Visible and Hyperspectral Imaging Systems for the Detection and Discrimination of Mechanical and Microbiological Damage of Mushrooms

Horticultural products such as mushrooms are exposed to environmental conditions during their postharvest life, which may affect product quality. Loss of whiteness during storage is particularly important in the mushroom industry. Rough handling and distribution, fruiting body senescence and bacterial infections are among the main causes of mushroom discolouration. The aim of this work was to study the use of visible and hyperspectral imaging (HSI) systems for the detection and discrimination of mechanical and microbiological damage of mushrooms. This piece of research involved a) monitoring the browning of mushroom with visible computer imaging systems, b) investigating the effect of mechanical damage on the kinetics of enzymes responsible for mushroom browning, c) exploring the potential use of Vis-NIR HSI to predict PPO activity in mushroom caps and d) studying the potential application of Vis-NIR HSI for microbial and viral detection on mushroom caps and for their discrimination from mechanical damage. Results presented in this thesis show that the efficacy of commercial webcams was limited in the detection of mechanical damage on mushroom caps. Damage increased the activity of PPOs on mushroom pileipellis, but the effect of the extent of damage was not significant at the levels of study. Vis-NIR HSI showed some potential as a tool to estimate the activity of PPO enzymes on mushroom caps. The combination of HSI with chemometric tools allowed for the differentiation of mechanically and microbiologically damaged mushroom classes. Results from this study could be used for developing non-destructive monitoring systems for mechanical and microbiological damage detection and discrimination. The potential application of such systems as on-line process analytical tools would facilitate rapid assessment of mushroom quality.

Visible Near-Infrared Hyperspectral Imaging for the Identification and Discrimination of Brown Blotch Disease on Mushroom (Agaricus bisporus) Caps

Brown blotch, caused by pathogenic Pseudomonas tolaasii (P. tolaasii), is the most problematic bacterial disease in Agaricus bisporus mushrooms. Although it does not cause any health problems, it reduces the consumer appeal of mushrooms in the market place, generating important economical losses worldwide. Hyperspectral imaging (HSI) is a non-destructive technique that combines imaging and spectroscopy to obtain information from a sample. The objective of this study was to investigate the use of HSI for brown blotch identification and discrimination from mechanical damage on mushrooms. Hyperspectral images of mushrooms subjected to i) no treatment, ii) mechanical damage or iii) microbiological spoilage were taken during storage and spectra representing each of the classes were selected. Partial least squares- discriminant analysis (PLS-DA) was carried out in two steps: i) discrimination between undamaged and damaged mushrooms and ii) discrimination between damage sources (i.e. mechanical or microbiological). The models were applied at a pixel level and a decision tree was used to classify mushrooms into one of the aforementioned classes. A correct classification of \u3e95% was achieved. Results from this study could be used for the development of a sensor to detect and classify mushroom damage of mechanical and microbial origin, which would facilitate the industry to make rapid and automated decisions to discard produce of poor marketability

Citizen consultations on science communication: A citizen science approach

Citizen science is part of a wider trend in science and society of promoting two-way dialogue and engagement between scientists and the public, by involving citizens in the research process. This paper examines how CONCISE, an international research project involving Spain, Italy, Portugal, Poland, and Slovakia, seeks to understand how citizens acquire and use scientific information, by engaging citizens through public consultations. The consultations gathered close to 500 citizens in 2019. Asking them for suggestions on how to improve science communication and involving them in the dissemination efforts, CONCISE aims to put citizens at the core of the research process.info:eu-repo/semantics/publishedVersio

Prediction of Polyphenol Oxidase Activity Using Visible Near-Infrared Hyperspectral Imaging on Mushroom (Agaricus bisporus) Caps.

Physical stress (i.e. bruising) during harvesting, handling and transportation triggers enzymatic discoloration of mushrooms, a common and detrimental phenomenon largely mediated by polyphenol oxidase (PPO) enzymes. Hyperspectral imaging (HSI) is a non-destructive technique that combines imaging and spectroscopy to obtain information from a sample. The objective of this study was to assess the ability of HSI to predict the activity of PPO on mushroom caps. Hyperspectral images of mushrooms subjected to various damage treatments were taken, followed by enzyme extraction and PPO activity measurement. Principal component regression (PCR) models (each with 3 PCs) built on raw reflectance and multiple scatter corrected (MSC) reflectance data were found to be the best modeling approach. Prediction maps showed that the MSC model allowed for compensation of spectral differences due to sample curvature and surface irregularities. Results reveal the possibility of developing a sensor which could rapidly identify mushrooms with higher likelihood to develop enzymatic browning and hence aid produce management decision makers in the industry

Communication role on perception and beliefs of EU citizens about science

Este documento presenta un conjunto de recomendaciones basadas en el conocimiento de las consultas públicas de CONCISE. Los puntos se enumeran según los diferentes destinatarios: comunicadores científicos, responsables políticos, científicos y público en general. El principal objetivo de CONCISE es determinar el papel que desempeña la comunicación científica en la formación de creencias, percepciones y conocimientos sobre cuestiones científicas. Para lograr este objetivo, CONCISE llevó a cabo cinco consultas públicas en Lisboa (Portugal), Valencia (España), Vicenza (Italia), Trnava (Eslovaquia) y Lodz (Polonia) con la participación de cerca de 500 ciudadanos. Esto permitió al consorcio recopilar testimonios de diferentes regiones de la UE, proporcionando así a CONCISE información comparable y fiable sobre las percepciones generales de los ciudadanos de la UE sobre los cuatro temas científicos candentes en estudio, a saber, las vacunas, la medicina complementaria y alternativa, el cambio climático y los organismos modificados genéticamente.This policy brief presents a set of recommendations based on the knowledge of CONCISE's public consultations. The points are listed according to the different target: science communicators, policymakers, scientists and general audience. CONCISE’s main objective is to determine the role that science communication plays in shaping beliefs, perceptions and knowledge of scientific issues. To achieve this aim, CONCISE carried out five public consultations in Lisbon (Portugal), Valencia (Spain), Vicenza (Italy), Trnava (Slovakia) and Lodz (Poland) with the participation of near on 500 citizens. This allowed the consortium to gather testimonies from different EU regions, thus providing CONCISE with comparable and reliable information on EU citizens’ general perceptions of the four burning science issues under study, namely, vaccines, complementary and alternative medicine, climate change and genetically modified organisms

El papel que desempeña la comunicación de la ciencia en la opinión de la ciudadanía europea

El documento recoge las recomendaciones políticas recomendadas a partir de los resultados de investigación del proyecto europeo H2020 CONCISE. En este proyecto se llevaron a cabo cinco consultas ciudadanas, en cinco ciudades europeas de España, Italia, Eslovaquia, Portugal y Polinia), en las que participaron alrededor de 100 ciudadanos en cada una de ellas, para hablar sobre ciencia. Concretamente a los ciudadanos se les preguntó cómo se informaban y en qué fuentes o canales confiaban más para informarse de temas como las vacunas, el cambio climático, las medicinas complementarias o alternativas, y los organismos modificados genéticamente. Los debates arrojaron información muy valiosa para el diseño de políticas públicas.H2020 CONCISE G.A. No 824537The document includes the suggested policy brief recommendations based on the European H2020 CONCISE project's research results. In this project, five citizen consultations were carried out in five European cities from Spain, Italy, Slovakia, Portugal and Poland, in which around 100 citizens participated in each of them to talk about science. Specifically, citizens were asked how they were informed and how sources or channels they trusted the most to find out about vaccines, climate change, complementary or alternative medicines, and genetically modified organisms. The debates yielded very valuable information for the design of public policies

Recent applications of hyperspectral imaging in microbiology

Hyperspectral chemical imaging (HSI) is a broad term encompassing spatially resolved spectral data obtained through a variety of modalities (e.g. Raman scattering, Fourier transform infrared microscopy, fluorescence and near-infrared chemical imaging). It goes beyond the capabilities of conventional imaging and spectroscopy by obtaining spatially resolved spectra from objects at spatial resolutions varying from the level of single cells up to macroscopic objects (e.g. foods). In tandem with recent developments in instrumentation and sampling protocols, applications of HSI in microbiology have increased rapidly. This article gives a brief overview of the fundamentals of HSI and a comprehensive review of applications of HSI in microbiology over the past 10 years. Technical challenges and future perspectives for these techniques are also discussed

Visible Near-Infrared Hyperspectral Imaging for the Identification and Discrimination of Brown Blotch Disease on Mushroom (Agaricus bisporus) Caps

Brown blotch, caused by pathogenic Pseudomonas tolaasii (P. tolaasii), is the most problematic bacterial disease in Agaricus bisporus mushrooms. Although it does not cause any health problems, it reduces the consumer appeal of mushrooms in the market place, generating important economical losses worldwide. Hyperspectral imaging (HSI) is a non-destructive technique that combines imaging and spectroscopy to obtain information from a sample. The objective of this study was to investigate the use of HSI for brown blotch identification and discrimination from mechanical damage on mushrooms. Hyperspectral images of mushrooms subjected to i) no treatment, ii) mechanical damage or iii) microbiological spoilage were taken during storage and spectra representing each of the classes were selected. Partial least squares- discriminant analysis (PLS-DA) was carried out in two steps: i) discrimination between undamaged and damaged mushrooms and ii) discrimination between damage sources (i.e. mechanical or microbiological). The models were applied at a pixel level and a decision tree was used to classify mushrooms into one of the aforementioned classes. A correct classification of >95% was achieved. Results from this study could be used for the development of a sensor to detect and classify mushroom damage of mechanical and microbial origin, which would facilitate the industry to make rapid and automated decisions to discard produce of poor marketability

Hyperspectral Imaging for the Detection of Microbial Spoilage of Mushrooms

Brown blotch, caused by pathogenic Pseudomonas tolaasii, is the most problematic bacterial disease in Agaricus bisporus mushrooms; it reduces their consumer appeal in the market place, thus generating important economical losses worldwide. The mushroom industry is in need of fast and accurate evaluation methodologies to ensure that only high quality produce reaches the market. Hyperspectral imaging (HSI) is a non-destructive technique that combines imaging and spectroscopy to obtain spatial and spectral information from an object. The aim of this study was to investigate the potential of Vis-NIR HSI to identify microbiological damage in mushrooms and to discriminate it from mechanical damage. Hyperspectral images of mushrooms subjected to i) no treatment, ii) microbiological spoilage and iii) mechanical damage were taken during storage and spectra representing each of the classes were selected. Partial least squares- discriminant analysis (PLS-DA) was carried out in two steps: i) discrimination between undamaged and damaged mushrooms and ii) discrimination between damage sources (i.e. microbiological or mechanical). The models were applied at a pixel level and a decision tree was used to classify mushrooms into one of the aforementioned classes. A correct classification of >95% was achieved. This was the first reported study to employ HSI for the detection of damage of bacterial origin in horticultural products. The industry could incorporate the knowledge gained in this study towards the development of a HSI sensor to detect and classify mushroom damage of microbial and mechanical origin, enabling the rapid and automated identification of mushrooms of reduced marketability