The use of near infrared (NIR) spectroscopy to improve soil mapping at the farm scale

The creation of fine resolution soil maps is hampered by the increasing costs associated with conventional laboratory analyses of soil. In this study, near infrared (NIR) reflectance spectroscopy was used to reduce the number of conventional soil analyses required by the use of calibration models at the farm scale. Soil electrical conductivity and mid infrared (MIR) reflection from a satellite image were used and compared as ancillary data to guide the targeting of soil sampling. About 150 targeted samples were taken over a 97 hectare farm (approximately 1.5 samples per hectare) for each type of ancillary data. A sub-set of 25 samples was selected from each of the targeted data sets (150 points) to measure clay and soil organic matter (SOM) contents for calibration with NIR. For the remaining 125 samples only their NIR-spectra needed to be determined. The NIR calibration models for both SOM and clay contents resulted in predictions with small errors. Maps derived from the calibrated data were compared with a map based on 0.5 samples per hectare representing a conventional farm-scale soil map. The maps derived from the NIR-calibrated data are promising, and the potential for developing a cost-effective strategy to map soil from NIR-calibrated data at the farm-scale is considerable

Soil analysis using visible and near infrared spectroscopy

Visible-near infrared diffuse reflectance (vis-NIR) spectroscopy is a fast, non-destructive technique well suited for analyses of some of the essential constituents of the soil. These constituents, mainly clay minerals, organic matter and soil water strongly affect conditions for plant growth and influence plant nutrition. Here we describe the process by which vis–NIR spectroscopy can be used to collect soil spectra in the laboratory. Because it is an indirect technique, the succeeding model calibrations and validations that are necessary to obtain reliable predictions about the soil properties of interest, are also described in the chapter

Improved farm soil mapping using near infrared reflection spectroscopy

Information on soil texture, soil organic matter content (SOM), nutrient status and pH is fundamental for efficient crop production and for minimising negative effects on the environment. Farmers obtain this information, on which decisions on fertiliser and lime requirements are based, through farm soil mapping. Although there is a general awareness that within-field and within-farm variations might not be adequately captured using conventional sample point density, simply increasing the number of sample pointes would increase the cost to unacceptable levels. In this thesis, near infrared reflection (NIR) spectroscopy was used to obtain more accurate information on within-field or within-farm variations in a number of soil properties. One central objective was to estimate the within-field variation in N mineralisation, to allow for improved N fertilisation strategies. Another was the development of economically feasible strategies for increasing sample point density in conventional farm soil mapping for improved decision support in precision agriculture. The results presented here show that NIR spectroscopy can be used to estimate N mineralisation (measured as plant N uptake) in fields with large variations in SOM, and that the additional predictive capacity of NIR compared with SOM is related to variations in soil texture. The results also demonstrate that it is possible to make small farm-scale calibrations with a very limited number of calibration samples for clay and SOM content, producing information at a considerably higher density than conventional farm soil mapping. Within-field calibrations for pH and easily available P, K and Mg-AL also proved possible, but more calibration samples were needed. Predictions for silt failed regardless of the number of calibration samples

Visible and near infrared spectroscopy in soil science

This chapter provides a review on the state of soil visible–near infrared (vis–NIR) spectroscopy. Our intention is for the review to serve as a source of up-to date information on the past and current role of vis–NIR spectroscopy in soil science. It should also provide critical discussion on issues surrounding the use of vis–NIR for soil analysis and on future directions. To this end, we describe the fundamentals of visible and infrared diffuse reflectance spectroscopy and spectroscopic multivariate calibrations. A review of the past and current role of vis–NIR spectroscopy in soil analysis is provided, focusing on important soil attributes such as soil organic matter (SOM), minerals, texture, nutrients, water, pH, and heavy metals. We then discuss the performance and generalization capacity of vis–NIR calibrations, with particular attention on sample pre-tratments, co-variations in data sets, and mathematical data preprocessing. Field analyses and strategies for the practical use of vis–NIR are considered. We conclude that the technique is useful to measure soil water and mineral composition and to derive robust calibrations for SOM and clay content. Many studies show that we also can predict properties such as pH and nutrients, although their robustness may be questioned. For future work we recommend that research should focus on: (i) moving forward with more theoretical calibrations, (ii) better understanding of the complexity of soil and the physical basis for soil reflection, and (iii) applications and the use of spectra for soil mapping and monitoring, and for making inferences about soils quality, fertility and function. To do this, research in soil spectroscopy needs to be more collaborative and strategic. The development of the Global Soil Spectral Library might be a step in the right direction

Perspectives on validation in digital soil mapping of continuous attributes—A review

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

Precision agriculture research in sub-Saharan Africa countries: a systematic map

Precision agriculture (PA) has a huge potential for growth in sub-Saharan Africa (SSA), but it faces a number of social-economic and technological challenges. This study sought to map existing PA research and application in SSA countries following the methodology for systematic mapping in environmental sciences. After screening for relevance, the initial about 7715 articles was reduced to 128. Results show that most of the studies were conducted in countries with socio-economic and technological advancement, mainly South Africa followed by Nigeria and Kenya. The studies were conducted at various scales ranging from field to country level with field scale studies being the most common. Most studies were conducted in relatively small farms typical of most farmlands in SSA. Studies done in relatively large farms are fewer, and such farms would likely belong to a few organisations and individuals with high economic capacity. Many of these studies have been conducted by researchers from outside SSA and a combination of researchers from within and outside SSA. However, based on authorship of the articles, it appears that most of the studies conducted in SSA on precision agriculture have either involved or depended on non-African researchers. It is concluded that there have been significant strides towards use of precision agriculture in SSA. However, with about 21 countries having no research done, there exists greater potential for precision agriculture in the region. Besides, there is need for more research to investigate the low usage of precision agriculture for livestock management

Long-term ley and manure managements have consistent effects on microbial functional profiles and organic C groups across soils from a latitudinal gradient

Soil organic matter (SOM) is important in maintaining soil fertility and other ecosystem functions. Yet, land management in intensive agriculture has caused SOM level to decrease, with knock-on effects for soil fertility and quality. Therefore, land management options that ensure that SOM is not depleted and that soil functions are better sustained are of increasing interest. However, there is limited knowledge on how different land managements affect the composition of SOM and associated microbial functional profiles. Twelve long-term field experiments, covering a wide range of climatic zones and soil types, were selected in Sweden. They focused on the role of combining ley in crop rotations with the manure application (livestock farm), as opposed to the management without ley and receiving only inorganic fertilizer (arable farm). In ten out of the 12 study sites, livestock farm management tended to have higher proportions of aliphatic and double bonded C groups, as estimated by mid-infrared spectroscopy. This was further confirmed by C-13 NMR analysis, which found greater proportions of O-alkyl and di-O-alkyl groups and less aromatic C in livestock farm than arable farm management in five of the eight sites analyzed. The changes in SOM composition were reflected in microbial functional profiles across many sites: soils from livestock farm management utilized more carbohydrates and amino acids, while polymer and aromatic compounds were associated with arable farm management. Overall, shifts in both microbial functional profiles and SOM composition showed great consistency across geographical and climatic zones. Livestock farm management maintained higher levels of microbial functional diversity and were associated with higher proportions of "reactive" C functional groups. Our investigation demonstrates that livestock farm management could maintain soil fertility over the long-term via the changes in SOM composition and the regulation of microbial functional profiles

Går det att bestämma vattenhalten i fält med NIR för korrigering av andra sensormätningar?

En stor skillnad mellan sensormätningar gjorda på lab och mätningar gjorda direkt i fält är att fältmätningarna påverkas av vattenhalten i marken. Vattenhalten kommer att varierar mellan mätningstidpunkter men också beroende på var på fältet mätningen görs. Påverkan av vattenhalt och variationer i vattenhalt är några av anledningarna till att bestämningarna av t ex jordart eller tungmetaller från sensormätningar ofta blir något sämre med fältmätningar jämfört med mätningar på torkad jord på lab. Syftet med pilotprojektet var därför att undersöka möjligheten att göra vattenhaltsbestämningar direkt i fält med nära infraröd reflektans (NIR) spektroskopi. Vattenhaltsbestämningar från NIR-mätningar direkt i fält i samband med andra sensormätningar skulle kunna användas för att korrigera för vattenhalt i de andra sensormätningarna och därmed förbättra bestämningarna av jordart och tungmetaller utan att behöva ta in en mängd prov för analys på lab. Resultaten visar på möjligheten att använda NIR-mätningar för att bestämma vattenhalten i marken i samband med andra sensormätningar som t ex med ett PXRF (portabelt röntgenfluorescens) instrument. Men texturen har en stor inverkan på både vattenhalt och spektrum och det är viktigt att få med variationen i både vattenhalt och i textur i kalibreringen. Bäst modeller fick vi genom att använda ett fåtal provplatser, två, som täckte in ytterligheterna i textur och sedan bygga modeller på de två platserna där vi hade 10 olika vattenhalter per plats. Detta är möjligt i teorin, men inte i praktiken om modellerna visar sig vara så specifika som resultaten av pilotstudien antyder. Detta måste dock testas på fler platser. Mer framkomligt är det då att göra lokala kalibreringar i samband med varje sensormätning. Det skulle innebära att ett antal prov togs in för vattenhaltsbestämning genom torkning. Då de flesta andra sensorer också kräver någon form av kalibrering behöver detta inte nödvändigtvis innebära så mycket extrajobb. I pilotstudien gjordes sådana kalibreringar med 10 och 16 prov. Det var i minsta laget men då ska man komma ihåg att de tre fälten som ingick i pilotstudien har väldigt hög variation i textur. Med mindre texturvariationer borde det gå att hålla nere antalet kalibreringsprov för vattenhaltsbestämning

Using visible and near infrared spectroscopy to estimate carbonates and gypsum in soils in arid and subhumid regions of Isfahan, Iran

Soils in arid and semi-arid regions are strongly affected by the accumulation of carbonates, gypsum and other, more soluble, salts. Carbonates and gypsum both have a considerable influence on soil properties, especially the chemical properties of the soil solution. The development of reliable, fast and inexpensive methods to quantify the amounts of carbonates and gypsum in soil is therefore important. Visible and near infrared (vis-NIR) spectroscopy is a non-destructive, rapid and cheap method for measuring several soil properties simultaneously. However, research on vis-NIR spectroscopy in quantifying carbonates and gypsum is limited. Therefore, this study evaluated the efficiency of vis-NIR spectroscopy in quantifying carbonates and gypsum in surface soils using partial least-squares regression (PLSR) compared with standard laboratory methods and compared PLSR with a feature-specific method using continuum removal (CR). Carbonates and gypsum in a total of 251 sieved and air-dried topsoil samples from Isfahan Province in central Iran were measured by standard laboratory methods and vis-NIR spectroscopy (350–2500 nm wavelength range). In parallel, PLSR and the feature-specific method based on CR spectra were used to predict carbonates and gypsum. The PLSR model efficiency (E) for carbonates and gypsum in the validation set was 0.52 and 0.80, respectively. The PLSR model resulted in better predictions than the feature-specific method for both soil properties. Because of the unique absorption features of gypsum, which did not overlap with other soil properties, predictions of gypsum resulted in higher E values and lower errors than predictions of carbonates