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Soil, land care and environmental research
RESEARCH ARTICLE

Quantifying individual and collective influences of soil properties on crop yield

Rebecca Whetton A , Yifan Zhao B and Abdul M. Mouazen C D
+ Author Affiliations
- Author Affiliations

A Cranfield Soil and AgriFood Institute, Cranfield University, Bedfordshire MK43 0AL, UK.

B Through-life Engineering Services Institute, Cranfield University, Bedfordshire MK43 0AL, UK.

C Department of Soil Management, Ghent University, Coupure 653, 9000 Gent, Belgium.

D Corresponding author. Email: Abdul.Mouazen@UGent.be

Soil Research - https://doi.org/10.1071/SR16264
Submitted: 3 October 2016  Accepted: 2 June 2017   Published online: 20 July 2017

Abstract

Quantification of the agronomic influences of soil properties, collected at high sampling resolution, on crop yield is essential for site specific soil management. The objective of this study was to implement a novel Volterra Non-linear Regressive with eXogenous inputs (VNRX) model accounting for the linear and non-linear variability (VNRX-LN) to quantify causal factors affecting wheat yield in a 22-ha field with a waterlogging problem in Bedfordshire, UK. The VNRX-LN model was applied using high-resolution data of eight key soil properties (total nitrogen (TN), organic carbon, pH, available phosphorous, magnesium (Mg), calcium, moisture content and cation exchange capacity (CEC)). The data were collected with an on-line (tractor mounted) visible and near infrared spectroscopy sensor and used as multiple-input to the VNRX-LN model, whereas crop yield represented the single-output in the system. Results showed that the largest contributors to wheat yield were CEC, Mg and TN, with error reduction ratio contribution values of 14.6%, 4.69% and 1% respectively. The overall contribution of the soil properties considered in this study equalled 23.21%. This was attributed to a large area of the studied field having been waterlogged, which masked the actual effect of soil properties on crop yield. It is recommended that VNRX-LN is validated on a larger number of fields, where other crop yield affecting parameters e.g., crop disease, pests, drainage, topography and microclimate conditions should be taken into account.

Additional keywords: nonlinear parametric modelling, proximal soil sensing, VNRX-LN, yield-limiting factors.


References

Agegnehu G, Nelson P, Bird M (2016) Crop yield, plant nutrient uptake and soil physicochemical properties under organic soil amendments and nitrogen fertilization on Nitisols. Soil & Tillage Research 160, 1–13.
Crop yield, plant nutrient uptake and soil physicochemical properties under organic soil amendments and nitrogen fertilization on Nitisols.CrossRef |

Bergaya F, Vayer M (1997) CEC of clays: measurement by absorption of a copper ethylenediamine complex. Applied Clay Science 12, 275–280.
CEC of clays: measurement by absorption of a copper ethylenediamine complex.CrossRef | 1:CAS:528:DyaK2sXltVymsb0%3D&md5=306b3caef0930c944a61c7efbe85a378CAS |

Billings SA (2013) ‘Nonlinear system identification: NARMAX methods in the time, frequency, and spatio-temporal domains.’ (John Wiley & Sons: London)

Boyer J (1982) Plant productivity and environment. Science 218, 443–448.
Plant productivity and environment.CrossRef | 1:STN:280:DC%2BC3cvjvVahuw%3D%3D&md5=d5784a90247c619e170577a7ffce37c6CAS |

Bruulsema T (2015) ‘Plant Nutrition TODAY.’ (International Plant Nutrition Institute (IPNI): Georgia, USA)

Bryson RJ, Paveley ND, Clark WS, Sylvester-Bradley R, Scott RK (1997) Use of in-field measurements of green leaf area and incident radiation to estimate the effects of yellow rust epidemics on the yield of winter wheat. European Journal of Agronomy 7, 53–62.
Use of in-field measurements of green leaf area and incident radiation to estimate the effects of yellow rust epidemics on the yield of winter wheat.CrossRef |

Carlyle J (1993) Carbon in forested sandy soils: properties, processes, and the impact of forest management. New Zealand Journal of Forestry Science 23, 390–402.

Christy C (2008) Real-time measurement of soil attributes using on-the-go near infrared reflectance spectroscopy. Computers and Electronics in Agriculture 61, 10–19.
Real-time measurement of soil attributes using on-the-go near infrared reflectance spectroscopy.CrossRef |

Condon A, Giunta F (2003) Yield response of restricted-tillering wheat to transient waterlogging on duplex soils. Australian Journal of Agricultural Research 54, 957–967.
Yield response of restricted-tillering wheat to transient waterlogging on duplex soils.CrossRef |

Dhillon N, Samra J, Sadana U, Nielson D (1994) Spatial variability of soil test values in a typic Ustochrept. Soil Technology 7, 163–171.
Spatial variability of soil test values in a typic Ustochrept.CrossRef |

Frogbrook ZL, Oliver MA (2007) Identifying management zones in agricultural fields using spatially constrained classification of soil and ancillary data. Soil Use and Management 23, 40–51.
Identifying management zones in agricultural fields using spatially constrained classification of soil and ancillary data.CrossRef |

Halcro G, Corstanje R, Mouazen A (2013) Site-specific land management of cereal crops based on management zone delineation by proximal soil sensing. In ‘Precision agriculture ‘13’, 26–29 May 2013, Potsdam, Germany. (Ed. JV Stafford) pp. 475–481. (Wageningen Academic Publishers: The Netherlands)

Hazelton PA, Murphy BW (2007) ‘Interpreting soil test results: what do all the numbers mean Australia.’ (CSIRO Publishing: Melbourne, Australia)

Home Grown Cereals Authority (HGCA) (2014) Oilseed rape guide, s.l.: Agriculture and Horticulture Development Board. HGCA, Kenilworth, UK.

Hüner NPA, Hopkins WG (2008) ‘Introduction to plant physiology.’ 4th edn. (John Wiley & Sons, Inc.: New York, USA)

Khosla R, Inman D, Westfall DG, Reich RM, Frasier M, Mzuku M, Koch B, Hornung A (2008) A synthesis of multi-disciplinary research in precision agriculture: site-specific management zones in the semi-arid Western Great Plains of the USA. Precision Agriculture 9, 85–100.
A synthesis of multi-disciplinary research in precision agriculture: site-specific management zones in the semi-arid Western Great Plains of the USA.CrossRef |

Kipp S, Mistele B, Schmidhalter U (2014) The performance of active spectral reflectance sensors as influenced by measuring distance, device temperature and light intensity. Computers and Electronics in Agriculture 100, 24–33.
The performance of active spectral reflectance sensors as influenced by measuring distance, device temperature and light intensity.CrossRef |

Kodaira M, Shibusawa S (2013) Using a mobile real-time soil visible-near infrared sensor for high resolution soil property mapping. Geoderma 199, 64–79.
Using a mobile real-time soil visible-near infrared sensor for high resolution soil property mapping.CrossRef | 1:CAS:528:DC%2BC3sXlsVCqur4%3D&md5=3015a751573bf62517101853e90cf3f4CAS |

Kravchenko A, Bullock D (2000) Correlation of corn and soybean grain yield with topography and soil properties. Agronomy Journal 92, 75–83.
Correlation of corn and soybean grain yield with topography and soil properties.CrossRef |

Kuang B, Mouazen A (2011) Calibration of a visible and near infrared spectroscopy for soil analysis at field scales across three European farms. European Journal of Soil Science 62, 629–636.
Calibration of a visible and near infrared spectroscopy for soil analysis at field scales across three European farms.CrossRef | 1:CAS:528:DC%2BC3MXhtV2hs73N&md5=7dc693cc63e9d84738f9c77a161467f0CAS |

Kuang B, Mouazen AM (2013) Effect of spiking strategy and ratio on calibration of on-line visible and near infrared soil sensor for measurement in European farms. Soil & Tillage Research 128, 125–136.
Effect of spiking strategy and ratio on calibration of on-line visible and near infrared soil sensor for measurement in European farms.CrossRef |

Kuang B, Mahmood HS, Quraishi Z, Hoogmoed WB, Mouazen AM, Henten E (2012) Sensing soil properties in the laboratory, in situ, and on-line: a review. Advances in Agronomy 114, 155–223.
Sensing soil properties in the laboratory, in situ, and on-line: a review.CrossRef | 1:CAS:528:DC%2BC38Xhs12lsr%2FI&md5=48d20f1e7d85f5e5892b3ffc4aa61151CAS |

Kweon G, Lund E, Maxton C (2013) Soil organic matter and cation-exchange capacity sensing with on-the-go electrical conductivity and optical sensors. Geoderma 199, 80–89.
Soil organic matter and cation-exchange capacity sensing with on-the-go electrical conductivity and optical sensors.CrossRef | 1:CAS:528:DC%2BC3sXhtFSnt78%3D&md5=df1b616f5a5d99efdcf2deb3d77fff84CAS |

Lowenberg-DeBoer J, Aghib A (1999) Average return and risk characteristics of site specific P and K management: eastern corn belt on-farm trial results. Journal of Production Agriculture 12, 276–282.
Average return and risk characteristics of site specific P and K management: eastern corn belt on-farm trial results.CrossRef |

Maleki MR, Mouazena AM, Ketelaerea BD, Ramona H, Baerdemaekera JD (2008) On-the-go variable-rate phosphorus fertilisation based on a visible and near infrared soil sensor. Biosystems Engineering 99, 35–46.
On-the-go variable-rate phosphorus fertilisation based on a visible and near infrared soil sensor.CrossRef |

Marín-González O, Kuang B, Quraishi MZ, Munóz-García MA, Mouazen AM (2013) On-line measurement of soil properties without direct spectral response in near infrared spectral range. Soil & Tillage Research 132, 21–29.
On-line measurement of soil properties without direct spectral response in near infrared spectral range.CrossRef |

Matheron G (1963) Principles of geostatistics. Economic Geology and the Bulletin of the Society of Economic Geologists 58, 1246–1266.
Principles of geostatistics.CrossRef | 1:CAS:528:DyaF2cXltFKiug%3D%3D&md5=f19e436540ef0b61c9e592bb20ac67b0CAS |

Mengel K, Kirkby EA, Kosegarten H, Appel T (Eds) (1987) Copper, further elements of importance. In ‘Principles of plant nutrition’. 4th edn. pp. 537–588. (International Potash Institute: Berne, Switzerland)

Mouazen A (2006) Soil Survey Device. International publication published under the patent cooperation treaty (PCT). World Intellectual Property Organization, International Bureau. International Publication Number: WO2006/015463; PCT/BE2005/000129; IPC: G01N21/00; G01N21/00.

Mouazen AM, Kuang B (2016) On-line visible and near infrared spectroscopy for in-field phosphorous management. Soil & Tillage Research 155, 471–477.
On-line visible and near infrared spectroscopy for in-field phosphorous management.CrossRef |

Mouazen AM, De Baerdemaeker J, Ramon H (2005) Towards development of on-line soil moisture content sensor using a fibre-type NIR spectrophotometer. Soil & Tillage Research 80, 171–183.
Towards development of on-line soil moisture content sensor using a fibre-type NIR spectrophotometer.CrossRef |

Mouazen AM, De Baerdemaeker J, Ramon H (2006) Effect of wavelength range on the measurement accuracy of some selected soil constituents using visual-near infrared spectroscopy. Journal of Near Infrared Spectroscopy 14, 189–199.
Effect of wavelength range on the measurement accuracy of some selected soil constituents using visual-near infrared spectroscopy.CrossRef | 1:CAS:528:DC%2BD28XnslCmsLc%3D&md5=bd41318f2784c2fa3c293d4e4834b9b5CAS |

Mouazen AM, Maleki MR, Cockx L, Van Meirvenned M, Van Holm LHJ, Merckx R, De Baerdemaeker J, Ramon H (2009) Optimum three-point linkage set up for improving the quality of soil spectra and the accuracy of soil phosphorous measured using an on-line visible and near infrared sensor. Soil & Tillage Research 103, 144–152.
Optimum three-point linkage set up for improving the quality of soil spectra and the accuracy of soil phosphorous measured using an on-line visible and near infrared sensor.CrossRef |

Mulla D (2013) Twenty five years of remote sensing in precision agriculture: key advances and remaining knowledge gaps. Biosystems Engineering 114, 358–371.
Twenty five years of remote sensing in precision agriculture: key advances and remaining knowledge gaps.CrossRef |

Raun WR, Johnson GV, Lees HL, Sembiring H, Phillips SB, Solie JB, Stone ML, Whitney RW (1998) Microvariability in soil test, plant nutrient and yield parameters in bermudagrass. Soil Science Society of America Journal 62, 683–690.
Microvariability in soil test, plant nutrient and yield parameters in bermudagrass.CrossRef | 1:CAS:528:DyaK1cXks1eqsb8%3D&md5=284a2cf6944a96f89fbd8684827f5844CAS |

Shibusawa S, Imade Anom SW, Sato S, Sasao A, Hirako S (2001) Soil mapping using the real-time soil spectrophotometer. In ‘Third European Conference on Precision Agriculture’, 18–20 June 2001, agro Montpellier, Ecole Nationale Supérieure Agronomique de Montpellier. (Eds G Grenier, S Blackmore) pp. 497–508. (ECPA: Montpellier, France)

Soil Survey Staff (1999) Soil taxonomy – a basic system of soil classification for making and interpreting soil surveys.’ 2nd edn. Agricultural Handbook 436. (Natural Resources Conservation Service, USDA: Washington DC)

Stenberg B, Viscarra Rossel R, Mouazen AM, Wetterlind J (2010) Visible and near infrared spectroscopy in soil science. Advances in Agronomy 107, 163–215.

The British Standards Institution (1995a) British Standard 7755 Section 3.8. Soil quality. Chemical methods. Determination of organic and total carbon after dry combustion (elementary analysis). Equivalent to ISO 10694 : 1995. The British Standards Institution, London, UK.

The British Standards Institution (1995b) British Standard 7755 Section 3.2. Determination of pH. Equivalent to ISO 10390 : 2005. The British Standards Institution, London, UK.

The British Standards Institution (1995c) British standard 7755 Section 3.6. Determination of Phosphorous. Spectrometric determination of phosphorous soluble in sodium hydrogen carbonate solution. Equivalent to ISO 11263 : 1994. The British Standards Institution, London, UK.

The British Standards Institution (1996) British standard 7755 Section 3.12. Determination of the potential cation exchange capacity and exchangeable cations using barium chloride solution buffered at pH=8.1. Equivalent to ISO 13536 : 1995. The British Standards Institution, London, UK.

The British Standards Institution (2008) Soil improvers and growing media: sample preparation for chemical and physical tests, determination of dry matter content, moisture content and laboratory compacted bulk density. Equivalent to ISO 13040 : 2007. The British Standards Institution, London, UK.

Zhao Y, Billings SA, Wei H, Sarrigiannis P (2012) Tracking time-varying causality and directionality of information flow using an error reduction ratio test with applications to electroencephalography data. Physical Review. E 86, 051919
Tracking time-varying causality and directionality of information flow using an error reduction ratio test with applications to electroencephalography data.CrossRef |



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