Using a legacy soil sample to develop a mid-IR spectral library

Soil Research ◽  
2008 ◽  
Vol 46 (1) ◽  
pp. 1 ◽  
Author(s):  
R. A. Viscarra Rossel ◽  
Y. S. Jeon ◽  
I. O. A. Odeh ◽  
A. B. McBratney
Keyword(s):  
Soil Properties ◽  
Soil Sample ◽  
Diffuse Reflectance ◽  
Mean Squared Error ◽  
Clay Content ◽  
Spectral Library ◽  
Total N ◽  
Organic C ◽  
Soil Database ◽  
Eastern Australia

This paper describes the development of a diffuse reflectance spectral library from a legacy soil sample. When developing a soil spectral library, it is important to consider the number of samples that are needed to adequately describe the soil variability in the region in which the library is to be used; the manner in which the soil is sampled, handled, prepared, stored, and scanned; and the reference analytical procedures used. As with any type of modelling, the dictum is ‘garbage in = garbage out’ and hopefully the converse ‘quality in = quality out’. The aims of this paper are to: (i) develop a soil mid infrared (mid-IR) diffuse reflectance spectral library for cotton-growing regions of eastern Australia from a legacy soil sample, (ii) derive soil spectral calibrations for the prediction of soil properties with uncertainty, and (iii) assess the accuracy of the predictions and populate the legacy soil database with good quality information. A scheme for the construction and use of this spectral library is presented. A total of 1878 soil samples from different layers were scanned. They originated from the Upper Namoi, Namoi, and Gwydir Valley catchments of north-western New South Wales (NSW) and the McIntyre region of southern Queensland (Qld). A conditioned Latin hypercube sampling (cLHS) scheme was used to sample the spectral data space and select 213 representative samples for laboratory soil analyses. Using these data, partial least-squares regression (PLSR) was used to construct the calibration models, which were validated internally using cross validation and externally using an independent test dataset. Models for organic C (OC), cation exchange capacity (CEC), clay content, exchangeable Ca, total N (TN), total C (TC), gravimetric moisture content θg, total sand and exchangeable Mg were robust and produced accurate results (R2adj. > 0.75 for both cross and test set validations). The root mean squared error (RMSE) of mid-IR-PLSR predictions was compared to those from (blind) duplicate laboratory measurements. Mid-IR-PLSR produced lower RMSE values for soil OC, clay content, and θg. Finally, bootstrap aggregation-PLSR (bagging-PLSR) was used to predict soil properties with uncertainty for the entire library, thus repopulating the legacy soil database with good quality soil information.

scholarly journals Developing the Swiss soil spectral library for local estimation and monitoring

2021 ◽  
Author(s):  
Philipp Baumann ◽  
Anatol Helfenstein ◽  
Andreas Gubler ◽  
Armin Keller ◽  
Reto Giulio Meuli ◽  
...  
Keyword(s):  
Soil Properties ◽  
Chemical Diversity ◽  
Total Carbon ◽  
Data Driven ◽  
Organic Soils ◽  
Spectral Library ◽  
Total N ◽  
Organic C ◽  
Measured Range

Abstract. Information on soils' composition and physical, chemical and biological properties is paramount to elucidate agroecosystem functioning in space and over time. For this purposes we developed a national Swiss soil spectral library (SSL; n = 4374) in the mid-infrared (mid-IR), calibrating 17 properties from legacy measurements on soils from the Swiss biodiversity monitoring program (n = 3778; 1094 sites) and the Swiss long-term monitoring network (n = 596; 71 sites). General models were trained with the interpretable rule-based learner CUBIST, testing combinations of {5, 10, 20, 50, 100} committees of rules and {2, 5, 7, 9} neighbors to localize predictions with repeated by location grouped ten-fold cross-validation. To evaluate the information in spectra to facilitate long-term soil monitoring at a plot-level, we conducted 71 model transfers for the NABO sites to induce locally relevant information from the SSL, using the data-driven sample selection method rs-local. Eleven soil properties were estimated with discrimination capacity suitable for screening (R2 > 0.6), out of which total carbon (C), organic C (OC), total N, organic matter content, pH, and clay showed accuracy eligible for accurate diagnostics (R2 > 0.8). Cubist and the spectra estimated total C accurately with RMSE = 0.84 % while the measured range was 0.1–⁠58.3 %, and OC with RMSE = 1.20 % (measured range 0.0–⁠27.3 %). Compared to general estimates of properties from Cubist, local modeling on average reduced the root mean square error of total C per site fourfold. We found that the selected SSL subsets were highly dissimilar in terms of both their spectral input space and the measured values. This suggests that data-driven selection with RS-LOCAL leverages chemical diversity in composition rather than similarity. Our results suggest that mid-IR soil estimates were sufficiently accurate to support many soil applications that require a large volume of input data, such as precision agriculture, soil C accounting and monitoring, and digital soil mapping. This SSL can be updated continuously, for example with samples from deeper profiles and organic soils, so that the measurement of key soil properties becomes even more accurate and efficient in the near future.

scholarly journals A Comparison, Validation, and Evaluation of the S-world Global Soil Property Database

Land ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 544
Author(s):  
Jetse J. Stoorvogel ◽  
Vera L. Mulder
Keyword(s):  
Comparative Analysis ◽  
Soil Properties ◽  
Soil Property ◽  
Evaluation Criteria ◽  
Clay Content ◽  
Soil Database ◽  
Global Environmental ◽  
Global Soil ◽  
Mean Square Difference ◽  
Methodological Evaluation

Despite the increased usage of global soil property maps, a proper review of the maps rarely takes place. This study aims to explore the options for such a review with an application for the S-World global soil property database. Global soil organic carbon (SOC) and clay content maps from S-World were studied at two spatial resolutions in three steps. First, a comparative analysis with an ensemble of seven datasets derived from five other global soil databases was done. Second, a validation of S-World was done with independent soil observations from the WoSIS soil profile database. Third, a methodological evaluation of S-world took place by looking at the variation of soil properties per soil type and short distance variability. In the comparative analysis, S-World and the ensemble of other maps show similar spatial patterns. However, the ensemble locally shows large discrepancies (e.g., in boreal regions where typically SOC contents are high and the sampling density is low). Overall, the results show that S-World is not deviating strongly from the model ensemble (91% of the area falls within a 1.5% SOC range in the topsoil). The validation with the WoSIS database showed that S-World was able to capture a large part of the variation (with, e.g., a root mean square difference of 1.7% for SOC in the topsoil and a mean difference of 1.2%). Finally, the methodological evaluation revealed that estimates of the ranges of soil properties for the different soil types can be improved by using the larger WoSIS database. It is concluded that the review through the comparison, validation, and evaluation provides a good overview of the strengths and the weaknesses of S-World. The three approaches to review the database each provide specific insights regarding the quality of the database. Specific evaluation criteria for an application will determine whether S-World is a suitable soil database for use in global environmental studies.

scholarly journals Maize Production and Soil Properties Change in Alley Cropping System at Different Nitrogen Levels

2010 ◽  
pp. 41-49
Author(s):  
Md Abiar Rahman ◽  
Md Giashuddin Miah ◽  
Hisashi Yahata
Keyword(s):  
Soil Properties ◽  
Alley Cropping ◽  
Cropping System ◽  
Woody Species ◽  
Maize Yield ◽  
Similar Amount ◽  
Maize Production ◽  
Total N ◽  
Organic C ◽  
Nitrogen Levels

Productivity of maize and soil properties change under alley cropping system consisting of four woody species (Gliricidia sepium, Leucaena leucocephala, Cajanus cajan and Senna siamea) at different nitrogen levels (0, 25, 50, 75 and 100% of recommended rate) were studied in the floodplain ecosystem of Bangladesh. Comparative growth performance of four woody species after pruning showed that L. leucocephala attained the highest height, while C. cajan produced the maximum number of branches. Higher and almost similar amount of pruned materials (PM) were obtained from S. siamea, G. sepium and C. cajan species. In general, maize yield increased with the increase in N level irrespective of added PM. However, 100% N plus PM, 75% N plus PM and 100% N without PM (control) produced similar yields. The grain yield of maize obtained from G. sepium alley was 2.82, 4.13 and 5.81% higher over those of L. leucocephala, C. cajan and S. siamea, respectively. Across the alley, only one row of maize in the vicinity of the woody species was affected significantly. There was an increasing trend in soil properties in terms of organic C, total N and CEC in alley cropping treatments especially in G. sepium and L. leucocephala alleys compared to the initial and control soils. Therefore, one fourth chemical N fertilizer can be saved without significant yield loss in maize production in alley cropping system.

Spatial and temporal variability in chemical properties of a podzolic B horizon of an old-growth maple forest

1995 ◽  
Vol 75 (3) ◽  
pp. 343-348 ◽  
Author(s):  
Christian Godbout ◽  
Jean-Louis Brown
Keyword(s):  
Soil Properties ◽  
Chemical Properties ◽  
Spatial And Temporal Variability ◽  
Eastern Canada ◽  
Old Growth ◽  
Total N ◽  
Organic C ◽  
Exchangeable Ca ◽  
The Difference ◽  
Soil Changes

A Podzolic soil from an old-growth maple hardwood forest in eastern Canada was systematically sampled from a 16.5-m-long trench in 1975. In 1986, the upper 10 cm of the B horizon was resampled from two sampling lines located on each side and parallel to the 1975 trench, one at a distance of 1 m downhill and the other at a distance of 4 m uphill. Total N, organic C, pH, and exchangeable Ca, Mg and K were measured. The objectives were to evaluate the change in the chemical status of the B horizon from 1975 to 1986 and to characterize the spatial variability of the horizon. No significant change was found in the soil chemical properties tested during this 11-yr period. No significant autocorrelation was observed between soil samples 60 cm apart, except for the downhill sampling line, which was located 1 m from the trench. For most properties, the magnitude of the difference between two soil sampling units was not proportional to the distance separating them over the range of 0.6–4.2 m. Except for pH, a difference in soil properties of more than 30% was observed in 37–56% of sample pairs 60 cm apart. Resampling near (1 m) an old soil pit may not be valid because of possible local modifications of soil properties created by the pit, even when it is filled in. Key words: Podzol, soil variability, acidic deposition, soil changes

scholarly journals Field Proximal Soil Sensor Fusion for Improving High-Resolution Soil Property Maps

Soil Systems ◽  
2020 ◽  
Vol 4 (3) ◽  
pp. 52
Author(s):  
Gustavo M. Vasques ◽  
Hugo M. Rodrigues ◽  
Maurício R. Coelho ◽  
Jesus F. M. Baca ◽  
Ricardo O. Dart ◽  
...  
Keyword(s):  
Soil Properties ◽  
Ordinary Kriging ◽  
Soil Property ◽  
Clay Content ◽  
Exchange Capacity ◽  
Organic C ◽  
Covariate Data ◽  
Independent Validation ◽  
Soil Sensors ◽  
Dense Grid

Mapping soil properties, using geostatistical methods in support of precision agriculture and related activities, requires a large number of samples. To reduce soil sampling and measurement time and cost, a combination of field proximal soil sensors was used to predict and map laboratory-measured soil properties in a 3.4-ha pasture field in southeastern Brazil. Sensor soil properties were measured in situ on a 10 × 10-m dense grid (377 samples) using apparent electrical conductivity meters, apparent magnetic susceptibility meter, gamma-ray spectrometer, water content reflectometer, cone penetrometer, and portable X-ray fluorescence spectrometer (pXRF). Soil samples were collected on a 20 × 20-m thin grid (105 samples) and analyzed in the laboratory for organic C, sum of bases, cation exchange capacity, clay content, soil volumetric moisture, and bulk density. Another 25 samples collected throughout the area were also analyzed for the same soil properties and used for independent validation of models and maps. To test whether the combination of sensors enhances soil property predictions, stepwise multiple linear regression (MLR) models of the laboratory soil properties were derived using individual sensor covariate data versus combined sensor data—except for the pXRF data, which were evaluated separately. Then, to test whether a denser grid sample boosted by sensor-based soil property predictions enhances soil property maps, ordinary kriging of the laboratory-measured soil properties from the thin grid was compared to ordinary kriging of the sensor-based predictions from the dense grid, and ordinary cokriging of the laboratory properties aided by sensor covariate data. The combination of multiple soil sensors improved the MLR predictions for all soil properties relative to single sensors. The pXRF data produced the best MLR predictions for organic C content, clay content, and bulk density, standing out as the best single sensor for soil property prediction, whereas the other sensors combined outperformed the pXRF sensor for the sum of bases, cation exchange capacity, and soil volumetric moisture, based on independent validation. Ordinary kriging of sensor-based predictions outperformed the other interpolation approaches for all soil properties, except organic C content, based on validation results. Thus, combining soil sensors, and using sensor-based soil property predictions to increase the sample size and spatial coverage, leads to more detailed and accurate soil property maps.

scholarly journals Evaluation of Physicochemical Properties of Sandy-Textured Soils under Smallholder Agricultural Land Use Practices in Sarawak, East Malaysia

2019 ◽  
Vol 2019 ◽  
pp. 1-14
Author(s):  
Soo Ying Ho ◽  
Mohd Effendi Bin Wasli ◽  
Mugunthan Perumal
Keyword(s):  
Land Use ◽  
Physicochemical Properties ◽  
Soil Properties ◽  
Oil Palm ◽  
Agricultural Land ◽  
Secondary Forests ◽  
Land Uses ◽  
Total N ◽  
Organic C ◽  
Nutrient Contents

A study was conducted in the Sabal area, Sarawak, to evaluate the physicochemical properties of sandy-textured soils under smallholder agricultural land uses. Study sites were established under rubber, oil palm, and pepper land uses, in comparison to the adjacent secondary forests. The sandy-textured soils underlain in all agricultural land uses are of Spodosols, based on USDA Soil Taxonomy. The soil properties under secondary forests were strongly acidic with poor nutrient contents. Despite higher bulk density in oil palm farmlands, soil properties in rubber and oil palm land uses showed little variation to those in secondary forests. Conversely, soils under pepper land uses were less acidic with higher nutrient contents at the surface layer, especially P. In addition, soils in the pepper land uses were more compact due to human trampling effects from regular farm works at a localized area. Positive correlations were observed between soil total C and soil total N, soil exchangeable K, soil sum of bases, and soil effective CEC, suggesting that soil total C is the determinant of soil fertility under the agricultural land uses. Meanwhile, insufficient K input in oil palm land uses was observed from the partial nutrient balances estimation. In contrast, P and K did not remain in the soils under pepper land use, although the fertilizers application by the farmers was beyond the crop uptake and removal (harvesting). Because of the siliceous sandy nature (low clay contents) of Spodosols, they are poor in nutrient retention capacity. Hence, maintaining ample supply of organic C is crucial to sustain the productivity and fertility of sandy-textured soils, especially when the litterfall layers covering the E horizon were removed for oil palm and pepper cultivation.

Simulation of soil carbon dynamics in Australia with {\sc Roth C}

2021 ◽  
Author(s):  
Raphael Viscarra Rossel ◽  
Juhwan Lee ◽  
Mingxi Zhang ◽  
Zhongkui Luo ◽  
YingPing Wang
Keyword(s):  
C:N Ratio ◽  
Clay Content ◽  
Natural Environments ◽  
Soil Organic C ◽  
Total N ◽  
Organic C ◽  
Continental Scale ◽  
C Stocks ◽  
C Decomposition ◽  
Soil Measurements

<p>We simulated soil organic carbon (C) dynamics across Australia with the Rothamsted carbon model ({\sc Roth C}) by connecting new spatially-explicit soil measurements and data with the model. This helped us to bridge the disconnection that exists between datasets used to inform the model and the processes that it depicts. We compiled publicly available continental-scale datasets and pre-processed, standardised and configured them to the required spatial and temporal resolutions. We then calibrated {\sc Roth C} and run simulations to estimate the baseline soil organic C stocks and composition in the 0--0.3~m layer at 4,043 sites in cropping, modified grazing, native grazing, and natural environments across Australia. We used data on the C fractions, the particulate, mineral associated, and resistant organic C (POC, MAOC and ROC, respectively) to represent the three main C pools in the {\sc Roth C} model's structure.<span class="Apple-converted-space">  </span>The model explained 97--98\% of the variation in measured total organic C in soils under cropping and grazing, and 65\% in soils under natural environments. We optimised the model at each site and experimented with different amounts of C inputs to simulate the potential for C accumulation under constant and chainging climate in a 100-year simulation. Soils under native grazing were the most potentially vulnerable to C decomposition and loss, while soils under natural environments were the least vulnerable. An empirical assessment of the controls on the C change showed that climate, pH, total N, the C:N ratio, and cropping were the most important controls on POC change. Clay content and climate were dominant controls on MAOC change. Consistent and explicit soil organic C simulations improve confidence in the model's estimations, contributing to the development of sustainable soil management under global change.<span class="Apple-converted-space"> </span></p>

Soil properties following long-term application of stockpiled feedlot manure containing straw or wood-chip bedding under barley silage production

2014 ◽  
Vol 94 (3) ◽  
pp. 389-402 ◽  
Author(s):  
J. J. Miller ◽  
B. W. Beasley ◽  
C. F. Drury ◽  
X. Hao ◽  
F. J. Larney
Keyword(s):  
Soil Properties ◽  
C:N Ratio ◽  
Wood Chip ◽  
Water Soluble ◽  
Bedding Material ◽  
Total N ◽  
Organic C ◽  
Silage Production ◽  
Total Organic C

Miller, J. J., Beasley, B. W., Drury, C. F., Hao, X. and Larney, F. J. 2014. Soil properties following long-term application of stockpiled feedlot manure containing straw or wood-chip bedding under barley silage production. Can. J. Soil Sci. 94: 389–402. The influence of long-term land application of stockpiled feedlot manure (SM) containing either wood-chip (SM-WD) or straw (SM-ST) bedding on soil properties during the barley (Hordeum vulgare L.) silage growing season is unknown. The main objective of our study was determine the effect of bedding material in stockpiled manure (i.e., SM-WD vs. SM-ST) on certain soil properties. A secondary objective was to determine if organic amendments affected certain soil properties compared with unamended soil. Stockpiled feedlot manure with SM-WD or SM-ST bedding at 77 Mg (dry wt) ha−1 yr−1 was annually applied for 13 to 14 yr to a clay loam soil in a replicated field experiment in southern Alberta. There was also an unamended control. Soil properties were measured every 2 wk during the 2011 and 2012 growing season. Properties included water-filled pore space (WFPS), total organic C and total N, NH4-N and NO3-N, water-soluble non-purgeable organic C (NPOC), water-soluble total N (WSTN), denitrification (acetylene inhibition method), and CO2 flux. The most consistent and significant (P≤0.05) bedding effects on soil properties in both years occurred for total organic C, C:N ratio, and WSTN. Total organic C and C:N ratio were generally greater for SM-WD than SM-ST, and the reverse trend occurred for WSTN. Bedding effects on other soil properties (WFPS, NH4-N, NO3-N, NPOC) occurred in 2012, but not in 2011. Total N, daily denitrification, and daily CO2 flux were generally unaffected by bedding material. Mean daily denitrification fluxes ranged from 0.9 to 1078 g N2O-N ha−1 d−1 for SM-ST, 0.8 to 326 g N2O-N ha−1 d−1 for SM-WD, and 0.6 to 250 g N2O-N ha−1 d−1 for the CON. Mean daily CO2 fluxes ranged from 5.3 to 43.4 kg CO2-C ha−1 d−1 for SM-WD, 5.5 to 26.0 kg CO2-C ha−1 d−1 for SM-ST, and from 0.5 to 6.8 kg CO2-C ha−1 d−1 for the CON. The findings from our study suggest that bedding material in feedlot manure may be a possible method to manage certain soil properties.

Retention and nitrification of injected anhydrous NH3as affected by soil pH

2012 ◽  
Vol 92 (4) ◽  
pp. 589-598 ◽  
Author(s):  
Mônica B. Benke ◽  
Tee Boon Goh ◽  
Rigas Karamanos ◽  
Newton Z. Lupwayi ◽  
Xiying Hao
Keyword(s):  
Soil Properties ◽  
Soil Ph ◽  
Acid Soils ◽  
Field Capacity ◽  
Alkaline Soils ◽  
Canadian Prairie ◽  
Agronomic Efficiency ◽  
Total N ◽  
Organic C ◽  
Prairie Soils

Benke, M. B., Goh, T. B., Karamanos, R., Lupwayi, N. Z. and Hao, X. 2012. Retention and nitrification of injected anhydrous NH3as affected by soil pH. Can. J. Soil Sci. 92: 589–598. Anhydrous ammonia is an economical and extensively used fertilizer, yet loss after injection can reduce its agronomic efficiency. A laboratory experiment was conducted to examine how soil properties affect ammonia retention and nitrification following anhydrous NH3injection using 10 different Canadian prairie soils. Soils were also injected with atmospheric air for comparison. Following injection, soils were incubated for up to 216 h at field capacity. Among the soil properties studied [pH (1:2 water), clay, total N, and organic C contents], only pH was negatively related (R2=0.55, n=10, 24 h incubation) to percentage injected N retained by soil. The amount of N retained by soil 24 h following injection was 92±2% (mean±SEM) when pH <6, compared with 64±2% when pH>7.5. Rate of nitrification increased (P<0.001) about 48–96 h following injection and was greater in pH>7.5 than pH<6 soils. There was no difference (P>0.05) in bacterial diversity between ammonia- and air-injected soils. The slower nitrification rates suggest that potential leaching and denitrification losses in acid soils could be smaller than in alkaline soils.

Effect of phosphorus, farmyard manure and nitrogen on some soil properties in a soya bean-maize sequence

1986 ◽  
Vol 107 (3) ◽  
pp. 555-559
Author(s):  
P. M. Nimje ◽  
Jagdish Seth
Keyword(s):  
Soil Properties ◽  
Bulk Density ◽  
Farmyard Manure ◽  
Soya Bean ◽  
Water Holding Capacity ◽  
Available P ◽  
Total N ◽  
Organic C ◽  
Phosphorus Application ◽  
Water Holding

SUMMARYThe effects of applying phosphorus, farmyard manure (FYM) and nitrogen on some soil properties were studied at the end of 2 years of field experimentation at New Delhi, India. Each year a crop of soya bean sown in the rainy season received phosphorus and farmyard manure and maize sown in winter received nitrogen fertilizer. Phosphorus was applied to soya bean at 0, 40 and 80 kg P2O5/ha, farmyard manure at 0 and 15 t/ha and nitrogen to maize at 0, 60 and 120 kg N/ha. Phosphorus application increased organic C, total N and available P status of the soil. It also improved bulk density and water-holding capacity of the soil. Farmyard manure increased organic C, total N, available P and K and pH of the soil, but decreased EC and bulk density of the soil. Water-holding capacity of the soil was increased by FYM. N fertilizer increased organic C and total N only.

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