Spectroscopic determination of major nutrients (N, P, K) of soil

Thesis (Master)--Izmir Institute of Technology, Food Engineering, Izmir, 2004Includes bibliographical references (leaves: 84-88)Text in English; Abstract: Turkish and Englishxvi, 99 leavesThe aim of this study was to determine the major soil nutrients (nitrogen, phosphorus and potassium) which mainly affect the raw material quality of food, using near infrared reflectance spectroscopy (1000-2500 nm). Genetic inverse least squares and partial least squares were used to predict the concentrations of major soil nutrients.The soil samples, collected from Menemen Application and Research Farms, were prepared for the near infrared analysis by using two different methods. According to the first method, two experiments were performed. The soil samples of which were oven dried and screened through a 2 mm sieve, were mixed with NPK fertilizer in the concentration range of 1-15% (wt/wt) (first experiment), and with NH4NO3 and TSP fertilizers in the concentration range of 0.075-0.3% (wt/wt) (second experiment). Using genetic inverse least squares method, regression coefficients of 0.9820, 0.9779 and 0.9906 were obtained for the prediction of nitrogen, phosphorus and potassium concentrations in samples containing NPK fertilizer, respectively. In the second experiment, prediction of nitrogen concentration in samples containing NH4NO3 fertilizer was done reliable with a regression coefficient of 0.8409 using genetic inverse least squares method. On the other hand, regression coefficient of 0.6005 was obtained for the prediction of phosphorus concentration in samples containing TSP fertilizer with the same statistical method.The second method differed from the first one by eliminating the drying of soil samples and moisturizing step following the addition of fertilizers into soil samples. The aim was to prevent baseline shifts in the spectra arising from the moisture changes in the samples. Five types of fertilizer [KNO3, CaNO3, TSP, (NH4)2SO4, NPK] were used in the preparation of samples in the concentration range of 0.02-0.5% (wt/wt). Using genetic inverse least squares method, calibration models produced between the reflectance spectra and the nutrient concentrations had regression coefficients greater than 0.80, however the prediction ability of the models was poor (R2<0.50) except for the samples containing (NH4)2SO4 and NPK fertilizers. The regression coefficients for the prediction of nitrogen and sulfur concentrations in (NH4)2SO4 containing samples were found as 0.8620 and 0.8555, respectively. For the prediction of nitrogen, phosphorus and potassium concentrations in NPK containing samples, the regression coefficients were found as 0.6737, 0.7633 and 0.8724, respectively. The partial least squares method was also used for the prediction of nutrient concentrations in the samples prepared according to the second method. Except samples containing (NH4)2SO4 fertilizer, nitrogen, phosphorus and potassium amounts could not be predicted in the other samples using partial least squares method (R2<0.20). The regression coefficients obtained for the prediction of nitrogen and sulfur amounts in (NH4)2SO4 containing samples were 0.9301.An additional work was carried out with laboratory analyzed soil samples collected from several points of two agricultural fields in Menemen Application and Research Farms. Total nitrogen, extractable phosphorus and exchangeable potassium amounts were determined by Agricultural Engineering Department of Ege University according to the Kjeldahl method, Bingham method and ammonium acetate method, respectively.Predictions of these nutrient concentrations by genetic inverse least squares method were poor (R2< 0.20). Using partial least squares method, the nutrient concentrations could not be predicted (factor number . 0).The results of this study indicate that, near infrared reflectance technique provided rapid, non-destructive and simultaneous determination of nitrogen, phosphorus and potassium concentrations in soil- fertilizer mixtures depending on the sample preparation steps, fertilizer types and concentrations and multivariate calibration methods (genetic inverse least squares and partial least squares methods)

Remote Sensing for Precision Nitrogen Management

This book focuses on the fundamental and applied research of the non-destructive estimation and diagnosis of crop leaf and plant nitrogen status and in-season nitrogen management strategies based on leaf sensors, proximal canopy sensors, unmanned aerial vehicle remote sensing, manned aerial remote sensing and satellite remote sensing technologies. Statistical and machine learning methods are used to predict plant-nitrogen-related parameters with sensor data or sensor data together with soil, landscape, weather and/or management information. Different sensing technologies or different modelling approaches are compared and evaluated. Strategies are developed to use crop sensing data for in-season nitrogen recommendations to improve nitrogen use efficiency and protect the environment

The Long-term Dynamics of Soil Organic Carbon in the Anthropogenic Soils of Scotland's Medieval Urban Landscape

In an interdisciplinary study requiring the synergistic association of historical evidence and chemical and biochemical analyses, this thesis investigates the properties and characteristics of historically modified soils known as anthrosols. These soils, developed through the anthropogenic addition of high volumes of organic-rich municipal waste materials to land, including human and animal waste, as part of the waste management practices in medieval urban communities in Scotland at St Andrews, Roxburgh and Elgin, offer an insight to the state and dynamics of these organic material. Soil is one of the most sensitive environmental domains to transformation. These transformations are visible from the alterations to the physical and chemical properties of soil. Anthropogenic activities may leave behind signatures in the soil in the form of artefacts, ecofacts, elemental enrichment or depletion, enhancement in soil magnetic properties and organic matter content. In the historical dimension of this study, the observable features and measurable properties of soil profiles are exploited to reveal past organisation and functions of cultural landscapes by carefully studying the stratigraphic units of soil profile, and examining the association of each unit with settlement artefacts and soil properties. Through comparison with historical records of past events on the respective study sites, the relationship between the soils record of past human activities is observed through physical, chemical and biochemical properties. The historical record is used to assess if such evidence can be used reliably to develop the account of site use for the medieval burghs of Scotland. In the environmental aspect, investigation focuses on the physical and chemical conditions of these soils in terms of their carbon content, composition, residence time estimates and their role in global C cycle and terrestrial carbon budgeting. Past investigations of anthopogenically-deepened soils have been interpreted with respect to historical site use, however, the environmental implications of the resultant accumulated organic material or residue have not previously been considered in much detail. A particular novelty of this aspect of the project is that it is an in-depth examination of anthropogenic soils with known histories extending into the medieval period. This time-depth allows a new understanding of the processes and products of decomposition of known organic materials that were added to soil. The biophysicochemical data obtained from these soils such as their extant organic carbon content and variability with depth, the composition of the various carbon species that together constitute soil organic matter, and biological community and activity (microorganisms and enzymes) provides critical information on the relative recalcitrance, state of decomposition, and the mechanism of stabilisation of these materials in the soil

Non-destructive prediction of ‘marsh’ grapefruit (citrus x paradisi MacFad) postharvest quality and physiological rind disorders using visible to near infrared spectroscopy.

Master of Science in Horticulture. University of KwaZulu-Natal, Pietermaritzburg 2016.Abstract available in PDF file

Near-infrared spectroscopy and machine learning for classification of food powders during a continuous process

In food production environments, the wrong powder material is occasionally loaded onto a production line which impacts food safety, product quality, and production economics. The aim of this study was to assess the potential of using Near Infrared (NIR) spectroscopy combined with Machine Learning to classify food powders under motion conditions. Two NIR sensors with different wavelength ranges were compared and the ML models were tasked with classifying between 25 food powder materials. Eleven different spectra pre-processing methods, three feature selection methods, and five algorithms were investigated to find the optimal ML pipeline. It was found that pre-processing the spectra using autoencoders followed by using support vector machines with the all spectral wavelengths from both sensors was most accurate. The results were improved further using under-sampling and boosting. Overall, this method achieved 99.52, 97.12, 94.08, and 91.68% accuracy for the static, 0.017, 0.036 and 0.068 m s-1 sample speeds. The models were also validated using an independent test sets

Impacts of Global Change and Soil Properties on Phosphorus Transformation and Plant Responses in Alpine Grassland Ecosystem on the Northeastern Tibetan Plateau

The grassland ecosystems of the Tibetan Plateau have witnessed substantial transformations in recent decades, driven by various global factors, including alterations in temperature and precipitation, nitrogen (N) deposition, and regional effects. Despite documented shifts in species richness and distribution towards higher elevations, there is a scarcity of comprehensive plant and soil data along elevation gradients in alpine grasslands. The intricate interplay between soil properties and nutrient supply on vegetation patterns at high altitudes, particularly the response of the "grass-line" to global warming, remains unexplored. To bridge these knowledge gaps, our research investigated the impacts of global changes, specifically warming and N deposition, and soil properties on soil phosphorus (P) transformation and plant P uptake. Leveraging insights from long-term nutrient addition experiments, random sampling, and open-top chamber experiments along elevation gradients in an alpine grassland on the northeastern Tibetan Plateau, the study delved into soil properties such as texture, bulk density, soil organic carbon (SOC), and soil P fractions. Furthermore, it explores plant and microbial P pools, P acquisition strategies, and biomass. Results revealed that N input had a discernible effect on plant P requirements, particularly under conditions of deficient soil available P. Changes in P acquisition strategies wielded a more substantial influence on community structure and composition than alterations in root traits. The addition of P significantly impacted plant growth, signifying a shift from nitrogen to P limitation with increased N input. Soil properties exhibited variations among sites, but pH remained stable at 0–10 cm soil depth due to the adequate levels of calcium and magnesium in the soil, which could buffer the impact of N deposition on soil acidification in the grassland ecosystem. Strong positive correlations were observed between organic P pools, SOC, and total N, highlighting the pivotal role of soil organic matter in sustaining soil P reserves. More importantly, P limitation did not emerge as the primary factor propelling grasses to higher elevations; instead, other soil properties and nutrients might play a key role. These findings underscore the importance of specific combinations of soil properties in constraining plant growth on the northeastern plateau, thereby influencing biodiversity and biomass production. This research highlights the factors influencing effective soil nutrients and provides valuable insights into predicting the impact of global changes on the stability and productivity of alpine grassland ecosystems

The use of a rapid incineration field test for determining soil organic carbon in the Southern Cape Region

Knowledge of soil organic carbon levels is important both for agricultural effectiveness and soil carbon sequestration accounting, especially against the backdrop of increased climate change impacts and pressure on food production landscapes. However, current methods for soil carbon determination are expensive, energy intensive, time consuming and potentially hazardous leading to a call for alternative methods, which should be cheap, fast, simple, accurate, safe and usable where resources and soil analysis laboratories are limited. To this end the student invented a novel rapid incineration field test (RIFT) for determining soil organic carbon and tested its validity in this study. This method incorporates principles found in dry combustion as well as loss-on-ignition and quantifying organic carbon through gravimetric analysis. In order to illustrate effectiveness and accuracy it was necessary to correlate RIFT with a reference method, in this instance dry combustion with a Leco device as well as another commonly used indirect method namely the Walkley-Black wet chemical oxidation method. Samples from eleven soil forms were collected from the Southern Cape region and they were subjected to the three testing methods. It was found that RIFT is indeed as effective and in 72% of the soil forms even more effective than Walkley-Black. Furthermore, it was ascertained whether the accuracy of RIFT can be improved by correcting for clay content. The correlation of RIFT with clay % was not very significant and clay % as a variable was therefore not used in this study to obtain further refinement of RIFT predictions. Another finding was also that RIFT illustrated less variability than both the Leco and Walkley-Black methods. Lastly it was ascertained that the RIFT device and methodology is indeed cost effective, energy efficient, fast and safe in terms of the need to use potentially hazardous chemicals.Thesis (MA) -- Faculty of Science, School of Natural Resource Management, 202

The use of a rapid incineration field test for determining soil organic carbon in the Southern Cape Region

Knowledge of soil organic carbon levels is important both for agricultural effectiveness and soil carbon sequestration accounting, especially against the backdrop of increased climate change impacts and pressure on food production landscapes. However, current methods for soil carbon determination are expensive, energy intensive, time consuming and potentially hazardous leading to a call for alternative methods, which should be cheap, fast, simple, accurate, safe and usable where resources and soil analysis laboratories are limited. To this end the student invented a novel rapid incineration field test (RIFT) for determining soil organic carbon and tested its validity in this study. This method incorporates principles found in dry combustion as well as loss-on-ignition and quantifying organic carbon through gravimetric analysis. In order to illustrate effectiveness and accuracy it was necessary to correlate RIFT with a reference method, in this instance dry combustion with a Leco device as well as another commonly used indirect method namely the Walkley-Black wet chemical oxidation method. Samples from eleven soil forms were collected from the Southern Cape region and they were subjected to the three testing methods. It was found that RIFT is indeed as effective and in 72% of the soil forms even more effective than Walkley-Black. Furthermore, it was ascertained whether the accuracy of RIFT can be improved by correcting for clay content. The correlation of RIFT with clay % was not very significant and clay % as a variable was therefore not used in this study to obtain further refinement of RIFT predictions. Another finding was also that RIFT illustrated less variability than both the Leco and Walkley-Black methods. Lastly it was ascertained that the RIFT device and methodology is indeed cost effective, energy efficient, fast and safe in terms of the need to use potentially hazardous chemicals.Thesis (MA) -- Faculty of Science, School of Natural Resource Management, 202