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Kristin Piikki
The Alliance of Bioversity International and the International Center for Tropical Agriculture (CIAT), c/o ICIPE—International Centre of Insect Physiology and Ecology, Duduville Campus Off Kasarani Road, P.O. Box 823-0062, Nairobi 0062, Kenya

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Review
Published: 22 January 2021 in Sustainability
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Opportunities exist for adoption of precision agriculture technologies in all parts of the world. The form of precision agriculture may vary from region to region depending on technologies available, knowledge levels and mindsets. The current review examined research articles in the English language on precision agriculture practices for increased productivity among smallholder farmers in Sub-Saharan Africa. A total of 7715 articles were retrieved and after screening 128 were reviewed. The results indicate that a number of precision agriculture technologies have been tested under SSA conditions and show promising results. The most promising precision agriculture technologies identified were the use of soil and plant sensors for nutrient and water management, as well as use of satellite imagery, GIS and crop-soil simulation models for site-specific management. These technologies have been shown to be crucial in attainment of appropriate management strategies in terms of efficiency and effectiveness of resource use in SSA. These technologies are important in supporting sustainable agricultural development. Most of these technologies are, however, at the experimental stage, with only South Africa having applied them mainly in large-scale commercial farms. It is concluded that increased precision in input and management practices among SSA smallholder farmers can significantly improve productivity even without extra use of inputs.

ACS Style

Cecilia Onyango; Justine Nyaga; Johanna Wetterlind; Mats Söderström; Kristin Piikki. Precision Agriculture for Resource Use Efficiency in Smallholder Farming Systems in Sub-Saharan Africa: A Systematic Review. Sustainability 2021, 13, 1158 .

AMA Style

Cecilia Onyango, Justine Nyaga, Johanna Wetterlind, Mats Söderström, Kristin Piikki. Precision Agriculture for Resource Use Efficiency in Smallholder Farming Systems in Sub-Saharan Africa: A Systematic Review. Sustainability. 2021; 13 (3):1158.

Chicago/Turabian Style

Cecilia Onyango; Justine Nyaga; Johanna Wetterlind; Mats Söderström; Kristin Piikki. 2021. "Precision Agriculture for Resource Use Efficiency in Smallholder Farming Systems in Sub-Saharan Africa: A Systematic Review." Sustainability 13, no. 3: 1158.

Review
Published: 15 December 2020 in Soil Use and Management
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We performed a systematic mapping of validation methods used in digital soil mapping (DSM), in order to gain an overview of current practices and make recommendations for future publications on DSM studies. A systematic search and screening procedure, largely following the RepOrting standards for Systematic Evidence Syntheses (ROSES) protocol, was carried out. It yielded a database of 188 peer‐reviewed DSM studies from the past two decades, all written in English and all presenting a raster map of a continuous soil property. Review of the full‐texts showed that most publications (97%) included some type of map validation, while just over one‐third (35%) estimated map uncertainty. Most commonly, a combination of multiple (existing) soil sampe datasets was used and the resulting maps were validated by single data‐splitting or cross‐validation. It was common for essential information to be lacking in method descriptions. This is unfortunate, as lack of information on sampling design (missing in 25% of 188 studies) and sample support (missing in 45% of 188 studies) makes it difficult to interpret what derived validation metrics represent, compromising their usefulness. Therefore, we present a list of method details that should be provided in DSM studies. We also provide a detailed summary of the 28 validation metrics used in published DSM studies, how to interpret the values obtained and whether the metrics can be compared between datasets or soil attributes.

ACS Style

Kristin Piikki; Johanna Wetterlind; Mats Söderström; Bo Stenberg. Perspectives on validation in digital soil mapping of continuous attributes—A review. Soil Use and Management 2020, 37, 7 -21.

AMA Style

Kristin Piikki, Johanna Wetterlind, Mats Söderström, Bo Stenberg. Perspectives on validation in digital soil mapping of continuous attributes—A review. Soil Use and Management. 2020; 37 (1):7-21.

Chicago/Turabian Style

Kristin Piikki; Johanna Wetterlind; Mats Söderström; Bo Stenberg. 2020. "Perspectives on validation in digital soil mapping of continuous attributes—A review." Soil Use and Management 37, no. 1: 7-21.

Conference paper
Published: 04 August 2020 in Lecture Notes in Electrical Engineering
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CropSAT is an interactive decision support system (DSS) that provides vegetation index (VI) maps from Sentinel-2 data all across the globe and lets users delineate fields, design variable-rate application of user specified inputs (mainly nitrogen, but also e.g. fungicides or growth regulators) based on the VI maps. The CropSAT DSS was initially developed in a research project at the Swedish University of Agricultural Sciences (SLU), and has since its launch in 2015 been continuously developed in a private-public-partnership between SLU, private companies and the Swedish Board of Agriculture. Now it has global coverage, is continuously updated with new satellite images, and is provided free-of-charge in multiple languages (including Arabic and French). The present study aims at describing the CropSAT systems, summarizing research results from the ongoing developmental process and pointing to opportunities for applications in precision agriculture, e.g. in Morocco and other countries in North Africa.

ACS Style

Omran Alshihabi; Kristin Piikki; Mats Söderström. CropSAT – A Decision Support System for Practical Use of Satellite Images in Precision Agriculture. Lecture Notes in Electrical Engineering 2020, 415 -421.

AMA Style

Omran Alshihabi, Kristin Piikki, Mats Söderström. CropSAT – A Decision Support System for Practical Use of Satellite Images in Precision Agriculture. Lecture Notes in Electrical Engineering. 2020; ():415-421.

Chicago/Turabian Style

Omran Alshihabi; Kristin Piikki; Mats Söderström. 2020. "CropSAT – A Decision Support System for Practical Use of Satellite Images in Precision Agriculture." Lecture Notes in Electrical Engineering , no. : 415-421.

Review
Published: 11 February 2020 in Grassland Science
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Grasslands occupy almost half of the world's land area. Soil organic carbon (SOC) is a key indicator of soil fertility and grassland productivity. Increasing SOC stocks (so‐called SOC sequestration) improves soil fertility and contributes to climate change mitigation by binding atmospheric carbon dioxide (CO2). Grasslands constitute about 70% of all agricultural land, but their potential for SOC sequestration is largely unknown. This review paper quantitatively summarizes observation‐based studies on the SOC sequestration potential of grasslands in six East African countries (Burundi, Ethiopia, Kenya, Rwanda, Tanzania and Uganda) and seeks to identify knowledge gaps related to SOC sequestration potential in the region. In the studies reviewed, SOC stocks in grasslands range from 3 to 93 Mg C/ha in the upper 0.3 m of the soil profile, while SOC sequestration rate ranges from 0.1 to 3.1 Mg C ha‐1 year‐1 under different management strategies. Grazing management is reported to have a considerable impact on SOC sequestration rates, and grassland regeneration and protection are recommended as options to stimulate SOC sequestration. However, a very limited number of relevant studies are available (n = 23) and there is a need for fundamental information on SOC sequestration potential in the region. The effectiveness of potential incentive mechanisms, such as payments for environmental services, to foster uptake of SOC‐enhancing practices should also be assessed.

ACS Style

Bezaye Tessema; Rolf Sommer; Kristin Piikki; Mats Söderström; Sara Namirembe; An Notenbaert; Lulseged Tamene; Sylvia Sarah Nyawira; Birthe Paul. Potential for soil organic carbon sequestration in grasslands in East African countries: A review. Grassland Science 2020, 66, 135 -144.

AMA Style

Bezaye Tessema, Rolf Sommer, Kristin Piikki, Mats Söderström, Sara Namirembe, An Notenbaert, Lulseged Tamene, Sylvia Sarah Nyawira, Birthe Paul. Potential for soil organic carbon sequestration in grasslands in East African countries: A review. Grassland Science. 2020; 66 (3):135-144.

Chicago/Turabian Style

Bezaye Tessema; Rolf Sommer; Kristin Piikki; Mats Söderström; Sara Namirembe; An Notenbaert; Lulseged Tamene; Sylvia Sarah Nyawira; Birthe Paul. 2020. "Potential for soil organic carbon sequestration in grasslands in East African countries: A review." Grassland Science 66, no. 3: 135-144.

Journal article
Published: 14 January 2020 in Sensors
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Portable X-ray fluorescence (PXRF) measurements on 1520 soil samples were used to create national prediction models for copper (Cu), zinc (Zn), and cadmium (Cd) concentrations in agricultural soil. The models were validated at both national and farm scales. Multiple linear regression (MLR), random forest (RF), and multivariate adaptive regression spline (MARS) models were created and compared. National scale cross-validation of the models gave the following R2 values for predictions of Cu (R2 = 0.63), Zn (R2 = 0.92), and Cd (R2 = 0.70) concentrations. Independent validation at the farm scale revealed that Zn predictions were relatively successful regardless of the model used (R2 > 0.90), showing that a simple MLR model can be sufficient for certain predictions. However, predictions at the farm scale revealed that the non-linear models, especially MARS, were more accurate than MLR for Cu (R2 = 0.94) and Cd (R2 = 0.80). These results show that multivariate modelling can compensate for some of the shortcomings of the PXRF device (e.g., high limits of detection for certain elements and some elements not being directly measurable), making PXRF sensors capable of predicting elemental concentrations in soil at comparable levels of accuracy to conventional laboratory analyses.

ACS Style

Karl Adler; Kristin Piikki; Mats Söderström; Jan Eriksson; Omran Alshihabi. Predictions of Cu, Zn, and Cd Concentrations in Soil Using Portable X-Ray Fluorescence Measurements. Sensors 2020, 20, 474 .

AMA Style

Karl Adler, Kristin Piikki, Mats Söderström, Jan Eriksson, Omran Alshihabi. Predictions of Cu, Zn, and Cd Concentrations in Soil Using Portable X-Ray Fluorescence Measurements. Sensors. 2020; 20 (2):474.

Chicago/Turabian Style

Karl Adler; Kristin Piikki; Mats Söderström; Jan Eriksson; Omran Alshihabi. 2020. "Predictions of Cu, Zn, and Cd Concentrations in Soil Using Portable X-Ray Fluorescence Measurements." Sensors 20, no. 2: 474.

Review paper
Published: 04 January 2020 in Environmental Geochemistry and Health
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A synthesis of available agronomic datasets and peer-reviewed scientific literature was conducted to: (1) assess the status of micronutrients in sub-Saharan Africa (SSA) arable soils, (2) improve the understanding of the relations between soil quality/management and crop nutritional quality and (3) evaluate the potential profitability of application of secondary and micronutrients to key food crops in SSA, namely maize (Zea mays L.), beans (Phaseolus spp. and Vicia faba L.), wheat (Triticum aestivum L.) and rice (Oryza sativa L.). We found that there is evidence of widespread but varying micronutrient deficiencies in SSA arable soils and that simultaneous deficiencies of multiple elements (co-occurrence) are prevalent. Zinc (Zn) predominates the list of micronutrients that are deficient in SSA arable soils. Boron (B), iron (Fe), molybdenum (Mo) and copper (Cu) deficiencies are also common. Micronutrient fertilization/agronomic biofortification increases micronutrient concentrations in edible plant organs, and it was profitable to apply fertilizers containing micronutrient elements in 60–80% of the cases. However, both the plant nutritional quality and profit had large variations. Possible causes of this variation may be differences in crop species and cultivars, fertilizer type and application methods, climate and initial soil conditions, and soil chemistry effects on nutrient availability for crop uptake. Therefore, micronutrient use efficiency can be improved by adapting the rates and types of fertilizers to site-specific soil and management conditions. To make region-wide nutritional changes using agronomic biofortification, major policy interventions are needed.

ACS Style

J. Kihara; P. Bolo; M. Kinyua; J. Rurinda; Kristin Piikki. Micronutrient deficiencies in African soils and the human nutritional nexus: opportunities with staple crops. Environmental Geochemistry and Health 2020, 42, 3015 -3033.

AMA Style

J. Kihara, P. Bolo, M. Kinyua, J. Rurinda, Kristin Piikki. Micronutrient deficiencies in African soils and the human nutritional nexus: opportunities with staple crops. Environmental Geochemistry and Health. 2020; 42 (9):3015-3033.

Chicago/Turabian Style

J. Kihara; P. Bolo; M. Kinyua; J. Rurinda; Kristin Piikki. 2020. "Micronutrient deficiencies in African soils and the human nutritional nexus: opportunities with staple crops." Environmental Geochemistry and Health 42, no. 9: 3015-3033.

Review
Published: 01 January 2020 in South African Journal of Plant and Soil
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Cropland soils are considered to have the potential to sequester atmospheric CO2 through agronomic best management practices (BMPs). To estimate this potential in East Africa, the authors reviewed 69 published studies from Ethiopia, Kenya, Rwanda, Tanzania, Uganda, and Burundi assessing the effect of land use conversion from native vegetation to cropland on soil organic carbon (SOC) and the extent to which carbon sequestration is feasible through BMPs. Reported losses of SOC in the top 30 cm of the soil profile in short (25 years) term were 6.7 ± 6.0, 13.0 ± 9.2, and 2.8 ± 1.0 t C ha–1 year–1, respectively, for forest-to-cropland; and 16.0, 2.1 ± 2.2 and 0.3 ± 0.8 t C ha–1 year–1 respectively, for woodland-to-cropland conversion. Duration to steady-state SOC was 21–38 years for forest-to-cropland conversion. Short-term SOC sequestration (t C ha–1 year–1) in the 0–30 cm layer as a result of BMPs was 19.7 ± 3.9 from crop residues, 14.8 ± 8.7 from farmyard manure, 3.5 ± 4.5 from inorganic fertilizers, 2.7 from agroforestry, and 2.5 from improved fallow. However, the studies reviewed were mostly short-term and concentrated to a few locations. Future research should address these gaps.

ACS Style

S Namirembe; K Piikki; R Sommer; M Söderström; B Tessema; Ss Nyawira. Soil organic carbon in agricultural systems of six countries in East Africa – a literature review of status and carbon sequestration potential. South African Journal of Plant and Soil 2020, 37, 35 -49.

AMA Style

S Namirembe, K Piikki, R Sommer, M Söderström, B Tessema, Ss Nyawira. Soil organic carbon in agricultural systems of six countries in East Africa – a literature review of status and carbon sequestration potential. South African Journal of Plant and Soil. 2020; 37 (1):35-49.

Chicago/Turabian Style

S Namirembe; K Piikki; R Sommer; M Söderström; B Tessema; Ss Nyawira. 2020. "Soil organic carbon in agricultural systems of six countries in East Africa – a literature review of status and carbon sequestration potential." South African Journal of Plant and Soil 37, no. 1: 35-49.

Journal article
Published: 01 October 2019 in Geoderma
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ACS Style

Kristin Piikki; Mats Söderström. Digital soil mapping of arable land in Sweden – Validation of performance at multiple scales. Geoderma 2019, 352, 342 -350.

AMA Style

Kristin Piikki, Mats Söderström. Digital soil mapping of arable land in Sweden – Validation of performance at multiple scales. Geoderma. 2019; 352 ():342-350.

Chicago/Turabian Style

Kristin Piikki; Mats Söderström. 2019. "Digital soil mapping of arable land in Sweden – Validation of performance at multiple scales." Geoderma 352, no. : 342-350.

Journal article
Published: 25 July 2019 in Sustainability
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Soil organic carbon (SOC) sequestration is important in the global carbon cycle and an integral part of many initiatives and policies to mitigate climate change. For efficient targeting of measures leading to SOC sequestration, it is necessary to know the actual SOC content (%) and a realistic target SOC content (in contrast to the saturation content, which may not be easily achievable) under local biophysical and socioeconomic conditions. We developed a new method for the practical assessment of achievable SOC sequestration concerning soil texture based on a non-linear boundary plane approach, also applicable for mapping of SOC sequestration hotspots. The method was tested at two spatial scales (a 125 km2 catchment and a 4 km2 sub-area of that catchment) in a region in Western Kenya characterized by smallholder farming. Moreover, we assessed the associated benefits of increasing the SOC content from a crop production perspective and found significant correlations between SOC and other soil properties (pH, cation exchange capacity, and various plant-available macro- and micronutrients). This indicates a possible improvement in soil fertility when the SOC content is raised to the modeled target levels, which should be attainable without major changes in land use or agricultural systems.

ACS Style

Kristin Piikki; Mats Söderström; Rolf Sommer; Mayesse Da Silva; Sussy Munialo; Wuletawu Abera. A Boundary Plane Approach to Map Hotspots for Achievable Soil Carbon Sequestration and Soil Fertility Improvement. Sustainability 2019, 11, 4038 .

AMA Style

Kristin Piikki, Mats Söderström, Rolf Sommer, Mayesse Da Silva, Sussy Munialo, Wuletawu Abera. A Boundary Plane Approach to Map Hotspots for Achievable Soil Carbon Sequestration and Soil Fertility Improvement. Sustainability. 2019; 11 (15):4038.

Chicago/Turabian Style

Kristin Piikki; Mats Söderström; Rolf Sommer; Mayesse Da Silva; Sussy Munialo; Wuletawu Abera. 2019. "A Boundary Plane Approach to Map Hotspots for Achievable Soil Carbon Sequestration and Soil Fertility Improvement." Sustainability 11, no. 15: 4038.

Conference paper
Published: 08 July 2019 in Precision agriculture ’19
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ACS Style

K. Piikki; Mats Söderström; H. Stadig; J. Martinsson. Automated mixed-scale data fusion for mapping of within-field variation in a national decision support system - the example of pH correction. Precision agriculture ’19 2019, 1 .

AMA Style

K. Piikki, Mats Söderström, H. Stadig, J. Martinsson. Automated mixed-scale data fusion for mapping of within-field variation in a national decision support system - the example of pH correction. Precision agriculture ’19. 2019; ():1.

Chicago/Turabian Style

K. Piikki; Mats Söderström; H. Stadig; J. Martinsson. 2019. "Automated mixed-scale data fusion for mapping of within-field variation in a national decision support system - the example of pH correction." Precision agriculture ’19 , no. : 1.

Journal article
Published: 17 May 2018 in Sustainability
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Recent estimates show that one third of the world’s land and water resources are highly or moderately degraded. Global economic losses from land degradation (LD) are as high as USD $10.6 trillion annually. These trends catalyzed a call for avoiding future LD, reducing ongoing LD, and reversing past LD, which has culminated in the adoption of Sustainable Development Goal (SDG) Target 15.3 which aims to achieve global land degradation neutrality (LDN) by 2030. The political momentum and increased body of scientific literature have led to calls for a ‘new science of LDN’ and highlighted the practical challenges of implementing LDN. The aim of the present study was to derive LDN soil organic carbon (SOC) stock baseline maps by comparing different digital soil mapping (DSM) methods and sampling densities in a case study (Otjozondjupa, Namibia) and evaluate each approach with respect to complexity, cost, and map accuracy. The mean absolute error (MAE) leveled off after 100 samples were included in the DSM models resulting in a cost tradeoff for additional soil sample collection. If capacity is sufficient, the random forest DSM method out-performed other methods, but the improvement from using this more complex method compared to interpolating the soil sample data by ordinary kriging was minimal. The lessons learned while developing the Otjozondjupa LDN SOC baseline provide valuable insights for others who are responsible for developing LDN baselines elsewhere.

ACS Style

RaviC Nijbroek; Kristin Piikki; Mats Söderström; Bas Kempen; Katrine Turner; Simeon Hengari; John Mutua. Soil Organic Carbon Baselines for Land Degradation Neutrality: Map Accuracy and Cost Tradeoffs with Respect to Complexity in Otjozondjupa, Namibia. Sustainability 2018, 10, 1610 .

AMA Style

RaviC Nijbroek, Kristin Piikki, Mats Söderström, Bas Kempen, Katrine Turner, Simeon Hengari, John Mutua. Soil Organic Carbon Baselines for Land Degradation Neutrality: Map Accuracy and Cost Tradeoffs with Respect to Complexity in Otjozondjupa, Namibia. Sustainability. 2018; 10 (5):1610.

Chicago/Turabian Style

RaviC Nijbroek; Kristin Piikki; Mats Söderström; Bas Kempen; Katrine Turner; Simeon Hengari; John Mutua. 2018. "Soil Organic Carbon Baselines for Land Degradation Neutrality: Map Accuracy and Cost Tradeoffs with Respect to Complexity in Otjozondjupa, Namibia." Sustainability 10, no. 5: 1610.

Journal article
Published: 08 May 2017 in Acta Agriculturae Scandinavica, Section B — Soil & Plant Science
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ACS Style

Mats Söderström; Kristin Piikki; Maria Stenberg; Henrik Stadig; Johan Martinsson. Producing nitrogen (N) uptake maps in winter wheat by combining proximal crop measurements with Sentinel-2 and DMC satellite images in a decision support system for farmers. Acta Agriculturae Scandinavica, Section B — Soil & Plant Science 2017, 67, 637 -650.

AMA Style

Mats Söderström, Kristin Piikki, Maria Stenberg, Henrik Stadig, Johan Martinsson. Producing nitrogen (N) uptake maps in winter wheat by combining proximal crop measurements with Sentinel-2 and DMC satellite images in a decision support system for farmers. Acta Agriculturae Scandinavica, Section B — Soil & Plant Science. 2017; 67 (7):637-650.

Chicago/Turabian Style

Mats Söderström; Kristin Piikki; Maria Stenberg; Henrik Stadig; Johan Martinsson. 2017. "Producing nitrogen (N) uptake maps in winter wheat by combining proximal crop measurements with Sentinel-2 and DMC satellite images in a decision support system for farmers." Acta Agriculturae Scandinavica, Section B — Soil & Plant Science 67, no. 7: 637-650.

Research papers
Published: 06 April 2017 in South African Journal of Plant and Soil
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Climate change is projected to have widespread impacts on the climate suitability and geographical distribution of agricultural crops. Simulations were conducted on the suitability of common beans (Phaseolus vulgaris L.) in Tanzania under progressive climate change, taking into account a soil fertility constraint. The results were used to assess the effects of incorporating information on soil fertility, more specifically soil organic carbon (SOC) content, into the niche-based EcoCrop model, which was previously based only on climate data. Extending the model improved the correlation between predicted suitability and production statistics at the regional level. Simulated suitability was highly sensitive to SOC-related model parameters, implying that it is critical to incorporate these parameters in order to improve estimates of crop suitability. Simulations using the best parameterisation identified showed that low SOC is currently more limiting for common bean suitability than climate in 51% of the Tanzanian land area (protected areas excluded). However, future projections suggest that climate will be more limiting for the geographic distribution of common beans than SOC in the near future (2030). Spatial data on predicted SOC levels and other soil properties in future scenario modelling are needed for better identification of suitable areas for common bean production.

ACS Style

Kristin Piikki; Leigh Winowiecki; Tor-Gunnar Vågen; Julian Ramirez-Villegas; Mats Söderström. Improvement of spatial modelling of crop suitability using a new digital soil map of Tanzania. South African Journal of Plant and Soil 2017, 34, 243 -254.

AMA Style

Kristin Piikki, Leigh Winowiecki, Tor-Gunnar Vågen, Julian Ramirez-Villegas, Mats Söderström. Improvement of spatial modelling of crop suitability using a new digital soil map of Tanzania. South African Journal of Plant and Soil. 2017; 34 (4):243-254.

Chicago/Turabian Style

Kristin Piikki; Leigh Winowiecki; Tor-Gunnar Vågen; Julian Ramirez-Villegas; Mats Söderström. 2017. "Improvement of spatial modelling of crop suitability using a new digital soil map of Tanzania." South African Journal of Plant and Soil 34, no. 4: 243-254.

Journal article
Published: 01 January 2017 in Advances in Animal Biosciences
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The publicly available Digital Soil Map of Sweden (DSMS) contains topsoil clay content information in a 50 m×50 m grid, and can be used as decision support in precision agriculture. However, it is also common that farmers have undertaken their own soil sampling (one sample per hectare with texture analysed in every third sample). In the present study, such soil samples from 403 farms were used to validate topsoil clay content information derived from 1) DSMS, 2) DSMS locally adapted by residual kriging, 3) DSMS locally adapted by regression kriging and 4) inverse distance weighting interpolation of the soil sample data without using DSMS. The latter has been common practice until now. The best method differed depending on the local accuracy of DSMS, the quality of the soil sampling and the spatial variation structure of the topsoil texture. The ‘Best method’ strategy, which meant to apply all the above methods and choose the one that performed best at each farm, significantly reduced the mean absolute error. We recommend using this strategy to locally adapt regional digital soil maps to derive accurate decision support for use in precision agriculture.

ACS Style

K. Piikki; M. Söderström; H. Stadig. Local adaptation of a national digital soil map for use in precision agriculture. Advances in Animal Biosciences 2017, 8, 430 -432.

AMA Style

K. Piikki, M. Söderström, H. Stadig. Local adaptation of a national digital soil map for use in precision agriculture. Advances in Animal Biosciences. 2017; 8 (2):430-432.

Chicago/Turabian Style

K. Piikki; M. Söderström; H. Stadig. 2017. "Local adaptation of a national digital soil map for use in precision agriculture." Advances in Animal Biosciences 8, no. 2: 430-432.

Journal article
Published: 19 November 2016 in Sensors
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Four proximal soil sensors were tested at four smallholder farms in Embu County, Kenya: a portable X-ray fluorescence sensor (PXRF), a mobile phone application for soil color determination by photography, a dual-depth electromagnetic induction (EMI) sensor, and a LED-based soil optical reflectance sensor. Measurements were made at 32–43 locations at each site. Topsoil samples were analyzed for plant-available nutrients (N, P, K, Mg, Ca, S, B, Mn, Zn, Cu, and Fe), pH, total nitrogen (TN) and total carbon (TC), soil texture, cation exchange capacity (CEC), and exchangeable aluminum (Al). Multivariate prediction models of each of the lab-analyzed soil properties were parameterized for 576 sensor-variable combinations. Prediction models for K, N, Ca and S, B, Zn, Mn, Fe, TC, Al, and CEC met the setup criteria for functional, robust, and accurate models. The PXRF sensor was the sensor most often included in successful models. We concluded that the combination of a PXRF and a portable soil reflectance sensor is a promising combination of handheld soil sensors for the development of in situ soil assessments as a field-based alternative or complement to laboratory measurements.

ACS Style

Kristin Piikki; Mats Söderström; Jan Eriksson; Jamleck Muturi John; Patrick Ireri Muthee; Johanna Wetterlind; Eric Lund. Performance Evaluation of Proximal Sensors for Soil Assessment in Smallholder Farms in Embu County, Kenya. Sensors 2016, 16, 1950 .

AMA Style

Kristin Piikki, Mats Söderström, Jan Eriksson, Jamleck Muturi John, Patrick Ireri Muthee, Johanna Wetterlind, Eric Lund. Performance Evaluation of Proximal Sensors for Soil Assessment in Smallholder Farms in Embu County, Kenya. Sensors. 2016; 16 (11):1950.

Chicago/Turabian Style

Kristin Piikki; Mats Söderström; Jan Eriksson; Jamleck Muturi John; Patrick Ireri Muthee; Johanna Wetterlind; Eric Lund. 2016. "Performance Evaluation of Proximal Sensors for Soil Assessment in Smallholder Farms in Embu County, Kenya." Sensors 16, no. 11: 1950.

Journal article
Published: 01 November 2016 in Geoderma
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Amazonian Dark Earths (ADEs) are fertile soils for agricultural production as well as important archaeological resources for understanding the pre-Columbian past of the Neotropical lowland rainforest. ADEs are threatened by expanding land exploitation and there is a need to develop efficient approaches to soil mapping and analysis for documenting these soils. In this paper we assess the potential of satellite remote sensing and proximal soil sensing to map, predict and monitor ADEs in land affected by agro-industrial development. We use instruments based on portable x-ray fluorescence (PXRF) and electromagnetic induction (EMI) as well as high-resolution satellite data (Spot 6) for detailed soil surveys at a 10-ha ADE site now mainly used for soybean production on the Belterra Plateau, Pará, Brazil. We predict the regional occurrence of ADE in a c. 250 km2 test area centred on the known ADE site São Francisco using satellite data. Multivariate adaptive regression splines models were parameterised for predictions of soil organic carbon (SOC), cation exchange capacity (CEC), phosphorus (P) and depth of the A horizon in ADEs from sensor data – both from individual sensors and in sensor combinations. Combining sensors gave the best validation results: the highest modelling efficiencies (E) were 0.70 (SOC), 0.88 (CEC) and 0.74 (for both P and A depth). The most powerful single proximal sensor outputs in the predictions were Sr from the PXRF data and magnetic susceptibility (MSa) as measured by the EMI instrument. In the regional satellite based model we located 17 previously unrecorded ADE sites > 2 ha. Ground control checks showed that 10 out of 11 sites were correctly classified. We conclude that these sensors are useful in studies of ADE in deforested cropland and provide new opportunities for detailed studies of the archaeological record.

ACS Style

Mats Söderström; Jan Eriksson; Christian Isendahl; Denise Pahl Schaan; Per Stenborg; Lilian Rebellato; Kristin Piikki. Sensor mapping of Amazonian Dark Earths in deforested croplands. Geoderma 2016, 281, 58 -68.

AMA Style

Mats Söderström, Jan Eriksson, Christian Isendahl, Denise Pahl Schaan, Per Stenborg, Lilian Rebellato, Kristin Piikki. Sensor mapping of Amazonian Dark Earths in deforested croplands. Geoderma. 2016; 281 ():58-68.

Chicago/Turabian Style

Mats Söderström; Jan Eriksson; Christian Isendahl; Denise Pahl Schaan; Per Stenborg; Lilian Rebellato; Kristin Piikki. 2016. "Sensor mapping of Amazonian Dark Earths in deforested croplands." Geoderma 281, no. : 58-68.

Journal article
Published: 16 June 2016 in South African Journal of Plant and Soil
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ACS Style

Mats Söderström; Kristin Piikki; Jeremy Cordingley. Improved usefulness of continental soil databases for agricultural management through local adaptation. South African Journal of Plant and Soil 2016, 34, 35 -45.

AMA Style

Mats Söderström, Kristin Piikki, Jeremy Cordingley. Improved usefulness of continental soil databases for agricultural management through local adaptation. South African Journal of Plant and Soil. 2016; 34 (1):35-45.

Chicago/Turabian Style

Mats Söderström; Kristin Piikki; Jeremy Cordingley. 2016. "Improved usefulness of continental soil databases for agricultural management through local adaptation." South African Journal of Plant and Soil 34, no. 1: 35-45.

Journal article
Published: 27 February 2016 in Precision Agriculture
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Mats Söderström; Gustav Sohlenius; Lars Rodhe; Kristin Piikki. Adaptation of regional digital soil mapping for precision agriculture. Precision Agriculture 2016, 17, 588 -607.

AMA Style

Mats Söderström, Gustav Sohlenius, Lars Rodhe, Kristin Piikki. Adaptation of regional digital soil mapping for precision agriculture. Precision Agriculture. 2016; 17 (5):588-607.

Chicago/Turabian Style

Mats Söderström; Gustav Sohlenius; Lars Rodhe; Kristin Piikki. 2016. "Adaptation of regional digital soil mapping for precision agriculture." Precision Agriculture 17, no. 5: 588-607.

Conference paper
Published: 06 September 2015 in First Conference on Proximal Sensing Supporting Precision Agriculture
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Remote and proximal sensors allow for the collection of data at a high resolution and to low costs, but for the approach to be cost-effective the number of calibration samples needs to be kept low. On the other hand, too few calibration samples can lead to unstable calibration models. In a small study on three adjacent fields (55 ha) at a farm in southwest Sweden, in-situ vis-NIR spectroscopy was used to increase the number of calibration samples used in a multiple adaptive regression spline (MARS) model for mapping clay and sand content. The present study did not find support for an improvement of MARS models when the number of calibration samples was increased from 20 to 100 by vis-NIR predictions of the 80 extra samples. This was probably because the 20 soil samples carried enough information to calibrate the exhaustive predictor data to sand and clay and all the extra samples did was only introduced noise. There were some indications of more stable models when the number of reference samples was reduced to 10 or when the best single predictor was excluded. In this study the number of calibration samples seemed to be less critical than their accuracy.

ACS Style

J. Wetterlind; K. Piikki. Increasing the Number of Calibration Samples in DSM by In-situ Vis-NIR Spectroscopy. First Conference on Proximal Sensing Supporting Precision Agriculture 2015, 1 .

AMA Style

J. Wetterlind, K. Piikki. Increasing the Number of Calibration Samples in DSM by In-situ Vis-NIR Spectroscopy. First Conference on Proximal Sensing Supporting Precision Agriculture. 2015; ():1.

Chicago/Turabian Style

J. Wetterlind; K. Piikki. 2015. "Increasing the Number of Calibration Samples in DSM by In-situ Vis-NIR Spectroscopy." First Conference on Proximal Sensing Supporting Precision Agriculture , no. : 1.

Journal article
Published: 16 February 2015 in European Journal of Soil Science
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In soil mapping, combining information from conceptually different proximal soil sensors can increase the accuracy of prediction and robustness of the model when compared with using individual sensors. In this study the predictability of soil texture (clay, silt and sand fractions) and soil organic matter (SOM) content was tested with a commercial integrated soil profiling tool that included sensors for measuring apparent electrical conductivity (ECa), reflectance in the visible and near‐infrared (vis‐NIR) parts of the electromagnetic spectrum and insertion force (IF). The measurements were made at 20 locations on each of two Swedish farms. At every location, sensor measurements were made at 1.5‐cm intervals from the soil surface to a depth of 0.8 m. Soil samples were collected close to the sensor measurement points and analysed for texture and SOM content. Farm‐specific calibrations were developed for texture and SOM with each sensor separately and with combinations of all three sensors. The calibrations were made using both partial least squares regression (PLSR) and simple linear regression. The results for the two farms were quite consistent in terms of rank in prediction performance between the individual sensors and the sensor combinations. The vis‐NIR spectrometer was the best individual sensor for predicting the soil properties tested on both farms, with root mean square error of cross‐validation (RMSECV) of 0.3–0.5% for SOM, about 6% for clay and silt and 10–11% for sand. The inclusion of IF reduced the RMSECV for predictions of SOM content by about 10%. For soil texture, including ECa reduced the RMSECV on average for all particle size fractions by 5–10%. However, the small improvements obtained by combining sensors do not provide strong support for combining vis‐NIR sensor measurements with measurements of ECa and or IF.

ACS Style

Johanna Wetterlind; K. Piikki; B. Stenberg; Mats Söderström. Exploring the predictability of soil texture and organic matter content with a commercial integrated soil profiling tool. European Journal of Soil Science 2015, 66, 631 -638.

AMA Style

Johanna Wetterlind, K. Piikki, B. Stenberg, Mats Söderström. Exploring the predictability of soil texture and organic matter content with a commercial integrated soil profiling tool. European Journal of Soil Science. 2015; 66 (4):631-638.

Chicago/Turabian Style

Johanna Wetterlind; K. Piikki; B. Stenberg; Mats Söderström. 2015. "Exploring the predictability of soil texture and organic matter content with a commercial integrated soil profiling tool." European Journal of Soil Science 66, no. 4: 631-638.