Consistency And Change In Spatial Variability Of Crop Yield Over Successive Seasons: Methods Of Data Analysis

2015 ◽  
pp. 141-149 ◽  
Author(s):  
R.M. Lark ◽  
J. V. Stafford
Keyword(s):  
Data Analysis ◽  
Spatial Variability ◽  
Crop Yield

scholarly journals Spatial variability of soil fertility and its relation with cocoa yield

2017 ◽  
Vol 21 (2) ◽  
pp. 88-93 ◽  
Author(s):  
Railton O. dos Santos ◽  
◽  
Laís B. Franco ◽  
Samuel A. Silva ◽  
George A. Sodré ◽  
...  
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
Spatial Variability ◽  
Soil Fertility ◽  
Soil Properties ◽  
Crop Yield ◽  
Chemical Properties ◽  
Western Region ◽  
Chemical Attributes ◽  
Cocoa Yield

ABSTRACT The knowledge on the spatial variability of soil properties and crops is important for decision-making on agricultural management. The objective of this study was to evaluate the spatial variability of soil fertility and its relation with cocoa yield. The study was conducted over 14 months in an area cultivated with cocoa. A sampling grid was created to study soil chemical properties and cocoa yield (stratified in season, off-season and annual). The data were analyzed using descriptive and exploratory statistics, and geostatistics. The chemical attributes were classified using fuzzy logic to generate a soil fertility map, which was correlated with maps of crop yield. The soil of the area, except for the western region, showed possibilities ranging from medium to high for cocoa cultivation. Soil fertility showed positive spatial correlation with cocoa yield, and its effect was predominant only for the off-season and annual cocoa.

scholarly journals Spatial Variability of Soil Physical and Hydraulic Properties in a Durum Wheat Field: An Assessment by the BEST-Procedure

Water ◽  
2019 ◽  
Vol 11 (7) ◽  
pp. 1434 ◽  
Author(s):  
Mirko Castellini ◽  
Anna Maria Stellacci ◽  
Matteo Tomaiuolo ◽  
Emanuele Barca
Keyword(s):  
Spatial Variability ◽  
Crop Yield ◽  
Soil Texture ◽  
Hydraulic Properties ◽  
Wheat Yield ◽  
Structure Stability ◽  
Soil Hydraulic Properties ◽  
Field Scale ◽  
Cross Correlation Analysis ◽  
Soil Hydraulic

Spatial variability of soil properties at the field scale can determine the extent of agricultural yields and specific research in this area is needed. The general objective of this study was to investigate the relationships between soil physical and hydraulic properties and wheat yield at the field scale and test the BEST-procedure for the spatialization of soil hydraulic properties. A simplified version of the BEST-procedure, to estimate some capacitive indicators from the soil water retention curve (air capacity, ACe, relative field capacity, RFCe, plant available water capacity, PAWCe), was applied and coupled to estimates of structure stability index (SSI), determinations of soil texture and measurements of bulk density (BD), soil organic carbon (TOC) and saturated hydraulic conductivity (Ks). Variables under study were spatialized to investigate correlations with observed medium-high levels of wheat yields. Soil physical quality assessment and correlations analysis highlighted some inconsistencies (i.e., a negative correlation between PAWCe and crop yield), and only five variables (i.e., clay + silt fraction, BD, TOC, SSI and PAWCe) were spatially structured. Therefore, for the soil–crop system studied, application of the simplified BEST-procedure did not return completely reliable results. Results highlighted that (i) BD was the only variable selected by stepwise analysis as a function of crop yield, (ii) BD showed a spatial distribution in agreement with that detected for crop yield, and (iii) the cross-correlation analysis showed a significant positive relationship between BD and wheat yield up to a distance of approximately 25 m. Such results have implications for Mediterranean agro-environments management. In any case, the reliability of simplified measurement methods for estimating soil hydraulic properties needs to be further verified by adopting denser measurements grids in order to better capture the soil spatial variability. In addition, the temporal stability of observed spatial relationships, i.e., between BD or soil texture and crop yields, needs to be investigated along a larger time interval in order to properly use this information for improving agronomic management.

scholarly journals Soil Data Analysis and Crop Yield Prediction in Data Mining using R – Programming

2020 ◽  
Vol 9 (3) ◽  
pp. 1857-1860
Keyword(s):  
Data Mining ◽  
Data Analysis ◽  
Decision Tree ◽  
Crop Yield ◽  
Climatic Condition ◽  
Research Work ◽  
Yield Prediction ◽  
Decision Tree Algorithm ◽  
Data Set ◽  
R Programming

Data mining is better choices in emerging research filed- soil data analysis. crop yield prediction is an important issue for selecting the crop. earlier prediction of crop is done by the experience of farmer on a particular type of field and crop. predicting the crop is done by the farmer’s experience based on the factors like soil types, climatic condition, seasons, and weather, rainfall and irrigation facilities. data mining techniques is the better choice for predicting the crop. the analysis of soil plays an important role in agricultural filed. soil fertility prediction is one of the very important factors in agriculture this research work implements to predict yield of crop, decision tree algorithm is used to find yield. the aim of this research to pinpoint the accuracy and to finding the yield of the crop using decision tree and c 4.5 algorithm is used to predict the yield of crop using rprogramming and also to find range of magnesium found in the collected soil data set. this prediction will be very useful for the farmer to predict the crop yield for cultivation

scholarly journals Spatial variability of total soil nitrogen and sulphur content at two conventionally managed fields

2008 ◽  
Vol 54 (No. 10) ◽  
pp. 413-419 ◽  
Author(s):  
V. Vaněk ◽  
J. Balík ◽  
J. Šilha ◽  
J. Černý
Keyword(s):  
Spatial Variability ◽  
Crop Yield ◽  
Soil Nitrogen ◽  
Coefficient Of Variation ◽  
Sulphur Content ◽  
N Content ◽  
Total N ◽  
Total Soil ◽  
Positive Correlations ◽  
Total Soil Nitrogen

Spatial variability of total soil nitrogen and sulphur content has been observed in two plots (I – 54 ha and II – 32 ha). Soil samples were taken from the topsoil in a regular grid, which was localised by GPS (individual sampling points were 80 m apart); subsequently total soil N and S contents were analysed. The average N content in plot I was 0.16%; in plot II it was 0.12%. The content of S in plots I and II was 0.09% and 0.08%, respectively. Spatial variability of total N differed in separate parts of the plots. A higher variability was recorded in plot I, where the coefficient of variation (<I>CV</I>) was 15.7%, whereas in plot II it was only 11.1%. However, sulphur showed only little variability, and thus its coefficient of variation was low (2.5 a 2.3% in plots I and II, respectively). A positive and mostly conclusive relationship has been observed between the N content of soil and the crop yield. This effect was more significant in plot II. The S content in soil showed no correlation with yield. Furthermore, positive correlations were observed between field altitude, soil moisture and crop yield in both plots.

scholarly journals Spatial variability of soil attributes and sugarcane yield in relation to topographic location

2010 ◽  
Vol 14 (12) ◽  
pp. 1250-1256 ◽  
Author(s):  
Zigomar M. de Souza ◽  
Domingos G. P. Cerri ◽  
Paulo S. G. Magalhães ◽  
Diego S. Siqueira
Keyword(s):  
Spatial Variability ◽  
Crop Yield ◽  
Cation Exchange Capacity ◽  
Exchange Capacity ◽  
Soil Samples ◽  
Test Area ◽  
Management Zones ◽  
Soil Attributes ◽  
Sugarcane Yield ◽  
Definition Of

Soils submitted to the same management system in places with little variation of landscape, manifest differentiated spatial variability of their attributes and crop yield. The aim of this work was to investigate the correlation between spatial variability of the soil attributes and sugarcane yield as a result of soil topography. To achieve this objective, a test area of 42 ha located at the São João Sugar Mill, in Araras, in the State of São Paulo, Brazil, was selected. Sugarcane yield was measured with a yield monitor fitted in a sugarcane harvester and GPS signal. A total of 170 soil samples were taken at regular 50 m grid, at a depth of 0 - 0.2 m. The area under study was divided into two sites based on topography. The following soil attributes were analysed: organic matter (OM) content, exchangeable potassium (K), calcium (Ca) and magnesium (Mg), their base saturation percentage (%BS), cation exchange capacity (CEC), pH, clay, silt, total sand and density. The use of landscape and geostatistics enable defining areas with different spatial variability in soil attributes and crop yield, providing the visualization and definition of homogeneous management zones. The largest spatial variability of soil attributes and sugarcane yield was in the lowest part of the field.

Spatial Variability of Crop Yield as a Stochastic Soil Process

1981 ◽  
Vol 45 (3) ◽  
pp. 600-605 ◽  
Author(s):  
Eshel Bresler ◽  
S. Dasberg ◽  
D. Russo ◽  
G. Dagan
Keyword(s):  
Spatial Variability ◽  
Crop Yield ◽  
Soil Process
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