Register      Login
Crop and Pasture Science Crop and Pasture Science Society
Plant sciences, sustainable farming systems and food quality
RESEARCH ARTICLE

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

S. K. Behera A B , K. Suresh A , K. Ramachandrudu A , K. Manorama A and B. N. Rao A
+ Author Affiliations
- Author Affiliations

A Indian Institute of Oil Palm Research, Pedavegi, West Godavari District, Andhra Pradesh 534 450, India.

B Corresponding author. Email: sanjib_bls@rediffmail.com; sanjibkumarbehera123@gmail.com

Crop and Pasture Science 67(1) 109-116 https://doi.org/10.1071/CP15029
Submitted: 29 January 2015  Accepted: 13 July 2015   Published: 14 January 2016

Abstract

Spatial variability of leaf nutrients in oil palm (Elaeis guineensis Jacq.) plantations in Goa, Karnataka, Mizoram and Gujarat states of India were examined for implementation of site-specific fertilisation programs. Georeferenced leaf samples were collected randomly for the oil palm plantations. The leaf nutrient concentrations were assessed and analysed statistically and geostatistically. The concentrations of leaf nutrients such as nitrogen (N), phosphorus (P), potassium (K), calcium (Ca), magnesium (Mg), sulfur (S) and boron (B) in oil palm plantations varied widely at different locations. Leaf P concentration was positively and significantly correlated with S concentration at Goa, Karnataka and Gujarat. Positive and significant correlation between leaf Ca and Mg concentration was recorded at Mizoram and Gujarat. Geostatistical analysis of leaf nutrients showed different distribution patterns at different locations. This study revealed the need to determine spatial variability of nutrient status of oil palm plantations before planning a differential fertiliser program. Therefore, saving of nutrients could be achieved by adopting site-specific nutrient-management strategies.

Additional keywords: geostatistics, ordinary kriging, precision farming, saving inputs.


References

Anon. (2013) Oil world. ISTA Mielke. Available at: www.oilworld.biz/annual (accessed 24 June 2014)

Baxter SJ, Oliver MA, Gaunt J (2001) Understanding the spatial variation of mineral nitrogen and potentially available nitrogen at the field scale. In ‘Proceedings Third European Conference on Precision Agriculture’. Montpellier, France. (Eds G Grenier, S Blackmore) pp. 887–892. (International Society of Precision Agriculture: Monticello, IL, USA)

Behera SK, Shukla AK (2015) Spatial distribution of surface soil acidity, electrical conductivity, soil organic carbon content and exchangeable potassium, calcium and magnesium in some cropped acid soils of India. Land Degradation & Development 26, 71–79.
Spatial distribution of surface soil acidity, electrical conductivity, soil organic carbon content and exchangeable potassium, calcium and magnesium in some cropped acid soils of India.Crossref | GoogleScholarGoogle Scholar |

Behera SK, Suresh K (2013) Soil and leaf sampling in oil palm. In ‘Compendium of lectures on soil and leaf nutrient analysis in oil palm’. (Eds MV Prasad, SK Behera, B Mounika) pp. 14–19. (Directorate of Oil Palm Research: Pedavegi, AP, India)

Bhargava BS (2002) Leaf analysis for nutrient diagnosis, recommendation and management in fruit crops. Journal of the Indian Society of Soil Science 50, 352–373.

Bhargava BS, Raghupathi HB (2001) Analysis of plant material for macro- and micro-nutrients. In ‘Methods of analysis of soils, plants, waters and fertilizers’. (Ed. HLS Tandon) pp. 49–82. (Fertilizer Development and Consultation Organization: New Delhi)

Bocchi S, Castrignano A, Fornaro F, Maggiore T (2000) Application of factorial kriging for mapping soil variation at field scale. European Journal of Agronomy 13, 295–308.
Application of factorial kriging for mapping soil variation at field scale.Crossref | GoogleScholarGoogle Scholar |

Booij R, Uenk D, Lokhorst C, Sonneveld C (2001) Monitoring crop nitrogen status in potatoes, using crop light reflection. In ‘Proceedings Third European Conference on Precision Agriculture’. Montpellier, France. (Eds G Grenier, S Blackmore) pp. 893–899. (International Society of Precision Agriculture: Monticello, IL, USA)

Bouma J (1997) Precision agriculture: introduction to the spatial and temporal variability of environmental quality. In ‘Precision Agriculture: Spatial and Temporal Variability of Environmental Quality. Ciba Foundation Symposium 210’. (Eds JV Lake, GR Bock, JA Goode) pp. 5–17. (Wiley: Wageningen, The Netherlands)

Boyer DG, Wright RJ, Feldhake CM, Bligh DP (1996) Soil spatial variability in steeply sloping acid soil environment. Soil Science 161, 278–287.
Soil spatial variability in steeply sloping acid soil environment.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DyaK28XjtF2ntLo%3D&md5=4033a8664fcdb550239f559d76f8c421CAS |

Cambardella CA (1994) Field scale variability of soil properties in central Iowa soils. Soil Science Society of America Journal 58, 1501–1511.
Field scale variability of soil properties in central Iowa soils.Crossref | GoogleScholarGoogle Scholar |

Crist TO (1998) The spatial distribution of termites in shortgrass steppe: a geostatistical approach. Oecologia 114, 410–416.
The spatial distribution of termites in shortgrass steppe: a geostatistical approach.Crossref | GoogleScholarGoogle Scholar |

DOPR (2013) Annual Report 2012–13. Directorate of Oil Palm Research (DOPR), Pedavegi, AP, India.

Foroughifar H, Pakpour A, Jafarzadeh AA, Miransari M, Torabi H (2013) Using geostatistics and geographic information system techniques to characterize spatial variability of soil properties, including micronutrients. Communications in Soil Science and Plant Analysis 44, 1273–1281.
Using geostatistics and geographic information system techniques to characterize spatial variability of soil properties, including micronutrients.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3sXktlGgtbY%3D&md5=528f770f3ee8207d720d65f153257418CAS |

Goh KJ, Hardter R, Fairhust TH (2003) Fertilizer for maximum return. In ‘Oil palm: management for high and sustainable yields’. (Eds TH Fairhust, R Hardter) pp. 279–306. (International Potash Institute: Singapore)

Goovaerts P (1998) Geostatistical tools for characterizing the spatial variability of microbiological and physico-chemical soil parameters. Biology and Fertility of Soils 27, 315–334.
Geostatistical tools for characterizing the spatial variability of microbiological and physico-chemical soil parameters.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DyaK1cXlvFeguro%3D&md5=34796405a2e5409ebe1a647a6d37e993CAS |

Jackson ML (1973) ‘Soil chemical analysis.’ (Prentice Hall of India: New Delhi)

Jones JB, Wolf B, Mills HA (1991) ‘Plant analysis handbook.’ (Micro-Macro Publishing: Athens)

Jurado-Expósito M, López-Granados F, Garcia-Torres L, Garcia-Ferrer A, Sánchez de la Orden M, Atenciano S (2003) Multi-species weed spatial variability and site-specific management maps in cultivated sunflower. Weed Science 51, 319–328.
Multi-species weed spatial variability and site-specific management maps in cultivated sunflower.Crossref | GoogleScholarGoogle Scholar |

Li XF, Chen ZB, Chen HB, Chen ZQ (2011) Spatial distribution of soil nutrients and their response to land use in eroded area of South China. Procedia Environmental Sciences 10, 14–19.
Spatial distribution of soil nutrients and their response to land use in eroded area of South China.Crossref | GoogleScholarGoogle Scholar |

López-Granados F, Jurado-Expósito M, Alamo S, Garcia-Torres L (2004) Leaf nutrient spatial variability and site-specific fertilization maps within olive (Olea europaea L.) orchards. European Journal of Agronomy 21, 209–222.
Leaf nutrient spatial variability and site-specific fertilization maps within olive (Olea europaea L.) orchards.Crossref | GoogleScholarGoogle Scholar |

Ma BL, Morrison MJ, Dwyer LM (1996) Canopy light reflectance and field greenness to assess nitrogen fertilization and yield of maize. Agronomy Journal 88, 915–920.
Canopy light reflectance and field greenness to assess nitrogen fertilization and yield of maize.Crossref | GoogleScholarGoogle Scholar |

Machet JM, Beaudoin N, Mary B, Boffety D, Bernard M (2001) Characterization of the variability in grain production and quality within a winter wheat field. In ‘Proceedings Third European Conference on Precision Agriculture’. Montpellier, France. (Eds G Grenier, S Blackmore) pp. 821–825. (International Society of Precision Agriculture: Monticello, IL, USA)

Narasimha Rao B, Suresh K, Behera SK, Ramachandrudu K, Manorama K (2014) Nutrient management in oil palm. Technical Bulletin. DOPR, Pedavegi, AP, India.

Prasad MV, Sairam CV, Arulraj S, Jameema J (2012) Estimation of cost of production of oil palm in Andhra Pradesh. In ‘PLACROSYM XX. Abstracts’. Coimbatore. p. 136. (Organising Committee Plantation Crops Symposium XX)

Prasad MV, Sarkar A, Jameema J (2013) Performance of oil palm production technologies. Indian Research Journal of Extension Education 10, 10–15.

Pushparajah E, Chew PS (1979) Utilization of soil and plant analyses for plantation agriculture. In ‘Proceedings Malaysian Seminar on the Fertility and Management of Deforested Land’. (Eds JT Henry, L Liau) pp. 177–199. (Society of Agricultural Scientists: Kota Kinabalu, Sabah, Malaysia)

Raghupathi HB, Bhargava BS (1999) Preliminary nutrient norms for ‘Alphonso’ mango using DRIS. Indian Journal of Agricultural Sciences 69, 648–650.

Savita B, Raghupathi HB, Verma S, Anjaneyulu K (2013) Nutritional status of sapota (Manilkara achras M. Fosberg) gardens and optimum ranges of nutrients for higher production. Journal of the Indian Society of Soil Science 61, 112–116.

Silva CA, Bernardi ACC, Machado PLOA, Meirelles MSP, Carmo CAFS 2001. Relationship between georeferenced soybean yield and soil fertility properties (Parana State, Brazil). In ‘Proceedings Third European Conference on Precision Agriculture’. Montpellier, France. (Eds G Grenier, S Blackmore) pp. 857–862. (International Society of Precision Agriculture: Monticello, IL, USA)

Soil Survey Staff (2014) ‘Keys to Soil Taxonomy.’ 12th edn (USDA-Natural Resources Conservation Service: Washington, DC)

Tesfahunegn GB, Tamene L, Vlek LPG (2011) Catchment-scale spatial variability of soil properties and implications on site-specific soil management in northern Ethiopia. Soil & Tillage Research 117, 124–139.
Catchment-scale spatial variability of soil properties and implications on site-specific soil management in northern Ethiopia.Crossref | GoogleScholarGoogle Scholar |

von Uexkull HR, Fairhurst TH (1991) Fertilizing for high yield and quality: The oil palm. IPI Bulletin 12. International Potash Institute, Bern, Switzerland.

Walter JD, Hofman VL, Backer LF (1996) Site-specific sugar beet yield monitoring. In ‘Proceedings Third European Conference on Precision Agriculture’. Montpellier, France. (Eds G Grenier, S Blackmore) pp. 821–825. (International Society of Precision Agriculture: Monticello, IL, USA)

Webb MJ, Nelson PN, Rogers LG, Curry GN (2011) Site-specific fertilizer recommendations for oil palm smallholders using information from large plantations. Journal of Plant Nutrition and Soil Science 174, 311–320.
Site-specific fertilizer recommendations for oil palm smallholders using information from large plantations.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3MXktlSjsr4%3D&md5=87ff4fa04b24767ae9af9d9fecc9ebd2CAS |

Webster R, Oliver MA (1990) ‘Statistical methods in soil and land resource survey.’ (Oxford University Press: London)

Webster R, Oliver MA (2001) ‘Geostatistics for environmental scientists.’ (John Wiley and Sons, Ltd: Hoboken, NJ, USA)