Authors:
J.J. Lin School of Physics and Electronics, Nanning Normal University, Nanning 530001, China

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Q.H. Meng School of Physics and Electronics, Nanning Normal University, Nanning 530001, China
Key Laboratory of New Electric Functional Materials of Guangxi Colleges and Universities, Nanning Normal University, Nanning 530001, China

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https://orcid.org/0009-0002-5294-2924
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Z.F. Wu School of Physics and Electronics, Nanning Normal University, Nanning 530001, China
Key Laboratory of New Electric Functional Materials of Guangxi Colleges and Universities, Nanning Normal University, Nanning 530001, China

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S.Y. Pei School of Physics and Electronics, Nanning Normal University, Nanning 530001, China
Key Laboratory of New Electric Functional Materials of Guangxi Colleges and Universities, Nanning Normal University, Nanning 530001, China

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P. Tian School of Physics and Electronics, Nanning Normal University, Nanning 530001, China

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X. Huang School of Physics and Electronics, Nanning Normal University, Nanning 530001, China

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Z.Q. Qiu School of Physics and Electronics, Nanning Normal University, Nanning 530001, China

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H.J. Chang School of Physics and Electronics, Nanning Normal University, Nanning 530001, China

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C.Y. Ni School of Physics and Electronics, Nanning Normal University, Nanning 530001, China

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Y.Q. Huang Key Laboratory of Environmental Evolution and Resource Utilization of the Beibu Gulf, Ministry of Education & Guangxi Key Laboratory of Earth Surface Processes and Intelligent Simulation, Nanning Normal University, Nanning 530001, China

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Y. Li Guangxi Technical Instruction Office for Fruit, Nanning 530022, China

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Abstract

This paper explores the prediction of the soluble solid content (SSC) in the visible and near-infrared (400–1,000 nm) regions of Baise mango. Hyperspectral images of Baise mangoes with wavelengths of 400–1,000 nm were obtained using a hyperspectral imaging system. Multiple scatter correction (MSC) was chosen to remove the effect of noise on the accuracy of the partial least squares (PLS) regression model. On this basis, the characteristic wavelengths of mango SSC were selected using the competitive adaptive reweighted sampling (CARS), genetic algorithm (GA), uninformative variable elimination (UVE), and combined CARS + GA-SPA, CARS + UVE-SPA, and GA + UVE-SPA characteristic wavelength methods. The results show that the combined MSC-CARS + GA-SPA-PLS algorithm can reduce redundant information and improve the computational efficiency, so it is an effective method to predict the SSC of mangoes.

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Senior editors

Editor(s)-in-Chief: András Salgó, Budapest University of Technology and Economics, Budapest, Hungary

Co-ordinating Editor(s) Marianna Tóth-Markus, Budapest, Hungary

Co-editor(s): A. Halász, Budapest, Hungary

       Editorial Board

  • László Abrankó, Hungarian University of Agriculture and Life Sciences, Budapest, Hungary
  • Tamás Antal, University of Nyíregyháza, Nyíregyháza, Hungary
  • Diána Bánáti, University of Szeged, Szeged, Hungary
  • József Baranyi, Institute of Food Research, Norwich, UK
  • Ildikó Bata-Vidács, Eszterházy Károly Catholic University, Eger, Hungary
  • Ferenc Békés, FBFD PTY LTD, Sydney, NSW Australia
  • György Biró, Budapest, Hungary
  • Anna Blázovics, Semmelweis University, Budapest, Hungary
  • Francesco Capozzi, University of Bologna, Bologna, Italy
  • Marina Carcea, Research Centre for Food and Nutrition, Council for Agricultural Research and Economics Rome, Italy
  • Zsuzsanna Cserhalmi, Budapest, Hungary
  • Marco Dalla Rosa, University of Bologna, Bologna, Italy
  • István Dalmadi, Hungarian University of Agriculture and Life Sciences, Budapest, Hungary
  • Katarina Demnerova, University of Chemistry and Technology, Prague, Czech Republic
  • Mária Dobozi King, Texas A&M University, Texas, USA
  • Muying Du, Southwest University in Chongqing, Chongqing, China
  • Sedef Nehir El, Ege University, Izmir, Turkey
  • Søren Balling Engelsen, University of Copenhagen, Copenhagen, Denmark
  • Éva Gelencsér, Budapest, Hungary
  • Vicente Manuel Gómez-López, Universidad Católica San Antonio de Murcia, Murcia, Spain
  • Jovica Hardi, University of Osijek, Osijek, Croatia
  • Hongju He, Henan Institute of Science and Technology, Xinxiang, China
  • Károly Héberger, Research Centre for Natural Sciences, ELKH, Budapest, Hungary
  • Nebojsa Ilić, University of Novi Sad, Novi Sad, Serbia
  • Dietrich Knorr, Technische Universität Berlin, Berlin, Germany
  • Hamit Köksel, Hacettepe University, Ankara, Turkey
  • Katia Liburdi, Tuscia University, Viterbo, Italy
  • Meinolf Lindhauer, Max Rubner Institute, Detmold, Germany
  • Min-Tze Liong, Universiti Sains Malaysia, Penang, Malaysia
  • Marena Manley, Stellenbosch University, Stellenbosch, South Africa
  • Miklós Mézes, Hungarian University of Agriculture and Life Sciences, Gödöllő, Hungary
  • Áron Németh, Budapest University of Technology and Economics, Budapest, Hungary
  • Perry Ng, Michigan State University,  Michigan, USA
  • Quang Duc Nguyen, Hungarian University of Agriculture and Life Sciences, Budapest, Hungary
  • Laura Nyström, ETH Zürich, Switzerland
  • Lola Perez, University of Cordoba, Cordoba, Spain
  • Vieno Piironen, University of Helsinki, Finland
  • Alessandra Pino, University of Catania, Catania, Italy
  • Mojmir Rychtera, University of Chemistry and Technology, Prague, Czech Republic
  • Katharina Scherf, Technical University, Munich, Germany
  • Regine Schönlechner, University of Natural Resources and Life Sciences, Vienna, Austria
  • Arun Kumar Sharma, Department of Atomic Energy, Delhi, India
  • András Szarka, Budapest University of Technology and Economics, Budapest, Hungary
  • Mária Szeitzné Szabó, Budapest, Hungary
  • Sándor Tömösközi, Budapest University of Technology and Economics, Budapest, Hungary
  • László Varga, Széchenyi István University, Mosonmagyaróvár, Hungary
  • Rimantas Venskutonis, Kaunas University of Technology, Kaunas, Lithuania
  • Barbara Wróblewska, Institute of Animal Reproduction and Food Research, Polish Academy of Sciences Olsztyn, Poland

 

Acta Alimentaria
E-mail: Acta.Alimentaria@uni-mate.hu

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2023  
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Acta Alimentaria
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Acta Alimentaria
Language English
Size B5
Year of
Foundation
1972
Volumes
per Year
1
Issues
per Year
4
Founder Magyar Tudományos Akadémia    
Founder's
Address
H-1051 Budapest, Hungary, Széchenyi István tér 9.
Publisher Akadémiai Kiadó
Publisher's
Address
H-1117 Budapest, Hungary 1516 Budapest, PO Box 245.
Responsible
Publisher
Chief Executive Officer, Akadémiai Kiadó
ISSN 0139-3006 (Print)
ISSN 1588-2535 (Online)

 

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