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França-Silva F, Rego CHQ, Gomes-Junior FG, de Moraes MHD, de Medeiros AD, da Silva CB. Detection of Drechslera avenae (Eidam) Sharif [ Helminthosporium avenae (Eidam)] in Black Oat Seeds ( Avena strigosa Schreb) Using Multispectral Imaging. SENSORS 2020; 20:s20123343. [PMID: 32545563 PMCID: PMC7348857 DOI: 10.3390/s20123343] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/08/2020] [Revised: 06/04/2020] [Accepted: 06/08/2020] [Indexed: 11/16/2022]
Abstract
Conventional methods for detecting seed-borne fungi are laborious and time-consuming, requiring specialized analysts for characterization of pathogenic fungi on seed. Multispectral imaging (MSI) combined with machine vision was used as an alternative method to detect Drechslera avenae (Eidam) Sharif [Helminthosporium avenae (Eidam)] in black oat seeds (Avena strigosa Schreb). The seeds were inoculated with Drechslera avenae (D. avenae) and then incubated for 24, 72 and 120 h. Multispectral images of non-infested and infested seeds were acquired at 19 wavelengths within the spectral range of 365 to 970 nm. A classification model based on linear discriminant analysis (LDA) was created using reflectance, color, and texture features of the seed images. The model developed showed high performance of MSI in detecting D. avenae in black oat seeds, particularly using color and texture features from seeds incubated for 120 h, with an accuracy of 0.86 in independent validation. The high precision of the classifier showed that the method using images captured in the Ultraviolet A region (365 nm) could be easily used to classify black oat seeds according to their health status, and results can be achieved more rapidly and effectively compared to conventional methods.
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Affiliation(s)
- Fabiano França-Silva
- Department of Crop Science, University of São Paulo-Luiz de Queiroz College of Agriculture, 11 Pádua Dias Avenue, 13418-900 Piracicaba, Brazil; (C.H.Q.R.); (F.G.G.-J.)
- Correspondence:
| | - Carlos Henrique Queiroz Rego
- Department of Crop Science, University of São Paulo-Luiz de Queiroz College of Agriculture, 11 Pádua Dias Avenue, 13418-900 Piracicaba, Brazil; (C.H.Q.R.); (F.G.G.-J.)
| | - Francisco Guilhien Gomes-Junior
- Department of Crop Science, University of São Paulo-Luiz de Queiroz College of Agriculture, 11 Pádua Dias Avenue, 13418-900 Piracicaba, Brazil; (C.H.Q.R.); (F.G.G.-J.)
| | - Maria Heloisa Duarte de Moraes
- Department of Plant Pathology and Nematology, University of São Paulo-Luiz de Queiroz College of Agriculture, 11 Pádua Dias Avenue, Piracicaba 13418-900, Brazil;
| | - André Dantas de Medeiros
- Department of Agronomy, Universidade Federal de Viçosa, Peter Henry Rolfs Avenue, Viçosa MG 36570-900, Brazil;
| | - Clíssia Barboza da Silva
- Laboratory of Radiobiology and Environment, University of São Paulo-Center for Nuclear Energy in Agriculture, 303 Centenário Avenue, Piracicaba SP 13416-000, Brazil;
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ElMasry G, Mandour N, Al-Rejaie S, Belin E, Rousseau D. Recent Applications of Multispectral Imaging in Seed Phenotyping and Quality Monitoring-An Overview. SENSORS 2019; 19:s19051090. [PMID: 30836613 PMCID: PMC6427362 DOI: 10.3390/s19051090] [Citation(s) in RCA: 55] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/21/2019] [Revised: 02/17/2019] [Accepted: 02/22/2019] [Indexed: 12/02/2022]
Abstract
As a synergistic integration between spectroscopy and imaging technologies, spectral imaging modalities have been emerged to tackle quality evaluation dilemmas by proposing different designs with effective and practical applications in food and agriculture. With the advantage of acquiring spatio-spectral data across a wide range of the electromagnetic spectrum, the state-of-the-art multispectral imaging in tandem with different multivariate chemometric analysis scenarios has been successfully implemented not only for food quality and safety control purposes, but also in dealing with critical research challenges in seed science and technology. This paper will shed some light on the fundamental configuration of the systems and give a birds-eye view of all recent approaches in the acquisition, processing and reproduction of multispectral images for various applications in seed quality assessment and seed phenotyping issues. This review article continues from where earlier review papers stopped but it only focused on fully-operated multispectral imaging systems for quality assessment of different sorts of seeds. Thence, the review comprehensively highlights research attempts devoted to real implementations of only fully-operated multispectral imaging systems and does not consider those ones that just utilized some key wavelengths extracted from hyperspectral data analyses without building independent multispectral imaging systems. This makes this article the first attempt in briefing all published papers in multispectral imaging applications in seed phenotyping and quality monitoring by providing some examples and research results in characterizing physicochemical quality traits, predicting physiological parameters, detection of defect, pest infestation and seed health.
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Affiliation(s)
- Gamal ElMasry
- Department of Pharmacology & Toxicology, College of Pharmacy, King Saud University, Riyadh 11564, Saudi Arabia.
- Faculty of Agriculture, Suez Canal University, Ring Road Km 4.5, Ismailia P.O. Box 41522, Egypt.
- INRA, UMR1345 Institut de Recherche en Horticulture et Semences, 42 rue Georges Morel CS 60057, F-49071 Beaucouzé CEDEX, Angers, France.
| | - Nasser Mandour
- Faculty of Agriculture, Suez Canal University, Ring Road Km 4.5, Ismailia P.O. Box 41522, Egypt.
| | - Salim Al-Rejaie
- Department of Pharmacology & Toxicology, College of Pharmacy, King Saud University, Riyadh 11564, Saudi Arabia.
| | - Etienne Belin
- INRA, UMR1345 Institut de Recherche en Horticulture et Semences, 42 rue Georges Morel CS 60057, F-49071 Beaucouzé CEDEX, Angers, France.
- Laboratoire Angevin de Recherche en Ingénierie des Systèmes (LARIS), Université d'Angers, 62 avenue Notre Dame du Lac, 49000 Angers, France.
| | - David Rousseau
- INRA, UMR1345 Institut de Recherche en Horticulture et Semences, 42 rue Georges Morel CS 60057, F-49071 Beaucouzé CEDEX, Angers, France.
- Laboratoire Angevin de Recherche en Ingénierie des Systèmes (LARIS), Université d'Angers, 62 avenue Notre Dame du Lac, 49000 Angers, France.
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Vrešak M, Halkjaer Olesen M, Gislum R, Bavec F, Ravn Jørgensen J. The Use of Image-Spectroscopy Technology as a Diagnostic Method for Seed Health Testing and Variety Identification. PLoS One 2016; 11:e0152011. [PMID: 27010656 PMCID: PMC4807013 DOI: 10.1371/journal.pone.0152011] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2015] [Accepted: 03/08/2016] [Indexed: 11/18/2022] Open
Abstract
Application of rapid and time-efficient health diagnostic and identification technology in the seed industry chain could accelerate required analysis, characteristic description and also ultimately availability of new desired varieties. The aim of the study was to evaluate the potential of multispectral imaging and single kernel near-infrared spectroscopy (SKNIR) for determination of seed health and variety separation of winter wheat (Triticum aestivum L.) and winter triticale (Triticosecale Wittm. & Camus). The analysis, carried out in autumn 2013 at AU-Flakkebjerg, Denmark, included nine winter triticale varieties and 27 wheat varieties provided by the Faculty of Agriculture and Life Sciences Maribor, Slovenia. Fusarium sp. and black point disease-infected parts of the seed surface could successfully be distinguished from uninfected parts with use of a multispectral imaging device (405-970 nm wavelengths). SKNIR was applied in this research to differentiate all 36 involved varieties based on spectral differences due to variation in the chemical composition. The study produced an interesting result of successful distinguishing between the infected and uninfected parts of the seed surface. Furthermore, the study was able to distinguish between varieties. Together these components could be used in further studies for the development of a sorting model by combining data from multispectral imaging and SKNIR for identifying disease(s) and varieties.
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Affiliation(s)
- Martina Vrešak
- Faculty of Agriculture and Life Sciences, Institute for Organic Farming, University of Maribor, Pivola, Hoce, Slovenia
- * E-mail:
| | - Merete Halkjaer Olesen
- Faculty of Science and Technology, Department of Agroecology, Aarhus University, Forsøgsvej, Slagelse, Denmark
| | - René Gislum
- Faculty of Science and Technology, Department of Agroecology, Aarhus University, Forsøgsvej, Slagelse, Denmark
| | - Franc Bavec
- Faculty of Agriculture and Life Sciences, Institute for Organic Farming, University of Maribor, Pivola, Hoce, Slovenia
| | - Johannes Ravn Jørgensen
- Faculty of Science and Technology, Department of Agroecology, Aarhus University, Forsøgsvej, Slagelse, Denmark
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Jaillais B, Roumet P, Pinson-Gadais L, Bertrand D. Detection of Fusarium head blight contamination in wheat kernels by multivariate imaging. Food Control 2015. [DOI: 10.1016/j.foodcont.2015.01.048] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
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Esteve Agelet L, Hurburgh CR. Limitations and current applications of Near Infrared Spectroscopy for single seed analysis. Talanta 2014; 121:288-99. [PMID: 24607140 DOI: 10.1016/j.talanta.2013.12.038] [Citation(s) in RCA: 66] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2013] [Revised: 12/15/2013] [Accepted: 12/16/2013] [Indexed: 11/28/2022]
Abstract
Near Infrared Spectroscopy (NIRS) analysis at the single seed level is a useful tool for breeders, farmers, feeding facilities, and food companies according to current researches. As a non-destructive technique, NIRS allows for the selection and classification of seeds according to specific traits and attributes without alteration of their properties. Critical aspects in using NIRS for single seed analysis such as reference method, sample morphology, and spectrometer suitability are discussed in this review. A summary of current applications of NIRS technologies at single seed level is also presented.
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Affiliation(s)
- Lidia Esteve Agelet
- Department of Agriculture and Biosystems Engineering, Iowa State University, USA.
| | - Charles R Hurburgh
- Department of Agriculture and Biosystems Engineering, Iowa State University, USA
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Jaillais B, Bertrand D, Abecassis J. Identification of the histological origin of durum wheat milling products by multispectral imaging and chemometrics. J Cereal Sci 2012. [DOI: 10.1016/j.jcs.2011.11.011] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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