of Nigeria.

scholarly journals Delineation of Management Zones for Site-Specific Information about Soil Fertility Characteristics through Proximal Sensing of Potato Fields

Agronomy ◽  
2020 ◽  
Vol 10 (12) ◽  
pp. 1854
Author(s):  
Humna Khan ◽  
Aitazaz A. Farooque ◽  
Bishnu Acharya ◽  
Farhat Abbas ◽  
Travis J. Esau ◽  
...  
Keyword(s):  
Soil Fertility ◽  
Prince Edward Island ◽  
Tuber Yield ◽  
Sampling Strategy ◽  
Time Domain Reflectometry ◽  
Specific Information ◽  
Proximal Sensing ◽  
Site Specific ◽  
Management Zones ◽  
Ground Conductivity

The delineation of management zones (MZs) has been suggested as a solution to mitigate adverse impacts of soil variability on potato tuber yield. This study quantified the spatial patterns of variability in soil and crop properties to delineate MZs for site-specific soil fertility characterization of potato fields through proximal sensing of fields. Grid sampling strategy was adopted to collect soil and crop data from two potato fields in Prince Edward Island (PEI). DUALEM-2 sensor, Time Domain Reflectometry (TDR-300), GreenSeeker were used to collect soil ground conductivity parameter horizontal coplanar geometry (HCP), soil moisture content (θ), and normalized difference vegetative index (NDVI), respectively. Soil organic matter (SOM), soil pH, phosphorous (P), potash (K), iron (Fe), lime index (LI), and cation exchange capacity (CEC) were determined from soil samples collected from each grid. Stepwise regression shortlisted the major properties of soil and crop that explained 71 to 86% of within-field variability. The cluster analysis grouped the soil and crop data into three zones, termed as excellent, medium, and poor at a 40% similarity level. The coefficient of variation and the interpolated maps characterized least to moderate variability of soil fertility parameters, except for HCP and K that were highly variable. The results of multiple means comparison indicated that the tuber yield and HCP were significantly different in all MZs. The significant relationship between HCP and yield suggested that the ground conductivity data could be used to develop MZs for site-specific fertilization in potato fields similar to those used in this study.

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 Establishing management zones using soil electrical conductivity and other soil properties by the fuzzy clustering technique

2008 ◽  
Vol 65 (6) ◽  
pp. 567-573 ◽  
Author(s):  
José Paulo Molin ◽  
Cesar Nunes de Castro
Keyword(s):  
Electrical Conductivity ◽  
Soil Fertility ◽  
Soil Properties ◽  
Precision Agriculture ◽  
Principal Component ◽  
Site Specific ◽  
Management Zones ◽  
Physical Attributes ◽  
Definition Of ◽  
Specific Management

The design of site-specific management zones that can successfully define uniform regions of soil fertility attributes that are of importance to crop growth is one of the most challenging steps in precision agriculture. One important method of so proceeding is based solely on crop yield stability using information from yield maps; however, it is possible to accomplish this using soil information. In this study the soil was sampled for electrical conductivity and eleven other soil properties, aiming to define uniform site-specific management zones in relation to these variables. Principal component analysis was used to group variables and fuzzy logic classification was used for clustering the transformed variables. The importance of electrical conductivity in this process was evaluated based on its correlation with soil fertility and physical attributes. The results confirmed the utility of electrical conductivity in the definition of management zones and the feasibility of the proposed method.

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