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A special issue of Molecules (ISSN 1420-3049). This special issue belongs to the section "Analytical Chemistry".

Deadline for manuscript submissions: closed (31 March 2024) | Viewed by 8408

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Special Issue Editors

Prof. Dr. Changwen Du

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Guest Editor

Institute of Soil Science, Chinese Academy of Sciences, Nanjing, China
Interests: agricultural products; infrared spectroscopy; laser induced breakdown spectroscopy; proximal sensing; chemometrics

Prof. Dr. Yunlei Xianyu

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Guest Editor

College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou, China
Interests: nanoparticles; biomolecules; food security; bio-sensing; advanced materials
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

A large amount of new and original knowledge in analytical chemistry has been raised and applied in agriculture, and therefore, a Special Issue entitled “Analytical Chemistry in Agricultural Application” is being launched. This Special Issue will collect full papers and high-quality reviews covering the all-around progress in new analytical methods and instruments as well as their applications in agriculture. The submitted articles should target fields including, but not limited to, the following: agricultural science, food science, environmental science, soil and water science, and crop and fertilizer science. Topics may include chemical reactions and selectivity, algorithms and data processing, elemental and molecular characterization, instrumentation, spectroscopy, and surface analysis. We invite our colleagues involved in all branches of analytical chemistry to make contributions to this Special Issue.

Prof. Dr. Changwen Du
Prof. Dr. Yunlei Xianyu
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Molecules is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

agricultural products
crop health
soil and water
proximal sensing
bio-sensing, modern spectroscopic technology
machine learning algorithms

Published Papers (5 papers)

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Research

14 pages, 2139 KiB

Open AccessArticle

Amine Switchable Hydrophilic Solvent Vortex-Assisted Homogeneous Liquid–Liquid Microextraction and GC-MS for the Enrichment and Determination of 2, 6-DIPA Additive in Biodegradable Film

by Kai Cai, Qiang Liu, Yechun Lin, Xingyou Yang, Qi Liu, Wenjie Pan and Weichang Gao

Molecules 2024, 29(9), 2068; https://doi.org/10.3390/molecules29092068 - 30 Apr 2024

Viewed by 261

Abstract

2, 6-diisopropylaniline (2, 6-DIPA) is a crucial non-intentionally organic additive that allows the assessment of the production processes, formulation qualities, and performance variations in biodegradable mulching film. Moreover, its release into the environment may have certain effects on human health. Hence, this study developed simultaneous heating hydrolysis–extraction and amine switchable hydrophilic solvent vortex-assisted homogeneous liquid–liquid microextraction for the gas chromatography–mass spectrometry analysis of the 2, 6-DIPA additive and its corresponding isocyanates in poly(butylene adipate-co-terephthalate) (PBAT) biodegradable agricultural mulching films. The heating hydrolysis–extraction conditions and factors influencing the efficiency of homogeneous liquid–liquid microextraction, such as the type and volume of amine, homogeneous-phase and phase separation transition pH, and extraction time were investigated and optimized. The optimum heating hydrolysis–extraction conditions were found to be a H₂SO₄ concentration of 2.5 M, heating temperature of 87.8 °C, and hydrolysis–extraction time of 3.0 h. As a switchable hydrophilic solvent, dipropylamine does not require a dispersant. Vortex assistance is helpful to speed up the extraction. Under the optimum experimental conditions, this method exhibits a better linearity (0.0144~7.200 μg mL⁻¹ with R = 0.9986), low limit of detection and quantification (0.0033 μg g⁻¹ and 0.0103 μg g⁻¹), high extraction recovery (92.5~105.4%), desirable intra- and inter-day precision (relative standard deviation less than 4.1% and 4.7%), and high enrichment factor (90.9). Finally, this method was successfully applied to detect the content of the additive 2, 6-DIPA in PBAT biodegradable agricultural mulching films, thus facilitating production process monitoring or safety assessments. Full article

(This article belongs to the Special Issue Analytical Chemistry in Agriculture Application)

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15 pages, 1906 KiB

Open AccessArticle

Biochemical Composition, Antioxidant Activity and Antiproliferative Effects of Different Processed Garlic Products

by Jingyang Lu, Nannan Li, Shuqin Li, Wei Liu, Mingyue Li, Min Zhang and Haixia Chen

Molecules 2023, 28(2), 804; https://doi.org/10.3390/molecules28020804 - 13 Jan 2023

Cited by 4 | Viewed by 1683

Abstract

Garlic (Allium sativum L.) is a type of agricultural product that is widely used as a food spice, herb and traditional medicine. White garlic (WG) can be processed into several kinds of products, such as green garlic (GG), Laba garlic (LAG) and black garlic (BG), which have multiple health effects. In this study, GC-MS (gas chromatography-mass spectrometry), DPPH (1,1′-diphenyl-2-propionyl hydrazide) radical scavenging, hydroxyl radical scavenging and MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide) in vitro assays were used to compare the composition, antioxidant and antiproliferation effects of different processed garlic extracts. The relationship between the constituents and the bioactivities was analyzed using the principal components analysis (PCA) and heatmap analysis. BG showed the highest antioxidant activity (IC₅₀ = 0.63 ± 0.02 mg/mL) in DPPH radical assays and the highest antioxidant activity (IC₅₀ = 0.80 ± 0.01 mg/mL) by hydroxyl radical assay. Moreover, GC-MS results showed that 12 organosulfur compounds were detected in the extracts of four garlic products, and allyl methyl trisulfide showed a positive relation with the anticancer activity on SMMC-7721 cells (hepatocellular carcinoma cells). The results suggested that the processing of garlic had a significant influence on the constituents and antioxidant effects and that GG, LAG and BG might be better candidates for the related functional food products compared to WG. Full article

(This article belongs to the Special Issue Analytical Chemistry in Agriculture Application)

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13 pages, 3233 KiB

Open AccessArticle

Rapid Determination of Nitrate Nitrogen Isotope in Water Using Fourier Transform Infrared Attenuated Total Reflectance Spectroscopy (FTIR-ATR) Coupled with Deconvolution Algorithm

by Ke Wu, Fei Ma, Cuilan Wei, Fangqun Gan and Changwen Du

Molecules 2023, 28(2), 567; https://doi.org/10.3390/molecules28020567 - 05 Jan 2023

Cited by 1 | Viewed by 2252

Abstract

Nitrate is a prominent pollutant in water bodies around the world. The isotopes in nitrate provide an effective approach to trace the sources and transformations of nitrate in water bodies. However, determination of isotopic composition by conventional analytical techniques is time-consuming, laborious, and expensive, and alternative methods are urgently needed. In this study, the rapid determination of ¹⁵NO₃⁻ in water bodies using Fourier transform infrared attenuated total reflectance spectroscopy (FTIR-ATR) coupled with a deconvolution algorithm and a partial least squares regression (PLSR) model was explored. The results indicated that the characteristic peaks of ¹⁴NO₃⁻/¹⁵NO₃⁻ mixtures with varied ¹⁴N/¹⁵N ratios were observed, and the proportion of ¹⁵NO₃⁻ was negatively correlated with the wavenumber of absorption peaks. The PLSR models for nitrate prediction of ¹⁴NO₃⁻/¹⁵NO₃⁻ mixtures with different proportions were established based on deconvoluted spectra, which exhibited good performance with the ratio of prediction to deviation (RPD) values of more than 2.0 and the correlation coefficients (R²) of more than 0.84. Overall, the spectra pretreatment by the deconvolution algorithm dramatically improved the prediction models. Therefore, FTIR-ATR combined with deconvolution and PLSR provided a rapid, simple, and affordable method for determination of ¹⁵NO₃⁻ content in water bodies, which would facilitate and enhance the study of nitrate sources and water environment quality management. Full article

(This article belongs to the Special Issue Analytical Chemistry in Agriculture Application)

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13 pages, 1869 KiB

Open AccessArticle

Revealing the Inner Changes of Component Composition Derived from DOM PARAFAC Based on Two-Dimensional Correlation Spectroscopy

by Hongyang Cui, Lina Xie, Guogang Zhang, Yue Zhao and Zimin Wei

Molecules 2022, 27(21), 7316; https://doi.org/10.3390/molecules27217316 - 27 Oct 2022

Cited by 2 | Viewed by 1331

Abstract

Plenty of humic acid components compositions are contained in dissolved organic matter (DOM) derived from composting. Fluorescence signals were employed to characterize the changes in DOM components in the component process. In the composting process, five individual DOM fluorescence parallel factor analysis (PARAFAC) components were identified. At the end of the composting, PARAFAC component C5, which represented high humification and complex structure compounds, was detected, but the simple structure DOM PARAFAC component C1 was absent. In this study, a technique combining EEM-PARAFAC with two-dimensional correlation spectroscopy (2DCOS) further supplied detailed information about the dynamics of DOM peaks in PARAFAC components. 2DCOS results showed that the variation of the peaks in PARAFAC components was different in the composting process. The formation of a complex DOM fluorescence substance was attributed to the residues from the simple fluorescence peak degradation. The evolution of the DOM fluorescence peaks in each PARAFAC component indicated that simple structure compounds helped the formation of the complex DOM fluorescence substance in the composting process. These results revealed that EEM/PARAFAC combined with 2DCOS could be used to track the evolution of DOM PARAFAC components during the composting process. Full article

(This article belongs to the Special Issue Analytical Chemistry in Agriculture Application)

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12 pages, 2459 KiB

Open AccessArticle

Deep Learning Combined with Hyperspectral Imaging Technology for Variety Discrimination of Fritillaria thunbergii

by Muhammad Hilal Kabir, Mahamed Lamine Guindo, Rongqin Chen, Fei Liu, Xinmeng Luo and Wenwen Kong

Molecules 2022, 27(18), 6042; https://doi.org/10.3390/molecules27186042 - 16 Sep 2022

Cited by 9 | Viewed by 1841

Abstract

Traditional Chinese herbal medicine (TCHM) plays an essential role in the international pharmaceutical industry due to its rich resources and unique curative properties. The flowers, stems, and leaves of Fritillaria contain a wide range of phytochemical compounds, including flavonoids, essential oils, saponins, and alkaloids, which may be useful for medicinal purposes. Fritillaria thunbergii Miq. Bulbs are commonly used in traditional Chinese medicine as expectorants and antitussives. In this paper, a feasibility study is presented that examines the use of hyperspectral imaging integrated with convolutional neural networks (CNN) to distinguish twelve (12) Fritillaria varieties (n = 360). The performance of support vector machines (SVM) and partial least squares-discriminant analysis (PLS-DA) was compared with that of convolutional neural network (CNN). Principal component analysis (PCA) was used to assess the presence of cluster trends in the spectral data. To optimize the performance of the models, cross-validation was used. Among all the discriminant models, CNN was the most accurate with 98.88%, 88.89% in training and test sets, followed by PLS-DA and SVM with 92.59%, 81.94% and 99.65%, 79.17%, respectively. The results obtained in the present study revealed that application of HSI in conjunction with the deep learning technique can be used for classification of Fritillaria thunbergii varieties rapidly and non-destructively. Full article

(This article belongs to the Special Issue Analytical Chemistry in Agriculture Application)

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