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Kadyrov D, Sutin A, Sedunov N, Sedunov A, Salloum H. Vibro-Acoustic Signatures of Various Insects in Stored Products. SENSORS (BASEL, SWITZERLAND) 2024; 24:6736. [PMID: 39460216 PMCID: PMC11511369 DOI: 10.3390/s24206736] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/16/2024] [Revised: 10/10/2024] [Accepted: 10/15/2024] [Indexed: 10/28/2024]
Abstract
Stored products, such as grains and processed foods, are susceptible to infestation by various insects. The early detection of insects in the supply chain is crucial, as introducing invasive pests to new environments may cause disproportionate harm. The STAR Center at Stevens Institute of Technology developed the Acoustic Stored Product Insect Detection System (A-SPIDS) to detect pests in stored products. The system, which comprises a sound-insulated container for product samples with a built-in internal array of piezoelectric sensors and additional electret microphones to record outside noise, was used to conduct numerous measurements of the vibroacoustic signatures of various insects, including the Callosobruchus maculatus, Tribolium confusum, and Tenebrio molitor, in different materials. A normalization method was implemented using the ambient noise of the sensors as a reference, to accommodate for the proprietary, non-calibrated sensors and allowing to set relative detection thresholds for unknown sensitivities. The normalized envelope of the filtered signals was used to characterize and compare the insect signals by estimating the Normalized Signal Pulse Amplitude (NSPA) and the Normalized Spectral Energy Level (NSEL). These parameters characterize the insect detection Signal Noise Ratio (SNR) for pulse-based detection (NSPA) and averaged energy-based detection (NSEL). These metrics provided an initial step towards the design of a reliable detection algorithm. In the conducted tests NSPA was significantly larger than NSEL. The NSPA reached 70 dB for T. molitor in corn flakes. The insect signals were lower in flour where the averaged NSPA and NSEL values were around 40 dB and 11 dB to 16 dB, respectively.
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Affiliation(s)
- Daniel Kadyrov
- Department of Civil, Environmental & Ocean Engineering, Stevens Institute of Technology, Hoboken, NJ 07030, USA; (A.S.); (N.S.)
| | - Alexander Sutin
- Department of Civil, Environmental & Ocean Engineering, Stevens Institute of Technology, Hoboken, NJ 07030, USA; (A.S.); (N.S.)
| | - Nikolay Sedunov
- Department of Civil, Environmental & Ocean Engineering, Stevens Institute of Technology, Hoboken, NJ 07030, USA; (A.S.); (N.S.)
| | - Alexander Sedunov
- Department of Civil, Environmental & Ocean Engineering, Stevens Institute of Technology, Hoboken, NJ 07030, USA; (A.S.); (N.S.)
| | - Hady Salloum
- Department of Civil Engineering, University of Houston, Houston, TX 77204, USA;
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2
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Meléndez F, Sánchez R, Fernández JÁ, Belacortu Y, Bermúdez F, Arroyo P, Martín-Vertedor D, Lozano J. Design of a Multisensory Device for Tomato Volatile Compound Detection Based on a Mixed Metal Oxide-Electrochemical Sensor Array and Optical Reader. MICROMACHINES 2023; 14:1761. [PMID: 37763924 PMCID: PMC10537342 DOI: 10.3390/mi14091761] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Revised: 09/04/2023] [Accepted: 09/08/2023] [Indexed: 09/29/2023]
Abstract
Insufficient control of tomato ripening before harvesting and infection by fungal pests produce large economic losses in world tomato production. Aroma is an indicative parameter of the state of maturity and quality of the tomato. This study aimed to design an electronic system (TOMATO-NOSE) consisting of an array of 12 electrochemical sensors, commercial metal oxide semiconductor sensors, an optical camera for a lateral flow reader, and a smartphone application for device control and data storage. The system was used with tomatoes in different states of ripeness and health, as well as tomatoes infected with Botrytis cinerea. The results obtained through principal component analysis of the olfactory pattern of tomatoes and the reader images show that TOMATO-NOSE is a good tool for the farmer to control tomato ripeness before harvesting and for the early detection of Botrytis cinerea.
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Affiliation(s)
- Félix Meléndez
- Industrial Engineering School, University of Extremadura, 06006 Badajoz, Spain; (F.M.); (J.Á.F.); (P.A.)
- Alianza Nanotecnología Diagnóstica ASJ S.L. (ANT), 28703 San Sebastián de los Reyes, Spain; (Y.B.); (F.B.)
| | - Ramiro Sánchez
- Centro de Investigaciones Científicas y Tecnológicas de Extremadura (CICYTEX), 06006 Badajoz, Spain; (R.S.); (D.M.-V.)
| | - Juan Álvaro Fernández
- Industrial Engineering School, University of Extremadura, 06006 Badajoz, Spain; (F.M.); (J.Á.F.); (P.A.)
| | - Yaiza Belacortu
- Alianza Nanotecnología Diagnóstica ASJ S.L. (ANT), 28703 San Sebastián de los Reyes, Spain; (Y.B.); (F.B.)
| | - Francisco Bermúdez
- Alianza Nanotecnología Diagnóstica ASJ S.L. (ANT), 28703 San Sebastián de los Reyes, Spain; (Y.B.); (F.B.)
| | - Patricia Arroyo
- Industrial Engineering School, University of Extremadura, 06006 Badajoz, Spain; (F.M.); (J.Á.F.); (P.A.)
| | - Daniel Martín-Vertedor
- Centro de Investigaciones Científicas y Tecnológicas de Extremadura (CICYTEX), 06006 Badajoz, Spain; (R.S.); (D.M.-V.)
| | - Jesús Lozano
- Industrial Engineering School, University of Extremadura, 06006 Badajoz, Spain; (F.M.); (J.Á.F.); (P.A.)
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Mojarab-Mahboubkar M, Afrazeh Z, Azizi R, Sendi JJ. Efficiency of Artemisia annua L. essential oil and its chitosan/tripolyphosphate or zeolite encapsulated form in controlling Sitophilus oryzae L. PESTICIDE BIOCHEMISTRY AND PHYSIOLOGY 2023; 195:105544. [PMID: 37666615 DOI: 10.1016/j.pestbp.2023.105544] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Revised: 07/16/2023] [Accepted: 07/18/2023] [Indexed: 09/06/2023]
Abstract
The rice weevil, Sitophilus oryzae L., is one of the most widespread and destructive stored-product pests and resistant to a wide range of chemical insecticides. In this research, Artemisia annua L. essential oil (EO) and its encapsulated form by chitosan/TPP (tripolyphosphate) and zeolite were tested against S. oryzae adults. The order of toxicity was chitosan/TPP (LC30: 30.83, LC50: 39.52, and LC90: 72.50 μL/L air) > pure EO (LC30: 35.75, LC50: 46.25, and LC90: 86.76 μL/L air) > EO loaded in the zeolite (LC30: 43.35, LC50: 55.07, and LC90: 98.80 μL/L air). These encapsulated samples were characterized by dynamic light scattering (DLS) and field emission scanning electron microscope (FE-SEM) which revealed the size and morphology of the droplets measuring 255.2 to 272 nm and 245 to 271.8 nm for EO loaded in chitosan and zeolite respectively. The encapsulation efficiency and loading percentages of A. annua EO in chitosan/TPP and zeolite were 40.16% and 6.01%, and 88% and 85%, respectively. Fumigant persistence was increased from 6 days for pure EO then, 20 and 22 days for encapsulated oil in zeolite and chitosan/TPP, respectively. Our results showed that A. annua EO contains (±)-camphor (29.29%), 1,8-cineole (12.56%), β-caryophyllene (10.29%), α-pinene (8.68%), and artemisia ketone (8.48%) as its major composition. The activity level of glutathione S-transferase increased while general esterase and acetylcholinesterase activity were significantly inhibited in the treated group compared with the control. Antioxidant enzymes, including catalase, peroxidase, and superoxide dismutase were activated in treated adults compared to controls. The current results suggest that encapsulation of A. annua EO by chitosan/TPP and zeolite in addition to safety and environmentally friendly approach could increase its sustainability and therefore enhancing the efficiency in controlling S. oryzae in storage.
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Affiliation(s)
- Malahat Mojarab-Mahboubkar
- Department of Plant Protection, Faculty of Agricultural Sciences, University of Guilan, Rasht 416351314, Iran
| | - Zahra Afrazeh
- Department of Plant Protection, Faculty of Agricultural Sciences, University of Guilan, Rasht 416351314, Iran
| | - Roya Azizi
- Department of Plant Protection, Faculty of Agricultural Sciences, University of Guilan, Rasht 416351314, Iran
| | - Jalal Jalali Sendi
- Department of Plant Protection, Faculty of Agricultural Sciences, University of Guilan, Rasht 416351314, Iran.
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Cheli F, Ottoboni M, Fumagalli F, Mazzoleni S, Ferrari L, Pinotti L. E-Nose Technology for Mycotoxin Detection in Feed: Ready for a Real Context in Field Application or Still an Emerging Technology? Toxins (Basel) 2023; 15:146. [PMID: 36828460 PMCID: PMC9958648 DOI: 10.3390/toxins15020146] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Revised: 01/17/2023] [Accepted: 02/04/2023] [Indexed: 02/16/2023] Open
Abstract
Mycotoxin risk in the feed supply chain poses a concern to animal and human health, economy, and international trade of agri-food commodities. Mycotoxin contamination in feed and food is unavoidable and unpredictable. Therefore, monitoring and control are the critical points. Effective and rapid methods for mycotoxin detection, at the levels set by the regulations, are needed for an efficient mycotoxin management. This review provides an overview of the use of the electronic nose (e-nose) as an effective tool for rapid mycotoxin detection and management of the mycotoxin risk at feed business level. E-nose has a high discrimination accuracy between non-contaminated and single-mycotoxin-contaminated grain. However, the predictive accuracy of e-nose is still limited and unsuitable for in-field application, where mycotoxin co-contamination occurs. Further research needs to be focused on the sensor materials, data analysis, pattern recognition systems, and a better understanding of the needs of the feed industry for a safety and quality management of the feed supply chain. A universal e-nose for mycotoxin detection is not realistic; a unique e-nose must be designed for each specific application. Robust and suitable e-nose method and advancements in signal processing algorithms must be validated for specific needs.
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Affiliation(s)
- Federica Cheli
- Department of Veterinary Medicine and Animal Science, University of Milan, 26900 Lodi, Italy
- CRC I-WE (Coordinating Research Centre: Innovation for Well-Being and Environment), University of Milan, 20100 Milan, Italy
| | - Matteo Ottoboni
- Department of Veterinary Medicine and Animal Science, University of Milan, 26900 Lodi, Italy
| | - Francesca Fumagalli
- Department of Veterinary Medicine and Animal Science, University of Milan, 26900 Lodi, Italy
| | - Sharon Mazzoleni
- Department of Veterinary Medicine and Animal Science, University of Milan, 26900 Lodi, Italy
| | - Luca Ferrari
- Department of Veterinary Medicine and Animal Science, University of Milan, 26900 Lodi, Italy
| | - Luciano Pinotti
- Department of Veterinary Medicine and Animal Science, University of Milan, 26900 Lodi, Italy
- CRC I-WE (Coordinating Research Centre: Innovation for Well-Being and Environment), University of Milan, 20100 Milan, Italy
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5
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Zhu L, Ma Q, Chen J, Zhao G. Current progress on innovative pest detection techniques for stored cereal grains and thereof powders. Food Chem 2022; 396:133706. [PMID: 35868281 DOI: 10.1016/j.foodchem.2022.133706] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2022] [Revised: 07/10/2022] [Accepted: 07/12/2022] [Indexed: 12/12/2022]
Abstract
For stored grains and their powders, pest infestation has always been a knotty problem and thus comprises a serious threat to global food security. Obviously, timely, rapid and accurate pest detection methods are of extreme importance to protect grains from pest mouth. In facing the defects of traditional methods, such as visual inspection, grain flotation and pest trap, diverse innovative approaches progressed fast alternatively, either targeting pest itself or diagnosing pest-induced changes. The former includes machine vision, metabolite analysis, pest-specific protein techniques, molecular techniques, bioacoustics analysis, conductive roller mill, low-field nuclear magnetic resonance spectroscopy and imaging, while the latter consists of thermal imaging, near-infrared spectroscopy and hyperspectral imaging, impact acoustics analysis, soft X-ray imaging and tomography. The principle, operation procedure, pros and cons and application scenarios were discussed for each method. The results herein hope to promote the technical revolution of pest inspection in stored cereal grains and their powders.
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Affiliation(s)
- Lijun Zhu
- College of Food Science, Southwest University, Chongqing 400715, People's Republic of China
| | - Qian Ma
- College of Food Science, Southwest University, Chongqing 400715, People's Republic of China
| | - Jia Chen
- College of Food Science, Southwest University, Chongqing 400715, People's Republic of China
| | - Guohua Zhao
- College of Food Science, Southwest University, Chongqing 400715, People's Republic of China; Chongqing Key Laboratory of Speciality Food Co-Built by Sichuan and Chongqing, Chongqing 400715, People's Republic of China.
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6
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Khorramifar A, Rasekh M, Karami H, Covington JA, Derakhshani SM, Ramos J, Gancarz M. Application of MOS Gas Sensors Coupled with Chemometrics Methods to Predict the Amount of Sugar and Carbohydrates in Potatoes. MOLECULES (BASEL, SWITZERLAND) 2022; 27:molecules27113508. [PMID: 35684450 PMCID: PMC9182414 DOI: 10.3390/molecules27113508] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/06/2022] [Revised: 05/26/2022] [Accepted: 05/27/2022] [Indexed: 12/19/2022]
Abstract
Five potato varieties were studied using an electronic nose with nine MOS sensors. Parameters measured included carbohydrate content, sugar level, and the toughness of the potatoes. Routine tests were carried out while the signals for each potato were measured, simultaneously, using an electronic nose. The signals obtained indicated the concentration of various chemical components. In addition to support vector machines (SVMs that were used for the classification of the samples, chemometric methods, such as the partial least squares regression (PLSR) method, the principal component regression (PCR) method, and the multiple linear regression (MLR) method, were used to create separate regression models for sugar and carbohydrates. The predictive power of the regression models was characterized by a coefficient of determination (R2), a root-mean-square error of prediction (RMSEP), and offsets. PLSR was able to accurately model the relationship between the smells of different types of potatoes, sugar, and carbohydrates. The highest and lowest accuracy of models for predicting sugar and carbohydrates was related to Marfona potatoes and Sprite cultivar potatoes. In general, in all cultivars, the accuracy in predicting the amount of carbohydrates was somewhat better than the accuracy in predicting the amount of sugar. Moreover, the linear function had 100% accuracy for training and validation in the C-SVM method for classification of five potato groups. The electronic nose could be used as a fast and non-destructive method for detecting different potato varieties. Researchers in the food industry will find this method extremely useful in selecting the desired product and samples.
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Affiliation(s)
- Ali Khorramifar
- Department of Biosystems Engineering, University of Mohaghegh Ardabili, Ardabil 56199-11367, Iran;
| | - Mansour Rasekh
- Department of Biosystems Engineering, University of Mohaghegh Ardabili, Ardabil 56199-11367, Iran;
- Correspondence: (M.R.); (H.K.); (M.G.); Tel.: +98-451-551-2081-9 (M.R.); +98-912-083-9910 (H.K.)
| | - Hamed Karami
- Department of Biosystems Engineering, University of Mohaghegh Ardabili, Ardabil 56199-11367, Iran;
- Correspondence: (M.R.); (H.K.); (M.G.); Tel.: +98-451-551-2081-9 (M.R.); +98-912-083-9910 (H.K.)
| | | | - Sayed M. Derakhshani
- Wageningen Food and Biobased Research, Bornse Weilanden 9, P.O. Box 17, 6700AA Wageningen, The Netherlands;
| | - Jose Ramos
- College of Computing and Engineering, Nova Southeastern University (NSU), 3301 College Avenue, Fort Lauderdale, FL 33314-7796, USA;
| | - Marek Gancarz
- Institute of Agrophysics, Polish Academy of Sciences, Doświadczalna 4, 20-290 Lublin, Poland
- Faculty of Production and Power Engineering, University of Agriculture in Kraków, Balicka 116B, 30-149 Krakow, Poland
- Correspondence: (M.R.); (H.K.); (M.G.); Tel.: +98-451-551-2081-9 (M.R.); +98-912-083-9910 (H.K.)
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Sha J, Xu C, Xu K. Progress of Research on the Application of Nanoelectronic Smelling in the Field of Food. MICROMACHINES 2022; 13:mi13050789. [PMID: 35630255 PMCID: PMC9145094 DOI: 10.3390/mi13050789] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/28/2022] [Revised: 05/12/2022] [Accepted: 05/16/2022] [Indexed: 11/16/2022]
Abstract
In the past 20 years, the development of an artificial olfactory system has made great progress and improvements. In recent years, as a new type of sensor, nanoelectronic smelling has been widely used in the food and drug industry because of its advantages of accurate sensitivity and good selectivity. This paper reviews the latest applications and progress of nanoelectronic smelling in animal-, plant-, and microbial-based foods. This includes an analysis of the status of nanoelectronic smelling in animal-based foods, an analysis of its harmful composition in plant-based foods, and an analysis of the microorganism quantity in microbial-based foods. We also conduct a flavor component analysis and an assessment of the advantages of nanoelectronic smelling. On this basis, the principles and structures of nanoelectronic smelling are also analyzed. Finally, the limitations and challenges of nanoelectronic smelling are summarized, and the future development of nanoelectronic smelling is proposed.
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Affiliation(s)
| | - Chong Xu
- Correspondence: ; Tel.: +86-024-2469-2899
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Meléndez F, Arroyo P, Gómez-Suárez J, Palomeque-Mangut S, Suárez JI, Lozano J. Portable Electronic Nose Based on Digital and Analog Chemical Sensors for 2,4,6-Trichloroanisole Discrimination. SENSORS (BASEL, SWITZERLAND) 2022; 22:3453. [PMID: 35591143 PMCID: PMC9102965 DOI: 10.3390/s22093453] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Revised: 04/25/2022] [Accepted: 04/28/2022] [Indexed: 06/15/2023]
Abstract
2,4,6-trichloroanisole (TCA) is mainly responsible for cork taint in wine, which causes significant economic losses; therefore, the wine and cork industries demand an immediate, economic, noninvasive and on-the-spot solution. In this work, we present a novel prototype of an electronic nose (e-nose) using an array of digital and analog metal-oxide gas sensors with a total of 31 signals, capable of detecting TCA, and classifying cork samples with low TCA concentrations (≤15.1 ng/L). The results show that the device responds to low concentrations of TCA in laboratory conditions. It also differentiates among the inner and outer layers of cork bark (81.5% success) and distinguishes among six different samples of granulated cork (83.3% success). Finally, the device can predict the concentration of a new sample within a ±10% error margin.
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Affiliation(s)
| | | | | | | | | | - Jesús Lozano
- Industrial Engineering School, University of Extremadura, 06006 Badajoz, Spain; (F.M.); (P.A.); (J.G.-S.); (S.P.-M.); (J.I.S.)
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Srivastava S, Mishra HN. Development of microencapsulated vegetable oil powder based cookies and study of its physicochemical properties and storage stability. Lebensm Wiss Technol 2021. [DOI: 10.1016/j.lwt.2021.112364] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
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10
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Liu K, Zhang C, Xu J, Liu Q. Research advance in gas detection of volatile organic compounds released in rice quality deterioration process. Compr Rev Food Sci Food Saf 2021; 20:5802-5828. [PMID: 34668316 DOI: 10.1111/1541-4337.12846] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2021] [Revised: 08/04/2021] [Accepted: 08/24/2021] [Indexed: 11/30/2022]
Abstract
Rice quality deterioration will cause grievous waste of stored grain and various food safety problems. Gas detection of volatile organic compounds (VOCs) produced by deterioration is a nondestructive detection method to judge rice quality and alleviate rice spoilage. This review discussed the research advance of VOCs detection in terms of nondestructive detection methods of rice quality deterioration, applications of VOCs in grain detection, inspection of characteristic gas produced during rice spoilage, rice deterioration prevention and control, and detection of VOCs released by rice mildew and insect attack. According to the main causes of rice quality deterioration and major sources of VOCs with off-odor generated during rice storage, deterioration can be divided into mold and insect infection. The results of literature manifested that researches mainly focused on the infection of Aspergillus in the mildew process and the attack of certain pests in recent years, thus the research scope was limited. In this paper, the gas detection methods combined with the chemometrics to qualitatively analyze the VOCs, as well as the correlation with the number of colonies and insects were further studied based on the common dominant strains during rice mildew, that is, Aspergillus and Penicillium fungi, and the common pests during storage, that is, Sitophilus oryzae and Rhyzopertha dominica. Furthermore, this paper pointed out that the quantitative determination of characteristic VOCs, the numeration relationship between VOCs and the degree of mildew and insect infestation, the further expansion of detection range, and the application of degraded rice should be the spotlight of future research.
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Affiliation(s)
- Kewei Liu
- College of Mechanical Engineering, Yangzhou University, Yangzhou, People's Republic of China
| | - Chao Zhang
- College of Mechanical Engineering, Yangzhou University, Yangzhou, People's Republic of China
| | - Jinyong Xu
- College of Mechanical Engineering, Yangzhou University, Yangzhou, People's Republic of China
| | - Qiaoquan Liu
- Key Laboratories of Crop Genetics and Physiology of Jiangsu Province, Co-Innovation Center for Modern Production Technology of Grain Crops of Jiangsu, Yangzhou University, Yangzhou, People's Republic of China
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11
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Fu L, Zhu J, Karimi-Maleh H. An Analytical Method Based on Electrochemical Sensor for the Assessment of Insect Infestation in Flour. BIOSENSORS 2021; 11:325. [PMID: 34562915 PMCID: PMC8466299 DOI: 10.3390/bios11090325] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/03/2021] [Revised: 08/27/2021] [Accepted: 09/08/2021] [Indexed: 11/20/2022]
Abstract
Uric acid is an important indicator of the insect infestation assessment in flour. In this work, we propose a method for uric acid detection based on voltammetry. This technique is particularly considered for the physicochemical properties of flour and contains a simple pretreatment process to rapidly achieve extraction and adsorption of uric acid in flour. To achieve specific recognition of uric acid, graphene and poly(3,4-ethylenedioxythiophene) (PEDOT) were used for the adsorption and concentration of uric acid in flour. The adsorbed mixture was immobilized on the surface of a screen-printed electrode for highly sensitive detection of the uric acid. The results showed that electrocatalytic oxidation of uric acid could be achieved after adsorption by graphene and PEDOT. This electrocatalytic reaction allows its oxidation peak to be distinguished from those of other substances that commonly possess electrochemical activity. This voltammetry-based detection method is a portable and disposable analytical method. Because it is simple to operate, requires no professional training, and is inexpensive, it is a field analysis method that can be promoted.
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Affiliation(s)
- Li Fu
- Key Laboratory of Novel Materials for Sensor of Zhejiang Province, College of Materials and Environmental Engineering, Hangzhou Dianzi University, Hangzhou 310018, China
| | - Jiangwei Zhu
- Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China;
| | - Hassan Karimi-Maleh
- School of Resources and Environment, University of Electronic Science and Technology of China, Xiyuan Ave, Chengdu 611731, China;
- Department of Chemical Engineering, Quchan University of Technology, Quchan 9477177870, Iran
- Department of Chemical Sciences, University of Johannesburg, Doornfontein Campus, P.O. Box 17011, Johannesburg 2028, South Africa
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12
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Mavani NR, Ali JM, Othman S, Hussain MA, Hashim H, Rahman NA. Application of Artificial Intelligence in Food Industry—a Guideline. FOOD ENGINEERING REVIEWS 2021. [PMCID: PMC8350558 DOI: 10.1007/s12393-021-09290-z] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Artificial intelligence (AI) has embodied the recent technology in the food industry over the past few decades due to the rising of food demands in line with the increasing of the world population. The capability of the said intelligent systems in various tasks such as food quality determination, control tools, classification of food, and prediction purposes has intensified their demand in the food industry. Therefore, this paper reviews those diverse applications in comparing their advantages, limitations, and formulations as a guideline for selecting the most appropriate methods in enhancing future AI- and food industry–related developments. Furthermore, the integration of this system with other devices such as electronic nose, electronic tongue, computer vision system, and near infrared spectroscopy (NIR) is also emphasized, all of which will benefit both the industry players and consumers.
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Affiliation(s)
- Nidhi Rajesh Mavani
- Department of Chemical and Process Engineering, Faculty of Engineering & Built Environment, Universiti Kebangsaan Malaysia, UKM, Selangor 43600 Bangi, Malaysia
| | - Jarinah Mohd Ali
- Department of Chemical and Process Engineering, Faculty of Engineering & Built Environment, Universiti Kebangsaan Malaysia, UKM, Selangor 43600 Bangi, Malaysia
| | - Suhaili Othman
- Department of Chemical and Process Engineering, Faculty of Engineering & Built Environment, Universiti Kebangsaan Malaysia, UKM, Selangor 43600 Bangi, Malaysia
- Department of Biological and Agricultural Engineering, Faculty of Engineering, Universiti Putra Malaysia, UPM Serdang, 43400 Selangor, Malaysia
| | - M. A. Hussain
- Department of Chemical Engineering, Faculty of Engineering, University of Malaya, 50603 Kuala Lumpur, Malaysia
| | - Haslaniza Hashim
- Department of Food Sciences, Faculty of Science & Technology, Universiti Kebangsaan Malaysia, UKM, Selangor 43600 Bangi, Malaysia
| | - Norliza Abd Rahman
- Department of Chemical and Process Engineering, Faculty of Engineering & Built Environment, Universiti Kebangsaan Malaysia, UKM, Selangor 43600 Bangi, Malaysia
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13
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Anwar T, Anwar H. Beef quality assessment using AutoML. 2021 MOHAMMAD ALI JINNAH UNIVERSITY INTERNATIONAL CONFERENCE ON COMPUTING (MAJICC) 2021. [DOI: 10.1109/majicc53071.2021.9526256] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/01/2023]
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14
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Srivastava S, Mishra G, Mishra HN. Vulnerability of different life stages of
Sitophilus oryzae
insects in stored rice grain to ozone treatment and its effect on physico‐chemical properties in rice grain. FOOD FRONTIERS 2021. [DOI: 10.1002/fft2.89] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
Affiliation(s)
- Shubhangi Srivastava
- Agricultural and Food Engineering Department Indian Institute of Technology Kharagpur West Bengal India
| | - Gayatri Mishra
- Agricultural and Food Engineering Department Indian Institute of Technology Kharagpur West Bengal India
| | - Hari Niwas Mishra
- Agricultural and Food Engineering Department Indian Institute of Technology Kharagpur West Bengal India
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John AT, Murugappan K, Nisbet DR, Tricoli A. An Outlook of Recent Advances in Chemiresistive Sensor-Based Electronic Nose Systems for Food Quality and Environmental Monitoring. SENSORS (BASEL, SWITZERLAND) 2021; 21:2271. [PMID: 33804960 PMCID: PMC8036444 DOI: 10.3390/s21072271] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/22/2021] [Revised: 03/16/2021] [Accepted: 03/17/2021] [Indexed: 01/05/2023]
Abstract
An electronic nose (Enose) relies on the use of an array of partially selective chemical gas sensors for identification of various chemical compounds, including volatile organic compounds in gas mixtures. They have been proposed as a portable low-cost technology to analyse complex odours in the food industry and for environmental monitoring. Recent advances in nanofabrication, sensor and microcircuitry design, neural networks, and system integration have considerably improved the efficacy of Enose devices. Here, we highlight different types of semiconducting metal oxides as well as their sensing mechanism and integration into Enose systems, including different pattern recognition techniques employed for data analysis. We offer a critical perspective of state-of-the-art commercial and custom-made Enoses, identifying current challenges for the broader uptake and use of Enose systems in a variety of applications.
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Affiliation(s)
- Alishba T. John
- Nanotechnology Research Laboratory, Research School of Chemistry, College of Science, The Australian National University, Canberra 2601, Australia;
| | - Krishnan Murugappan
- Nanotechnology Research Laboratory, Research School of Chemistry, College of Science, The Australian National University, Canberra 2601, Australia;
| | - David R. Nisbet
- Laboratory of Advanced Biomaterials, Research School of Chemistry and the John Curtin School of Medical Research, The Australian National University, Canberra 2601, Australia;
| | - Antonio Tricoli
- Nanotechnology Research Laboratory, Research School of Chemistry, College of Science, The Australian National University, Canberra 2601, Australia;
- Nanotechnology Research Laboratory, Faculty of Engineering, The University of Sydney, Camperdown 2006, Australia
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Influence of Electron Beam Irradiation on the Moisture and Properties of Freshly Harvested and Sun-Dried Rice. Foods 2020; 9:foods9091139. [PMID: 32825033 PMCID: PMC7555959 DOI: 10.3390/foods9091139] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2020] [Revised: 08/11/2020] [Accepted: 08/17/2020] [Indexed: 12/05/2022] Open
Abstract
Moisture content is an important factor that affects rice storage. Rice with high moisture (HM) content has superior taste but is difficult to store. In this study, low-dose electron beam irradiation (EBI) was used to study water distribution in newly harvested HM (15.03%) rice and dried rice (11.97%) via low-field nuclear magnetic resonance (LF-NMR). The gelatinization, texture and rheological properties of rice and the thermal and digestion properties of rice starch were determined. Results showed that low-dose EBI could change water distribution in rice mainly by affecting free water under low-moisture (LM) conditions and free water and bound water under HM conditions. HM rice showed smooth changes in gelatinization and rheological properties and softened textural properties. The swelling power and solubility index indicated that irradiation promoted the depolymerization of starch chains. Overall, low-dose EBI had little effect on the properties of rice. HM rice showed superior quality and taste, whereas LM rice exhibited superior nutritional quality. This work attempted to optimize the outcome of the EBI treatment of rice for storage purposes by analyzing its effects. It demonstrated that low-dose EBI was more effective and environmentally friendly than other techniques.
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Srivastava S, Mishra G, Mishra HN. Application of an expert system of X- ray micro computed tomography imaging for identification of Sitophilus oryzae infestation in stored rice grains. PEST MANAGEMENT SCIENCE 2020; 76:952-960. [PMID: 31468700 DOI: 10.1002/ps.5603] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/07/2019] [Revised: 08/25/2019] [Accepted: 08/25/2019] [Indexed: 06/10/2023]
Abstract
BACKGROUND The plausibility of image texture analysis to assess X-ray images of S. oryzae-infested rice after variable storage days (fresh, 45, 90, 135, 180 and 225 days) was investigated using an X-ray micro computed tomography instrument. Subsequently, image acquisition, pre-processing, and the extraction of the image textural features was done using volume graphics VGL 2.2 software. Morphological features (radius, diameter, volume, compactness, sphericity, defect volume, and voids) were extracted from the x, y, and z views of the rice grain and used as inputs for principal component analysis (PCA). RESULTS Clear grouping was observed between the fresh, 45 and 225-day-old S. oryzae-infested rice grains with a classification accuracy of 88.34%. The voids (884 248.53 μm3 ) and defect volume distribution (137 428.04 μm3 ) were found to be the maximum in 225-day-old samples. The similarity or the distance indices values between fresh and 255-day-old S. oryzae-infested rice samples were found to be 35 038.08, which resulted in clear discrimination between different storage days in S. oryzae-infested rice grains. CONCLUSION This work contributes to the potential use of image texture analysis to aid in distinguishing S. oryzae-infested rice grains from fresh rice grains. © 2019 Society of Chemical Industry.
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Affiliation(s)
- Shubhangi Srivastava
- Agricultural and Food Engineering Department, Indian Institute of Technology, Kharagpur, India
| | - Gayatri Mishra
- Agricultural and Food Engineering Department, Indian Institute of Technology, Kharagpur, India
| | - Hari N Mishra
- Agricultural and Food Engineering Department, Indian Institute of Technology, Kharagpur, India
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Li H, Luo D, Sun Y, GholamHosseini H. Classification and Identification of Industrial Gases Based on Electronic Nose Technology. SENSORS 2019; 19:s19225033. [PMID: 31752238 PMCID: PMC6891334 DOI: 10.3390/s19225033] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/11/2019] [Revised: 11/12/2019] [Accepted: 11/15/2019] [Indexed: 12/14/2022]
Abstract
Rapid detection and identification of industrial gases is a challenging problem. They have a complex composition and different specifications. This paper presents a method based on the kernel discriminant analysis (KDA) algorithm to identify industrial gases. The smell prints of four typical industrial gases were collected by an electronic nose. The extracted features of the collected gases were employed for gas identification using different classification algorithms, including principal component analysis (PCA), linear discriminant analysis (LDA), PCA + LDA, and KDA. In order to obtain better classification results, we reduced the dimensions of the original high-dimensional data, and chose a good classifier. The KDA algorithm provided a high classification accuracy of 100% by selecting the offset of the kernel function c = 10 and the degree of freedom d = 5. It was found that this accuracy was 4.17% higher than the one obtained using PCA. In the case of standard deviation, the KDA algorithm has the highest recognition rate and the least time consumption.
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Affiliation(s)
- Hui Li
- School of Information and Engineering, Guangdong University of Technology, Guangzhou 510006, China; (H.L.); (D.L.)
| | - Dehan Luo
- School of Information and Engineering, Guangdong University of Technology, Guangzhou 510006, China; (H.L.); (D.L.)
| | - Yunlong Sun
- School of Electric and Automatic Engineering, Changshu Institute of Technology, Changshu 215500, China
- Correspondence:
| | - Hamid GholamHosseini
- School of Engineering, Computer and Mathematical Sciences, Auckland University of Technology, Private Bag 92006, Auckland 1142, New Zealand;
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Shao X, Xu W, Xu S, Xing C, Ding C, Liu Q. Time-Domain NMR Applied to Sitophilus zeamais Motschulsky/Wheat Detection. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2019; 67:12565-12575. [PMID: 31618029 DOI: 10.1021/acs.jafc.9b04007] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Time-domain nuclear magnetic resonance (NMR) is used for the characterization of wheat infested with Sitophilus zeamais. NMR parameters (T21, T22, P21, P22, and A21/22) were achieved by biexponential analysis combined with a discrete method. Sound wheat, S. zeamais, and S. zeamais/wheat binary mixture are all explored by this method to find the changes in the process of the number increase and growth stage. Based on different sets of NMR parameters, the classification and quantification of the stage and number are made by linear discriminant analysis and partial least squares regression with very high accuracy. The weight and moisture content information lack will make the misclassification rate increase but not by more than 7%. This NMR-based hidden-insect detection method, with fast and nondestructive advantages, was confirmed by X-ray and had a high potential to be equipped in the online analysis system.
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Affiliation(s)
- Xiaolong Shao
- College of Food Science and Engineering, Collaborative Innovation Center for Modern Grain Circulation and Safety, Key Laboratory of Grains and Oils Quality Control and Processing , Nanjing University of Finance and Economics , Nanjing 210023 , China
| | - Wen Xu
- College of Food Science and Engineering, Collaborative Innovation Center for Modern Grain Circulation and Safety, Key Laboratory of Grains and Oils Quality Control and Processing , Nanjing University of Finance and Economics , Nanjing 210023 , China
| | - Shuihong Xu
- College of Food Science and Engineering, Collaborative Innovation Center for Modern Grain Circulation and Safety, Key Laboratory of Grains and Oils Quality Control and Processing , Nanjing University of Finance and Economics , Nanjing 210023 , China
| | - Changrui Xing
- College of Food Science and Engineering, Collaborative Innovation Center for Modern Grain Circulation and Safety, Key Laboratory of Grains and Oils Quality Control and Processing , Nanjing University of Finance and Economics , Nanjing 210023 , China
| | - Chao Ding
- College of Food Science and Engineering, Collaborative Innovation Center for Modern Grain Circulation and Safety, Key Laboratory of Grains and Oils Quality Control and Processing , Nanjing University of Finance and Economics , Nanjing 210023 , China
| | - Qin Liu
- College of Food Science and Engineering, Collaborative Innovation Center for Modern Grain Circulation and Safety, Key Laboratory of Grains and Oils Quality Control and Processing , Nanjing University of Finance and Economics , Nanjing 210023 , China
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Multilayer perceptron neural networking for prediction of quality attributes of spray-dried vegetable oil powder. Soft comput 2019. [DOI: 10.1007/s00500-019-04494-2] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
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