Browsing by Author "Haefele, Stephan M."
Now showing 1 - 14 of 14
Results Per Page
Sort Options
Item Open Access Agricultural decision-making under uncertainty: a loss function on the kriging variance from soil properties predicted by infrared and X-ray fluorescence spectroscopy(EGU: European Geophysical Union, 2021-04-30) Breure, Timo Samuel; Haefele, Stephan M.; Webster, Richard; Hannam, Jacqueline A.; Corstanje, Ronald; Milne, Alice E.Item Open Access Changes in organic carbon to clay ratios in different soils and land uses in England and Wales over time(Springer Nature, 2022-03-25) Prout, Jonah M.; Shepherd, Keith D.; McGrath, Steve P.; Kirk, Guy J. D.; Hassall, Kirsty L.; Haefele, Stephan M.Realistic targets for soil organic carbon (SOC) concentrations are needed, accounting for differences between soils and land uses. We assess the use of SOC/clay ratio for this purpose by comparing changes over time in (a) the National Soil Inventory of England and Wales, first sampled in 1978–1983 and resampled in 1994–2003, and (b) two long-term experiments under ley-arable rotations on contrasting soils in the East of England. The results showed that normalising for clay concentration provides a more meaningful separation between land uses than changes in SOC alone. Almost half of arable soils in the NSI had degraded SOC/clay ratios (< 1/13), compared with just 5% of permanent grass and woodland soils. Soils with initially large SOC/clay ratios (≥ 1/8) were prone to greater losses of SOC between the two NSI samplings than those with smaller ratios. The results suggest realistic long-term targets for SOC/clay in arable, ley grass, permanent grass and woodland soils are 1/13, 1/10, and > 1/8, respectively. Given the wide range of soils and land uses across England and Wales in the datasets used to test these targets, they should apply across similar temperate regions globally, and at national to sub-regional scales.Item Open Access Comparing the effect of different sample conditions and spectral libraries on the prediction accuracy of soil properties from near- and mid-infrared spectra at the field-scale(Elsevier, 2021-10-07) Breure, Timo Samuel; Prout, Jonah M.; Haefele, Stephan M.; Milne, Alice E.; Hannam, Jacqueline A.; Moreno-Rojas, S.; Corstanje, RonaldThe prediction accuracy of soil properties by proximal soil sensing has made their application more practical. However, in order to gain sufficient accuracy, samples are typically air-dried and milled before spectral measurements are made. Calibration of the spectra is usually achieved by making wet chemistry measurements on a subset of the field samples and local regression models fitted to aid subsequent prediction. Both sample handling and wet chemistry can be labour and resource intensive. This study aims to quantify the uncertainty associated with soil property estimates from different methods to reduce effort of field-scale calibrations of soil spectra. We consider two approaches to reduce these expenses for predictions made from visible-near-infrared ((V)NIR), mid-infrared (MIR) spectra and their combination. First, we considered reducing the level of processing of the samples by comparing the effect of different sample conditions (in-situ, unprocessed, air-dried and milled). Second, we explored the use of existing spectral libraries to inform calibrations (based on milled samples from the UK National Soil Inventory) with and without ‘spiking’ the spectral libraries with a small subset of samples from the study fields. Prediction accuracy of soil organic carbon, pH, clay, available P and K for each of these approaches was evaluated on samples from agricultural fields in the UK. Available P and K could only be moderately predicted with the field-scale dataset where samples were milled. Therefore this study found no evidence to suggest that there is scope to reduce costs associated with sample processing or field-scale calibration for available P and K. However, the results showed that there is potential to reduce time and cost implications of using (V)NIR and MIR spectra to predict soil organic carbon, clay and pH. Compared to field-scale calibrations from milled samples, we found that reduced sample processing lowered the ratio of performance to inter-quartile range (RPIQ) between 0% and 76%. The use of spectral libraries reduced the RPIQ of predictions relative to field-scale calibrations from milled samples between 54% and 82% and the RPIQ was reduced between 29% and 70% for predictions when spectral libraries were spiked. The increase in uncertainty was specific to the combination of soil property and sensor analysed. We conclude that there is always a trade-off between prediction accuracy and the costs associated with soil sampling, sample processing and wet chemical analysis. Therefore the relative merits of each approach will depend on the specific case in question.Item Open Access Effect of different organic amendments on actual and achievable yields in a cereal-based cropping system(Springer, 2023-02-27) Albano, Xavier; Whitmore, Andrew P.; Sakrabani, Ruben; Thomas, Cathy L.; Sizmur, Tom; Ritz, Karl; Harris, Jim A.; Pawlett, Mark; Watts, Chris; Haefele, Stephan M.Soil fertility is at risk in intensive cropping systems when using an exclusive regime of inorganic fertilisers without returning sufficient organic matter to the soil. Our objective was to evaluate the long-term effects of commonly used organic amendments interacting with different rates of inorganic nitrogen fertiliser on crop yields of winter wheat. Yield data from winter wheat were collected for five seasons between 2013 and 2019 from a continuous field trial based at Rothamsted Research, SE England. Organic amendments (anaerobic digestate, compost, farmyard manure, and straw at a rate of 0 and 2.5 ton C per hectare) and five rates of inorganic nitrogen fertiliser (NH4NO3 at 0, 80, 150, 190, 220 kg N ha−1) were applied to winter wheat grown in an arable rotation. At the same inorganic N rate, grain yields for the different organic amendment treatments (excluding the straw treatment) were statistically similar but significantly greater than the unamended control treatment. The nitrogen rate required for optimum yields tended to be lower in plots receiving a combination of organic amendments and mineral fertiliser. Based on the observed and modelled response functions, organic amendments excluding straw increased maximum achievable yields compared to non-amended controls. The size of the effect varied between seasons and amendments (+4.6 to +19.0% of the control yield), increasing the mean maximum achievable yield by 8.8% across four seasons. We conclude that the application of organic amendments can increase the yield potential in winter wheat substantially over what is achievable with inorganic fertiliser only.Item Open Access Full chain analysis of nitrogen use efficiency in rice-livestock systems in Uruguay: identifying opportunities for optimizing N management.(Cranfield University, 2022-11) Castillo Velazquez, Jesus; Kirk, Guy; Haefele, Stephan M.Traditionally the rice crop in Uruguay rotates with pastures for direct livestock grazing. This rotation has allowed a constant rice yield increase of 90 kg ha⁻¹ yr⁻¹ over the past 50 years, with yields averaging 8.4 Mg ha⁻¹ in the last decade. Relatively little nitrogen (N) fertilizer is added (80 kg ha⁻¹ yr⁻¹) and the system shows no sign of soil degradation. By contrast, the livestock component is conducted extensively with mostly (75-80%) unimproved pastures, with low animal productivity (100 kg liveweight ha⁻¹ yr⁻¹). This thesis is concerned with how the system N balance is sustained at regional and national scales and if it can be maintained in the future. The objectives were to quantify the N balance (all N inputs – outputs), N surplus (all N inputs – N removed in food products) and N use efficiency (NUE = N in food products / all N inputs) of different rice-livestock- pasture rotations across Uruguay over time. Because historical records of N inputs and outputs are available at regional and national scales, it was possible to assess the whole system in the long term at a farm-gate level. The DNDC model was parameterised with data from a rice long-term experiment and used to compliment the regional N balance data. Results showed a very high average NUE (55–60%) with N balances around neutrality (-6 to +5 kg N ha⁻¹ yr⁻¹) and low N surplus (20 kg N ha⁻¹ yr⁻¹). These values were worse where pastures have been replaced by other cash-crops or rotations shortened. However, there is an opportunity to intensify the system, maintaining the good N balance by improving the livestock component with improved pastures and higher stocking rates to improve N cycling. Results showed the rice-livestock system of Uruguay is a model mixed farming system with several decades of integration.Item Open Access Measured and modeled nitrogen balances in lowland rice-pasture rotations in temperate South America(Frontiers, 2023-04-03) Castillo, Jesús; Kirk, Guy J. D.; Rivero, M. Jordana; Fabini, Guillermo; Terra, José A.; Ayala, Walter; Roel, Alvaro; Irisarri, Pilar; Haefele, Stephan M.Rotational rice systems, involving pastures, other crops and/or livestock, are common in temperate South America, exemplified by the rice-pasture-livestock system of Uruguay which combines very high rice yields with tight nitrogen (N) balances. The generally good nutrient use efficiency in these systems provides a template for nutrient management in other mixed farming systems, if the underlying processes can be sufficiently well quantified and understood. Here, we studied N balances in rice–non-rice rotations in a long-term experiment in Uruguay, with the aim of parameterizing and testing the DNDC model of N dynamics for such systems for use in future work. The experiment includes three rotations: continuous rice (RI-CONT), rice-soybean (RI-SOY) and rice-pasture (RI-PAST). We considered 9 years of data on N balances (NBAL), defined as all N inputs minus all N outputs; N surplus (NSURP), defined as all N inputs minus only N outputs in food products; and N use efficiency (NUE), defined as the fraction of N inputs removed in food products. We parameterized DNDC against measured yield and input and output data, with missing data on N losses inferred from the N balance and compared with literature values. The model performance was assessed using standard indices of mean error, agreement and efficiency. The model simulated crop yields and rice cumulative N uptake very well, and soil N reasonably well. The values of NBAL were +45 and−20 kg N ha−1 yr−1 in RI-CONT and RI-SOY, respectively, and close to zero in RI-PAST (−6 kg N ha−1 yr−1). Values of NSURP decreased in the order RI-CONT >> RI-SOY > RI-PAST (+115, +25 and +13 kg N ha−1 yr−1, respectively). Values of NUE (84, 54, and 48% for RI-SOY, RI-PAST, and RI-CONT, respectively) decreased as NBAL increased. The sensitivity of DNDC's predictions to the agronomic characteristics of the different crops, rotations and water regimes agreed with expectations. We conclude that the DNDC model as parameterized here is suitable for exploring how to optimize N management in these systems.Item Open Access The nitrogen economy of rice-livestock systems in Uruguay(Elsevier, 2021-08-11) Castillo, Jesús; Kirk, Guy J. D.; Rivero, M. Jordana; Dobermann, Achim; Haefele, Stephan M.Over many decades there has been a global trend away from mixed farming and integrated crop-livestock systems to more-intensive single commodity systems. This has distorted local and global nutrient balances, resulting in environmental pollution as well as soil nutrient depletion. Future food systems should include integrated crop-livestock systems with tight nutrient budgets. For nitrogen (N), detailed understanding of processes, fluxes – including of gaseous forms – and budgets at a component level is needed to design productive systems with high N use efficiency (NUE) across the full nutrient chain. In Uruguay, a unique rice-livestock system has been practiced for over 50 years, attaining a high production level for rice (mean grain yields > 8 Mg ha−1) and an average level for livestock (120 kg liveweight gain ha−1 y−1). The aim of this study was to quantify the components of the N balance and NUE of this system, so as to understand its long-term sustainability, and draw conclusions for other regions. Analysis of country-level statistics for each component over the last 16 years shows tight N balances of +3.49, +2.20 and +2.22 kg N ha−1 yr−1 for rice, livestock and the whole system, respectively. Based on average values of N retained in edible food products, NUE values were 65.7, 13.2 and 23.1% for rice, livestock and the whole system, respectively. While NUE of livestock was unchanged over the period, NUE of the rice component decreased due to increasing fertiliser use. Further gains in N efficiency are possible by better integrating the system components. Actions to increase system level NUE include raising pasture and livestock productivity and controlling the increasing use of N fertilisers in rice. Tightly integrated crop-livestock systems can play a significant role in re-shaping global agriculture towards meeting food security, environmental and socioeconomic sustainability targets.Item Open Access Optimizing setup of scan number in FTIR spectroscopy using the moment distance index and PLS regression: application to soil spectroscopy(Nature Publishing Group, 2021-06-25) Barra, Issam; Khiari, Lotfi; Haefele, Stephan M.; Sakrabani, Ruben; Kebede, FassilVibrational spectroscopy such as Fourier-transform infrared (FTIR), has been used successfully for soil diagnosis owing to its low cost, minimal sample preparation, non-destructive nature, and reliable results. This study aimed at optimizing one of the essential settings during the acquisition of FTIR spectra (viz. Scans number) using the standardized moment distance index (SMDI) as a metric that could trap the fine points of the curve and extract optimal spectral fingerprints of the sample. Furthermore, it can be used successfully to assess the spectra resemblance. The study revealed that beyond 50 scans the similarity of the acquisitions has been remarkably improved. Subsequently, the effect of the number of scans on the predictive ability of partial least squares regression models for the estimation of five selected soil properties (i.e., soil pH in water, soil organic carbon, total nitrogen, cation exchange capacity and Olsen phosphorus) was assessed, and the results showed a general tendency in improving the correlation coefficient (R2) as the number of scans increased from 10 to 80. In contrast, the cross-validation error RMSECV decreased with increasing scan number, reflecting an improvement of the predictive quality of the calibration models with an increasing number of scans.Item Open Access Predicting the growth of lettuce from soil infrared reflectance spectra: the potential for crop management(Springer, 2020-08-10) Breure, Timo Samuel; Milne, Alice E.; Webster, R.; Haefele, Stephan M.; Hannam, Jacqueline A.; Moreno-Rojas, S.; Corstanje, RonaldHow well could one predict the growth of a leafy crop from refectance spectra from the soil and how might a grower manage the crop in the light of those predictions? Topsoil from two felds was sampled and analysed for various nutrients, particle-size distribution and organic carbon concentration. Crop measurements (lettuce diameter) were derived from aerial-imagery. Refectance spectra were obtained in the laboratory from the soil in the near- and mid-infrared ranges, and these were used to predict crop performance by partial least squares regression (PLSR). Individual soil properties were also predicted from the spectra by PLSR. These estimated soil properties were used to predict lettuce diameter with a linear model (LM) and a linear mixed model (LMM): considering diferences between lettuce varieties and the spatial correlation between data points. The PLSR predictions of the soil properties and lettuce diameter were close to observed values. Prediction of lettuce diameter from the estimated soil properties with the LMs gave somewhat poorer results than PLSR that used the soil spectra as predictor variables. Predictions from LMMs were more precise than those from the PLSR using soil spectra. All model predictions improved when the efects of variety were considered. Predictions from the refectance spectra, via the estimation of soil properties, can enable growers to decide what treatments to apply to grow lettuce and how to vary their treatments within their felds to maximize the net proft from the cropItem Open Access Regional differences in nitrogen balance and nitrogen use efficiency in the rice–livestock system of Uruguay(Frontiers, 2023-02-14) Castillo, Jesús; Kirk, Guy J. D.; Rivero, Jordana; Haefele, Stephan M.The reintegration of crops with livestock systems is proposed as a way of improving the environmental impacts of food production globally, particularly the impact involving nitrogen (N). A detailed understanding of processes governing N fluxes and budgets is needed to design productive and efficient crop–livestock systems. This study aimed to investigate regional differences in N balance (NBAL, defined as all N inputs minus outputs), N use efficiency (NUE, defined as N outputs/inputs × 100), and N surplus (NSURP, defined as all N inputs minus only outputs in food products) in the rice–livestock system of Uruguay. Three regions across Uruguay are distinguished based on soil fertility and length of pasture rotation. The northern region has high soil fertility and short length of rotation (HFSR); the central region has medium soil fertility and medium length of rotation (MFMR); the eastern region has low fertility and long pasture rotation (LFLR). Results for the last 18 years show a very high NUE (90%) for the rice component in all rotations, associated with negative NBALs ranging from −35 kg N ha−1 yr−1 in HFSR to −3 kg N ha−1 yr−1 in LFLR. However, the livestock component, which overall had low animal productivity (<2 kg N ha−1 yr−1), had low NUE (<10%) but positive NBALs in all the rotations, sustaining N supply in the rice component. At the system level, NUE was high (60%) and NBAL was slightly positive in all rotations (from +2.8 kg N ha−1 yr−1 in HFSR to +8.5 kg N ha−1 yr−1 in LFLR). Because of a recent increase in the N fertilizer dose in rice, NSURP for the overall system was intermediate (40 kg N ha−1 yr−1) and should be monitored in the future. Efforts to improve the system's efficiency should focus on the livestock component.Item Open Access A soil organic carbon indexing and measurement system(Cranfield University, 2021-10) Prout, Jonah Matthew; Kirk, Guy; Haefele, Stephan M.Soil organic carbon (SOC) is an important component of soils for the various goods and services that soils perform. But SOC stocks have declined significantly in soils around the world over many years due to poor land management. To enable land managers and policy makers to manage SOC better, simple guideline values and measures of SOC concentration are needed. An index based on the SOC to clay concentration ratio as related to soil structural conditions was tested for soils across England and Wales using data from the National Soil Inventory (NSI). Threshold values of SOC/clay equal to 1/8, 1/10 and 1/13 indicated Very Good, Good, Moderate and Degraded levels of SOC. Land use was a driver of SOC/clay ratio, with 38% of arable soils classed as Degraded compared with < 7% of permanent grass or woodland soils. To examine how SOC/clay ratios have been changing over time, I analysed data from resampled sites in the NSI (mean interval of 15 years). The Very Good class was particularly vulnerable to losses compared with other classes. This finding agrees with SOC protection being limited by soil clay concentration. Long-term experiments on soils of contrasting clay concentration showed that the index was sensitive to management activities. In further work I explored the use of dry soil spectral analysis to measure SOC and clay concentrations. I compared dry spectral and conventional wet laboratory analyses of soils in the NSI and in the US National Soil Survey Center-Kellogg Soil Survey Laboratory spectral library (NSSC-KSSL). The NSSC-KSSL results, and to a lesser extent the NSI results (which used older, less-accurate wet laboratory analyses), showed that the technique is suitable for assigning soils to Very Good, Degraded, or Good/Moderate ranges. The index provides quantitative guideline concentrations for SOC with a functional basis and scope for rapid assessment.Item Open Access Soil spectroscopy with the use of chemometrics, machine learning and pre-processing techniques in soil diagnosis: recent advances - a review(Elsevier, 2020-12-30) Barra, Issam; Haefele, Stephan M.; Sakrabani, Ruben; Kebede, FassilOver the past two decades soil spectroscopy, particularly, in the infrared range, is becoming a powerful technique to simplify analysis relative to the traditional chemical methods. It is known as a rapid, cost-effective, quantitative and eco-friendly technique, which can provide hyperspectral data with narrow and numerous wavebands, both in the laboratory and in the field. In this context, the present article reviews the recent developments in mid and near infrared techniques coupled with chemometrics and machine learning tools in addition to the preprocessing transformations and variable selection strategies to diagnose soil physical and chemical properties. Both spectral techniques demonstrated a good ability to provide accurate predictions of specific properties. Moreover, the MIR spectroscopy outperformed NIR for the estimation of most indicators used for fertilizers recommendation. Herein, a detailed overview on the opportunities and challenges that soil spectroscopy offers as efficient diagnostic tool in soil science was provided.Item Open Access Spectral soil analysis for fertilizer recommendations by coupling with QUEFTS for maize in East Africa: A sensitivity analysis(Elsevier, 2023-02-24) Asrat, Tadesse Gashaw; Sakrabani, Ruben; Corstanje, Ronald; Breure, Timo; Hassall, Kirsty L.; Kebede, Fassil; Haefele, Stephan M.Laboratory analysis of soil properties is prohibitively expensive and difficult to scale across the soils in sub-Saharan Africa. This results in a lack of soil-specific fertilizer recommendations, where recommendation can only be provided at a regional scale. This study aims to assess the feasibility of using spectral soil analysis to provide soil-specific fertilizer recommendations. Using a range of spectrometers [NeoSpectra Saucer (NIR), FieldSpec 4 (vis-NIR) with contact probe or mug light interface, FTIR Bruker Tensor 27 (MIR)], 346 archived soil samples (0–20 cm) with known soil chemical properties collected from Ethiopia, Kenya and Tanzania were scanned. Partial least square regression (PLSR) was used to develop prediction models for selected soil properties including pH, soil organic carbon (SOC), total nitrogen, Olsen P, and exchangeable K. These predicted properties, and associated uncertainty, were used to derive fertilizer recommendations for maize using the Quantitative Evaluation of the Fertility of Tropical Soils (QUEFTS) model parameters for sub-Saharan Africa. Most soil properties (pH, SOC, total nitrogen, and exchangeable K) were well predicted (Concordance Correlation Coefficient values between 0.88 and 0.96 and Ratio of Performance to Interquartile values between 1.4 and 5.9) by all the spectrometers but there were performance variations between soil properties and spectrometers. Use of the predicted soil data for the development of fertilizer recommendations gave promising results when compared to the recommendations obtained with the conventional soil analysis. For example, the least performing NeoSpectra Saucer over/under-estimated up to 8 and 24 kg ha-1N and P, respectively, though there was insignificant variation in estimation of P fertilizer among spectrometers. We conclude that spectral technology can be used to determine major soil properties with satisfactory precision, sufficient for specific fertilizer decision making in East Africa, possibly even with portable equipment in the field.Item Open Access What is a good level of soil organic matter? An index based on organic carbon to clay ratio(Wiley, 2020-06-12) Prout, Jonah M.; Shepherd, Keith D.; McGrath, Steve P.; Kirk, Guy J. D.; Haefele, Stephan M.Simple measures of appropriate levels of soil organic matter are needed for soil evaluation, management and monitoring, based on readily‐measurable soil properties. We test an index of soil organic matter based on the soil organic carbon (SOC) to clay ratio, defined by thresholds of SOC/clay ratio for specified levels of soil structural quality. The thresholds were originally delineated for a small number of Swiss soils. We assess the index using data from the initial sampling (1978–83) of the National Soil Inventory of England and Wales, covering 3809 sites under arable land, grassland and woodland. Land use, soil type, annual precipitation and soil pH together explained 21% of the variance in SOC/clay ratio in the dataset, with land use the most important variable. Thresholds of SOC/clay ratio of 1/8, 1/10 and 1/13 indicated the boundaries between ‘very good’, ‘good’, ‘moderate’ and ‘degraded’ levels of structural condition. On this scale, 38.2, 6.6, and 5.6% of arable, grassland and woodland sites, respectively, were degraded. The index gives a method to assess and monitor soil organic matter at national, regional or sub‐regional scales based on two routinely measured soil properties. Given the wide range of soils and land uses across England and Wales in the dataset used to test the index, we suggest it should apply to other European soils in similar climate zones.