Mapping spatial variability of leaf nutrient status of oil palm (Elaeis guineensis Jacq.) plantations in India

Behera, Sanjib Kumar; Suresh, K.; Ramachandrudu, K.; Manorama, K.; Rao, B. N.

doi:10.1071/cp15029

Cited by 8 publications

(8 citation statements)

References 13 publications

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“…The values of N, K, S, B, P, Mg, Zn, Mn, and Fe showed high spatial dependence according to classes set by Dalchiavon & Carvalho (2012), indicating that leaf nutrient contents are not randomly distributed (Table 2). These results agree with those reported by Behera et al (2016), Lima et al (2016), and Gazola et al (2017), who also found spatial dependence of leaf nutrient contents in oil palm, papaya, and soybeans, respectively. From the spatial dependence, it was possible to obtain maps for individual definition of the spatial variability of the nutrients.…”

Section: Spatial Variability Of Leaf Nutrient Contentsupporting

confidence: 93%

Spatial Variability in Leaf Analysis and Productivity of Fertirrigated Açaí

et al. 2020

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This study aimed to define management zones (MZs) for fertirrigated açaí cultivation, based on spatial variability of the foliar nutrients and productivity data. The work was carried out in an area of 5.75 ha of a 7-year crop, with 80 georeferenced sample points. Fresh fruit productivity and nutrient (N, P, K, Ca, Mg, S, B, Cu, Fe, Mn, and Zn) contents were determined. The average contents of macronutrients were considered adequate for adult açaí plants, and their spatial dependence associated with fruit productivity allowed the representation of their distributions through maps of variability. Through multivariate analysis, three main components were highlighted. These components explained 51.5 % of the total variability of the data, where PC1 showed a higher correlation with Ca, Mg, K, and P. In addition, three MZs were obtained, out of which one with the highest productivity showed the best Ca, Mg, S, B, and Fe leaf contents. Principal component analysis and determination of MZs emphasized Ca and Mg nutrition as being more related to spatial variability and açaí fruit productivity.

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Section: Spatial Variability Of Leaf Nutrient Contentsupporting

confidence: 93%

Spatial Variability in Leaf Analysis and Productivity of Fertirrigated Açaí

et al. 2020

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“…This means that they did not show spatial dependence. However, spatial dependence was found for leaf Mg content both by Behera et al (2016) in an oil palm field in India and by Qamar Uz and Schumann (2006) in a citrus field in the USA. In addition, López-Granados et al (2004) found spatial dependence of leaf N content in an olive field in Spain.…”

Section: -Geostatistics Analysismentioning

confidence: 95%

“…López-Granados et al ( 2004) and Behera et al (2016) verified the necessity of determining spatial variability in nutrient status before planning a differential fertilizer program. López-Granados et al ( 2004) used contour maps of leaf nutrients, achieved by kriging, to estimate the percentage of an olive orchard in Spain that needed fertilization, where the concentration of the respective nutrients did not exceed the fertilization threshold.…”

Section: -Geostatistics Analysismentioning

confidence: 97%

“…López-Granados et al ( 2004) used contour maps of leaf nutrients, achieved by kriging, to estimate the percentage of an olive orchard in Spain that needed fertilization, where the concentration of the respective nutrients did not exceed the fertilization threshold. Similarly, Behera et al (2016) used leaf nutrient maps from an oil palm field in India and verified that nutrient savings could be achieved by adopting sitespecific nutrient management strategies. However, the maps obtained in the present study used data from both soil and leaf nutrients simultaneously, using co-kriging.…”

Section: -Geostatistics Analysismentioning

confidence: 97%

“…However, most of these studies did not consider leaf analysis. There are some studies on leaf nutrient spatial variability on apple fields (SHARMA, 2018) and oil palm fields in India (BEHERA et al, 2016), olive fields in Spain (LÓPEZ-GRANADOS et al, 2004), coffee fields in Brazil (SILVA et al, 2013), as well as citrus fields in both Brazil (ARMINDO et al, 2012) and the USA (QAMAR UZ; SCHUMANN, 2006). However, none of them had used the data of leaf and soil nutrients in the same map to define management zones.…”

Section: Introductionmentioning

confidence: 99%

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Spatial correlation between soil and leaf macronutrients in semiarid Brazilian mango (Mangifera indica L.) fields

et al. 2021

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Understanding the relationship between the levels of nutrients in the soil and those found in the plant is of fundamental importance for site-specific fertility management in mango (Mangifera indica L.) crop fields. This study aimed to evaluate the spatial distribution of macronutrient contents both in the soil and in the leaf and their correlations in commercial mango orchards under semiarid region conditions and to delimit the management zones using soil and leaf data. The experiment was carried out in three commercial areas in San Francisco Valley, Brazil, cultivated with irrigated mango. Soil samples were collected in 0-0.2 and 0.2-0.4 m depths as well as leaf samples following sample grids. Ca, Mg, K, P, and N contents from soil and leaf samples were determined. Descriptive and geostatistics analyses were performed. Co-kriging was used for the delimitation of management zones. Positive spatial correlations were obtained between soil Ca2+ and leaf Ca contents (R2 = 0.80-0.93), soil K+ and leaf K contents (R2 = 0.35-0.61), and soil Mg2+ and leaf P contents (R2 = 0.51). Negative correlations were observed for soil Mg2+ and leaf Ca contents(R2 = 0.79-0.93) and soil Mg2+ and leaf K contents (R2 = 0.98). The soil 0-0.2 m depth had the greatest influence on mango Ca and K uptake. The negative correlation between soil Mg2+ and leaf Ca shows the competition existing in the plant uptake process. It was possible to delimit specific management zones using co-kriging for the three areas using soil and leaf data.

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