18 Jan 2021

18 Jan 2021

Review status: this preprint is currently under review for the journal SOIL.

Estimation of soil properties with mid-infrared soil spectroscopy across yam production landscapes in West Africa

Philipp Baumann1, Juhwan Lee2, Emmanuel Frossard3, Laurie Paule Schönholzer3, Lucien Diby4, Valérie Kouamé Hgaza5,6, Delwende Innocent Kiba3,7, Andrew Sila8, Keith Sheperd8, and Johan Six1 Philipp Baumann et al.
  • 1Group of Sustainable Agroecosystems, Institute of Agricultural Sciences, ETH Zurich, 8092 Zürich, Switzerland
  • 2Department of Agronomy and Medicinal Plant Resources, Gyeongnam National University of Science and Technology, Jinju, Republic of Korea
  • 3Group of Plant Nutrition, Institute of Agricultural Sciences, ETH Zurich, 8315 Lindau, Switzerland
  • 4World Agroforestry Centre (ICRAF), Côte d’Ivoire Country Programme, BP 2823 Abidjan, Ivory Coast
  • 5Centre Suisse de Recherches Scientifiques en Côte d’ivoire, 01 BP 1303 Abidjan, Ivory Coast
  • 6Département d’Agrophysiologie des Plantes, Université Peleforo Gon Coulibaly, BP 1328 Korhogo, Ivory Coast
  • 7Institut de l’Environnement et Recherches Agricoles, 01 BP 476 Ouagadougou, Burkina Faso
  • 8Land Health Decisions, World Agroforestry Centre (ICRAF), Nairobi, Kenya

Abstract. Low soil fertility is challenging the sustainable production of staple crops in the yam belt of West Africa. Quantitative soil measures are needed to assess soil fertility decline and to improve crop fertilization management in the region. We developed and tested a mid-infrared (mid-IR) soil spectral library to enable timely and cost-efficient assessments of soil properties. Our collection included 80 soil samples from four landscapes (10 km × 10 km) and 20 fields/landscape across a gradient from humid forest to savanna, and 14 additional samples from one landscape that had been sampled within the Land Health Degradation Framework. We derived partial least square regression models to estimate soil properties with spectra.The models produced accurate cross-validated estimates of total carbon, total nitrogen, total sulfur, total iron, total aluminum, total potassium, total calcium, exchangeable calcium, effective cation exchange capacity, diethylenetriaminepentaacetic acid (DTPA) extractable iron and clay content (R2 > 0.75). The estimates of total zinc, pH, exchangeable magnesium, bioavailable copper and manganese were less predictable (R2 > 0.50). Our results confirm that mid-IR spectroscopy is a reliable and quick method assess the regional-scale variation in most soil properties, especially the ones closely associated with soil organic matter. Although the relatively small mid-IR library shows satisfactory performance, we expect that frequent but small model updates will be needed to adapt the library to the variation of soil quality attributes within individual fields in the regions and their temporal fluctuations.

Philipp Baumann et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • AC1: 'Comment on soil-2020-100', Philipp Baumann, 20 Jan 2021
  • EC1: 'Comment on soil-2020-100', Stefan Hauser, 18 Apr 2021
  • RC1: 'Comment on soil-2020-100', Anonymous Referee #1, 20 Apr 2021
  • RC2: 'Comment on soil-2020-100', Stefan Hauser, 23 Apr 2021

Philipp Baumann et al.

Data sets

philipp-baumann/yamsys-soilspec-publication: Pre-release of spectral models for the publication of the soil spectral library of the West African yam belt (Version v0.1.0-beta). Zenodo Philipp Baumann

Model code and software

philipp-baumann/simplerspec: Beta release simplerspec 0.1.0 for zenodo (Version v0.1.0-beta). Zenodo Philipp Baumann

Philipp Baumann et al.


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Short summary
This work delivers openly accessible and validated calibrations for diagnosing 26 soil properties based on mid-infrared spectroscopy. These were developed for four regions in Burkina Faso and Ivory Coast, including 80 fields of smallholder farmers. The models can help to site-specifically and cost-efficiently monitor soil quality and fertility constraints to ameliorate soils and yields of yam or other staple crops in the four regions in between the humid forest and the northern Guinean savanna.