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Infrared Spectroscopy Keith D Shepherd. Optimizing Fertilizer Recommendations for Africa (OFRA) Project Inception 25-27 November 2013. Surveillance Science.

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Infrared Spectroscopy

Keith D Shepherd

Optimizing Fertilizer Recommendations for Africa (OFRA) Project Inception

25-27 November 2013

surveillance science
Surveillance Science

UNEP. 2012. Land Health Surveillance: An Evidence-Based Approach to Land Ecosystem Management. Illustrated with a Case Study in the West Africa Sahel. United Nations Environment Programme, Nairobi.

  • Increase sample density in landscapes
  • Direct prediction of soil-plant responses to management
  • Measure frequency of problems and associated risk factors in populations using statistical sampling designs & standardized measurement protocols

Shepherd KD and Walsh MG (2007) Infrared spectroscopy—enabling an evidence-based diagnostic surveillance approach to agricultural and environmental management in developing countries. Journal of Near Infrared Spectroscopy 15: 1-19.

spectral shape relates to basic soil properties
Spectral shape relates to basic soil properties
  • Mineral composition
  • Iron oxides
  • Organic matter
  • Water (hydration, hygroscopic, free)
  • Carbonates
  • Soluble salts
  • Particle size distribution

 Functional properties

infrared spectroscopy
Infrared spectroscopy

Dispersive VNIR


FT-MIR Robotic

FT-MIR Portable

Brown D, Shepherd KD, Walsh MG (2006). Global soil characterization using a VNIR diffuse reflectance library and boosted regression trees. Geoderma 132:273–290.

Shepherd KD and Walsh MG (2007) Infrared spectroscopy—enabling an evidence-based diagnostic surveillance approach to agricultural and environmental management in developing countries. Journal of Near Infrared Spectroscopy 15: 1-19.

Terhoeven-Urselmans T, Vagen T-G, Spaargaren O, Shepherd KD. 2010. Prediction of soil fertility properties from a globally distributed soil mid-infrared spectral library. Soil Sci. Soc. Am. J. 74:1792–1799

Handheld MIR ?

Mobile phone cameras ?


Soil organic carbon

  • Spectralpretreatments
  • Derivatives, smoothing
  • Data miningalgorithms:
  • PLS +
  • SupportVectorMachines
  • Neural networks
  • MultivariateAdaptiveRegressionSplines
  • BoostedRegressionTrees
  • RandomForests
  • BayesianAdditiveRegressionTrees


Out-of-bag validation

Soil pH

R package soil.spec

Soil spectral file conversion, data exploration and regression functions


Submit batch of spectra online

  • Uncertainties estimated for each sample
  • Samples with large error submitted for reference analysis
  • Calibration models improve as more samples submitted
  • All subscribers benefit

Spectral fingerprinting

X-ray diffraction spectroscopy

Total X-ray fluorescence spectroscopy

Infrared spectroscopy

spectral lab network
Spectral Lab Network
  • Planned
  • Eggerton University, Kenya
  • MoA, Liberia
  • IER, Arusha, Tanzania
  • FMARD, Nigeria
  • NIFOR, Nigeria
  • CNLS, Nairobi
  • BLGG, Kenya (mobile labs)
  • IAMM, Mozambique
  • AfSIS, Sotuba, Mali
  • AfSIS, Salien, Tanzania
  • AfSIS, Chitedze, Malawi
          • CNLS, Nairobi, Kenya
          • ICRAF, Nairobi, Kenya
  • CNRA, Abidjan, Cote D’Ivoire
  • KARI, Nairobi, Kenya
  • ICRAF, Yaounde, Cameroon
  • ObafemiAwolowo University, Ibadan, Nigeria
  • IAR, Zaria, Nigeria
  • ATA, Addis Ababa, Ethiopia (+ 5 on order)
  • IITA, Ibadan, Nigeria
  • IITA, Yaounde, Cameroon
  • ICRAF, Nairobi, Kenya
plant compost fertilizer analysis
Plant, compost, fertilizer analysis
  • IR for plant N/protein, organic resource quality/decomposition
  • Handheld XRF for plant P, K, Ca, Mg, micronutrients (in progress)
  • Handheld XRF for fertilizer quality control (in progress)

Shepherd KD, Palm CA, Gachengo CN and Vanlauwe B (2003) Rapid characterization of organic resource quality for soil and livestock management in tropical agroecosystems using near infrared spectroscopy. Agronomy Journal 95:1314-1322.

Shepherd, KD, Vanlauwe B, Gachengo CN Palm CA (2005) Decomposition and mineralization of organic residues predicted using near infrared spectroscopy. Plant and Soil 277:315-333.

calibrating plant response to ir
Calibrating plant response to IR

mtt finland foodafrica soil micronutrients
MTT-Finland FoodAfricaSoil Micronutrients

Evidence-based micronutrient management

Healthy crops

Healthy livestock

Healthy soils

Healthy people

land health surveillance out scaling
Land HealthSurveillance Out-scaling

Global-Continental Monitoring Systems

Vital signs

CRP pan-tropical sites


Regional Information Systems

National surveillance


Tibetan Plateau/ Mekong

Evergreen Ag / Horn of Africa


Project baselines

SLM Cameroon

Parklands Malawi

Rangelands E/W Africa

Cocoa - CDI


critical success factors
Critical success factors
  • Consistent field sampling protocol
  • Soil-Plant sample labeling, drying, preparation, sub-sampling, shipping, back-up storage
  • Data management, linking
  • Judicious selection of samples for reference analysis
  • Consistency of reference analyses
  • Use MIR as a soil covariate
  • Direct calibration of MIR to plant/soil response