Article
Soil Science
Ruby Hume, Petra Marschner, Sean Mason, Rhiannon K. Schilling, Brian Hughes, Luke M. Mosley
Summary: Acidification of soils limits agricultural production globally. Traditional lime application is effective for surface acidity, but not for subsurface acidity. In this study, Mid Infrared (MIR) spectroscopy was used to monitor lime movement through soils at high resolution. Results showed limited alkalinity movement in all trial sites, with increased movement in longer-term sites. Incorporating residual lime and additional applications may be necessary to remediate subsurface acidity.
SOIL & TILLAGE RESEARCH
(2023)
Article
Soil Science
Longnan Shi, Sharon O'Rourke, Felipe Bachion de Santana, Karen Daly
Summary: Soil bulk density (BD) is an important physical parameter for soil quality control and calculation of soil organic carbon (SOC) stock. However, laboratory analysis of BD is time-consuming and expensive, making it difficult for national-scale soil assessments. This study used chemometric and machine learning algorithms to estimate BD in Irish soil based on MIR spectral libraries. The best performance was achieved with a SVM model, which had a RPIQ of 3.61, R2 value of 0.81, and RMSEP of 0.132. The spectral soil BD model outperformed traditional pedo-transfer functions overall and showed similar accuracy for the A horizon but improved performance for other horizons.
Article
Soil Science
Said Nawar, Abdul M. Mouazen
Summary: Accurate assessment of key soil attributes using mid-infrared spectroscopy (MIRS) is crucial for precision agriculture. This research compares the performance of the stacked generalisation machine learning (SG-ML) framework and multilayer perceptron (MLP) deep learning method for predicting soil attributes. Results show that SG-ML performs better than MLP, achieving excellent predictive performance for OC, K, and P.
EUROPEAN JOURNAL OF SOIL SCIENCE
(2022)
Article
Chemistry, Analytical
Andrey Bogomolov, Tatiana Sakharova, Iskander Usenov, Camillo Mizaikoff, Valeria Belikova, Stanislav Perevoschikov, Viacheslav Artyushenko, Olga Bibikova
Summary: A multispectral fiber optic probe has been developed for simultaneous analysis of various liquid and solid samples using attenuated total reflection mid-infrared spectroscopy and fluorimetry. Technical evaluation has confirmed its output signal quality comparable to single-method probes, demonstrating the capability to deliver complementary chemical information. The qualitative analysis of biological tissue is highlighted as one of the key applications of this developed multispectral probe.
ANALYTICAL CHEMISTRY
(2021)
Article
Physics, Applied
Mohit Kumar, Pawan Kumar, Andres Vega, Maximilian A. Weissflog, Thomas Pertsch, Frank Setzpfandt
Summary: By tuning the pump wavelength, we have successfully achieved phase matching for nondegenerate photon pair generation in a silver gallium sulfide AgGaS2 crystal, generating photon pairs in the mid-infrared and visible spectral ranges. Additionally, we demonstrated photon pair generation with broad spectral bandwidth.
APPLIED PHYSICS LETTERS
(2021)
Article
Geosciences, Multidisciplinary
Yongsheng Hong, Jonathan Sanderman, Tomislav Hengl, Songchao Chen, Nan Wang, Jie Xue, Zhiqing Zhuo, Jie Peng, Shuo Li, Yiyun Chen, Yaolin Liu, Abdul Mounem Mouazen, Zhou Shi
Summary: This study used a globally distributed topsoil MIR spectral library to predict SOC using different modeling methods. The results showed that fractional-order derivatives (FODs) improved the prediction accuracy of SOC. The 0.75-order derivative was found to be optimal for ratio index-based linear regression (RI-LR) models, while the convolutional neural network (CNN) model outperformed other models for full-spectrum modeling.
Article
Environmental Sciences
Jianxin Yin, Zhan Shi, Baoguo Li, Fujun Sun, Tianyu Miao, Zhou Shi, Songchao Chen, Meihua Yang, Wenjun Ji
Summary: This study aimed to explore the feasibility of using in situ mid-infrared spectroscopy for predicting soil total nitrogen and total phosphorus. The results showed that laboratory mid-infrared spectroscopy was more accurate in predicting total nitrogen than in situ mid-infrared spectroscopy, mainly due to the influence of soil moisture.
Article
Green & Sustainable Science & Technology
Kuntal M. Hati, Nishant K. Sinha, Monoranjan Mohanty, Pramod Jha, Sunil Londhe, Andrew Sila, Erick Towett, Ranjeet S. Chaudhary, Somasundaram Jayaraman, Mounisamy Vassanda Coumar, Jyoti K. Thakur, Pradip Dey, Keith Shepherd, Pankaj Muchhala, Elvis Weullow, Muneshwar Singh, Shiv K. Dhyani, Chandrashekhar Biradar, Javed Rizvi, Ashok K. Patra, Suresh K. Chaudhari
Summary: This study evaluates the potential of mid-infrared spectroscopy for the rapid and nondestructive measurement of important soil properties of Alfisols. The results show that the partial least-squares regression (PLSR) models perform better than other regression techniques, except for electrical conductivity. However, the predictive models perform poorly for electrical conductivity and extractable nutrients.
Article
Multidisciplinary Sciences
Caleb R. Whatley, Nuwan K. Wijewardane, Raju Bheemanahalli, K. Raja Reddy, Yuzhen Lu
Summary: Fourier transform mid infrared (FT-MIR) spectroscopy combined with modeling techniques has been studied as a useful tool for multivariate chemical analysis in agricultural research. However, the sample preparation requirement of this method, which involves drying and fine grinding, can increase the time and cost of analysis. This study investigates the effect of different grinding times on model performance using leaf tissue samples from various crop species. The results suggest that a 5-minute fine grinding time is optimal in terms of overall model performance and sample preparation time.
SCIENTIFIC REPORTS
(2023)
Article
Soil Science
Junwei Wang, Tongqing Liu, Jixiong Zhang, Huimin Yuan, Gifty E. Acquah
Summary: This study investigated variable selection methods for estimating soil organic carbon (SOC) content and found that the ICO-SPA method can improve prediction accuracy and identify the most sensitive wavebands for SOC. The prediction accuracy of the ICO-SPA-PLSR model was similar to that of the other three variable selection methods.
EUROPEAN JOURNAL OF SOIL SCIENCE
(2022)
Article
Soil Science
Yongsheng Hong, Muhammad Abdul Munnaf, Angela Guerrero, Songchao Chen, Yaolin Liu, Zhou Shi, Abdul Mounem Mouazen
Summary: Spectral techniques, including the fusion of visible-to-near-infrared and mid-infrared absorbance, can improve the estimation of soil organic carbon. The use of continuous wavelet transform and optimal band combination strategies contribute to the accuracy of the prediction models. Among the investigated models, the combination of visible-to-near-infrared and mid-infrared using the optimal band combination fusion at a specific scale yielded the best prediction.
SOIL & TILLAGE RESEARCH
(2022)
Article
Soil Science
Ruby Hume, Petra Marschner, Rhiannon K. Schilling, Sean Mason, Luke M. Mosley
Summary: Globally, soil acidity poses a threat to crop production, and the use of mid infrared (MIR) spectroscopy for the detection of calcium carbonate (CaCO3) in soils has potential in agricultural contexts. This study aimed to develop MIR spectroscopy methods for the detection of low concentrations of CaCO3 in soils. The findings showed that MIR spectroscopy can accurately predict carbonate concentrations and has similar detection limits as traditional methods.
Article
Soil Science
Isabel Greenberg, Michael Seidel, Michael Vohland, Bernard Ludwig
Summary: Comparison of laboratory and in situ visible/near-infrared and mid-infrared spectroscopy is necessary for predicting soil properties. Lab MIR models outperformed in situ models for total OC, N and pH, while estimations for texture were comparable or slightly inferior to lab visNIR. Loss of accuracy from lab to field measurement was lower for visNIR at 14% median soil water content. Rankings of field visNIRS vs MIRS performance for C and N estimation are influenced by moisture levels.
EUROPEAN JOURNAL OF SOIL SCIENCE
(2022)
Review
Biochemistry & Molecular Biology
Charlotte Delrue, Sander De Bruyne, Marijn M. Speeckaert
Summary: Traditional renal biomarkers are insensitive for early detection of kidney disease. Infrared spectroscopy offers a label-free and non-destructive method for quick and inexpensive diagnosis of kidney disorders. This review provides an overview of the applications of near- and mid-infrared spectroscopy in patients with acute kidney injury and chronic kidney disease.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2023)
Article
Automation & Control Systems
J. Haritha, R. S. Valarmathi, M. Kalamani
Summary: In this study, the effect of different concentrations of urea on mid-infrared transmittance spectra in soil was analyzed using Partial Least Square Regression and Support Vector Machine algorithms. Results show that the Support Vector Machine model provides better prediction accuracy compared to the Partial Least Square Regression model.
INTELLIGENT AUTOMATION AND SOFT COMPUTING
(2022)
Article
Environmental Sciences
Fei Ma, Changwen Du, Yiqiang Zhang, Xuebin Xu, Jianmin Zhou
Summary: This study utilized different spectroscopic techniques to investigate the spatial distribution of elements in soil and the binding features of salt-organic associations. The results showed heterogeneous distributions of Mg, Ca, Na, and K in saline soil, with significant correlations between Mg and Ca, and a negative correlation between K and soil organic matter content.
LAND DEGRADATION & DEVELOPMENT
(2021)
Article
Food Science & Technology
Lianlian Wei, Fei Ma, Changwen Du
Summary: FTIR-PAS was used for quick assessment of rice quality in response to rising CO2/temperature, with PCA identifying the influences of elevated CO2 and higher temperature. Intensities of selected spectral bands showed positive linear correlation with starch, protein, and lipid content, demonstrating the potential of FTIR-PAS to detect rice responses to climate change.
Article
Polymer Science
Yaxiao Du, Xuebin Xu, Fei Ma, Changwen Du
Summary: In this study, MOFs were successfully synthesized using a mechanochemical method, characterized by XRD, FTIR-ATR, and LIBS, and shown to have distinct elemental compositions and nutrient release profiles. The results demonstrate the potential application of MOFs as a novel slow-release fertilizer.
Article
Agronomy
Yuming Guo, Haitao Xiang, Zhenwang Li, Fei Ma, Changwen Du
Summary: The study found that rice yield is influenced by both agronomic traits and climate factors, and the FFBN model performs better in prediction compared to the PLSR model. The optimal FFBN structure consists of one hidden layer with 29 neurons.
Article
Environmental Sciences
Haixiao Ge, Fei Ma, Zhenwang Li, Zhengzheng Tan, Changwen Du
Summary: Ensemble models combining various image features and machine learning algorithms were proposed for phenology detection in rice breeding, with the soft voting strategy showing the best performance. The overall accuracy and F1 scores were significantly improved with the ensemble models.
Article
Chemistry, Analytical
Mengjin Hu, Fei Ma, Zhenwang Li, Xuebin Xu, Changwen Du
Summary: Rapid quantification of soil organic matter is a challenge for assessing soil health and managing fertility in agricultural soil. This study utilized laser-induced breakdown spectroscopy (LIBS) and a self-adaptive partial least squares regression model (SAM-PLSR) to predict soil organic matter content. The results showed that optimizing the calibration parameters, such as sample selection and sample location, improved the prediction accuracy. Additionally, the variances of the target property and the spectra similarity of the soil background were found to be crucial factors for the calibration model.
Article
Environmental Sciences
Zhenwang Li, Zhengchao Qiu, Haixiao Ge, Changwen Du
Summary: Short episodes of low-temperature stress during reproductive stages can cause significant crop yield losses. This study characterized the spatial and temporal variability of cold stress during the rice heading and flowering stages in China and its impact on rice growth and yield. The results showed that cold stress was unevenly distributed in the study region, with the most severe events observed in the Yunnan Plateau. With increasing temperatures, cold stress decreased, but the phenological shift effects slowed down this trend and led to an underestimation of cold stress magnitude. Cold stress during heading and flowering still poses a potential threat to rice production.
Article
Agronomy
Haixiao Ge, Fei Ma, Zhenwang Li, Changwen Du
Summary: This study utilized a low-cost UAV platform and RF models combined with phenological data and color VIs to accurately estimate the yield of rice cultivars, demonstrating the significant improvement in model performance with the inclusion of phenological data. These findings suggest that the RF model is a cost-effective way to estimate yield in rice breeding by combining phenological data and color VIs.
Article
Agronomy
Haixiao Ge, Fei Ma, Zhenwang Li, Changwen Du
Summary: Global sensitivity analysis has shown Tavg, G4, and P2O to be the most influential parameters across cultivars during the growth season, with PORM having a considerable impact on yield regardless of specific-stage variations of climate conditions. The study highlights the comprehensive effects of crop parameters on model outputs under different cultivars and climate variations.
Article
Environmental Sciences
Zhengchao Qiu, Fei Ma, Zhenwang Li, Xuebin Xu, Changwen Du
Summary: This study used unmanned aerial systems (UAS) to rapidly and accurately acquire rice growth variables, which are useful for assessing rice growth and precision fertilization. The results showed that different nitrogen treatments had a significant impact on rice growth variables. Prediction models were built using spectral indices derived from visible and NIR images and key rice growth variables measured in the field, achieving high accuracy.
Article
Biochemistry & Molecular Biology
Cong Ge, Xuebin Xu, Fei Ma, Jianmin Zhou, Changwen Du
Summary: Benefitting from the unique structure of leaf cuticle layer, the researchers have successfully improved the hydrophobicity of controlled-release fertilizer by mimicking the leaf surface structure. By loading carnauba wax onto the polyacrylate coating, the appearance and release duration of the fertilizer were improved effectively.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2022)
Article
Chemistry, Multidisciplinary
Ke Wu, Xuebin Xu, Fei Ma, Changwen Du
Summary: In this study, iron-based MOFs (Fe-MOFs) were synthesized in both laboratory and pilot scales, and their structure and components were characterized. The release and degradation behaviors of nutrients in Fe-MOFs were investigated. The results showed that Fe-MOFs could serve as a fertilizer with varied nutrients and controlled release.
Article
Biochemistry & Molecular Biology
Ke Wu, Fei Ma, Cuilan Wei, Fangqun Gan, Changwen Du
Summary: This study explored a rapid method for determining (NO3-)-N-15 content in water bodies using Fourier transform infrared attenuated total reflectance spectroscopy (FTIR-ATR) coupled with a deconvolution algorithm and partial least squares regression (PLSR) model. The characteristic peaks of (NO3-)-N-14/(NO3-)-N-15 mixtures with different ratios were observed, and the (NO3-)-N-15 proportion was negatively correlated with the wavenumber of absorption peaks. PLSR models based on deconvoluted spectra showed good performance with ratio of prediction to deviation (RPD) values above 2.0 and correlation coefficients (R-2) above 0.84. The use of FTIR-ATR combined with deconvolution and PLSR provided a rapid, simple, and affordable method for determining (NO3-)-N-15 content in water bodies, facilitating the study of nitrate sources and water environment quality management.
Article
Environmental Sciences
Xuebin Xu, Changwen Du, Fei Ma, Zhengchao Qiu, Jianmin Zhou
Summary: In this study, a framework based on machine learning using Fourier mid-infrared attenuation total reflectance spectroscopy (FTIR-ATR), Sentinel-2 images, and DEM derivatives was developed to estimate soil organic matter (SOM) with high accuracy and resolution. The PLS, SVR, and CNN models performed well in predicting SOM from FTIR-ATR spectra, and the performance was enhanced further by using Sentinel-2 images and DEM derivatives. The PLS and SVR models provided high-resolution and highly variable SOM maps compared to the Kriging approach.
Article
Chemistry, Multidisciplinary
Ke Wu, Xuebin Xu, Fei Ma, Changwen Du
Summary: Based on the controlled-delivery function of metal-organic frameworks (MOFs), iron-based MOFs (Fe-MOFs) were explored as a novel fertilizer in laboratory studies. Fe-MOFs were successfully synthesized in both laboratory and pilot scales, with nutrient release rate and pattern matching crop growth, showing potential for industrial application in the fertilizer industry.
