The assessment of fresh and spoiled beef meat using a prototype device based on GigE Vision camera and DSP

Arsalane, Assia; Barbri, Noureddine El; Tabyaoui, Abdelmoumen; Klilou, Abdessamad; Rhofir, Karim

doi:10.1007/s11694-019-00090-y

Cited by 11 publications

(3 citation statements)

References 31 publications

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“…a single or a few components could not sufficiently characterise its quality, or the fact that they are very expensive (Xu et al 2011). The synergistic use of instrumental analytical techniques and chemometrics represents a promising way in the development of authenticity and traceability models (Osorio et al 2013;Danezis et al 2016;Granato et al 2018;Arsalane et al 2019;Rohman 2019;L opez-Pedrouso et al 2020). The objective of this work was to evaluate the reliability of the multivariate statistical analysis of intramuscular FA profile of bovine and ovine meat samples to discriminate the feeding system and the animal species they originate from.…”

Section: Introductionmentioning

confidence: 99%

Discriminant analysis as a tool to identify bovine and ovine meat produced from pasture or stall-fed animals

Acciaro

Decandia

Sitzia

et al. 2020

Italian Journal of Animal Science

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This work evaluated the reliability of the multivariate statistical analysis to discriminate the feeding system and the species of ruminants using their intramuscular fatty acids (FA) profile. FA composition of 53 meat samples (longissimus dorsi muscle) from animals of different species (sheep and cattle) raised with different feeding systems (pasture and stall-fed) (4 groups overall) was determined and expressed as % fatty acid methyl ester (FAME). A stepwise discriminant analysis (SDA) was applied to the full set of FA to select the variables that best discriminated between feeding systems and animal species. The selected variables were then submitted to a canonical discriminant analysis (CDA) to test the ability of those variables in discriminating against the four groups. Discriminant analysis (DA) was then exploited to classify meat samples. From the 62 initial variables detected in the FA profile, 24 were retained in the SDA. The subsequent CDA developed by using the selected variables, significantly discriminated the four groups (Hotelling's test p < 0.0001) by extracting three canonical functions. Heptadecenoic acid C17:1 c10, seemed to play a pivotal role both in discriminating species and feeding system while some 18:1 isomers (C18:1 c12, C18:1 c13 C18:1 t13/t14) together with CLA c9, t11 and x-3 were important in discriminating feeding systems. Multivariate statistical analysis of FA was able to track both the species and the feeding system of source animals with good accuracy. HIGHLIGHTS The increasing interest in the 'green image' of meat obtained from grass-based systems guides the search for methods to trace the animal feeding system. Extracting more information from the large amounts of meat data provided by laboratory equipment is of utmost importance. Multivariate statistical analysis is able to trace with good accuracy meat samples back to their animal species and feeding system origin.

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Section: Introductionmentioning

confidence: 99%

Discriminant analysis as a tool to identify bovine and ovine meat produced from pasture or stall-fed animals

Acciaro

Decandia

Sitzia

et al. 2020

Italian Journal of Animal Science

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“…The conventional and technological interventions are currently established by endogenous meat proteases and plant‐derived exogenous proteases (Bojorges et al., 2020; Chang et al., 2021). As the demand for consuming meat and its products increase in densely populated and developing countries, it is necessary to employ promising compounds to create quick and uniform tenderness in meat chunks without many destructive effects on myofibrillar and connective tissues (Arsalane et al., 2019; Noshad et al., 2021). Since the addition of these components is dependent on their hydrolytic activities toward targets, the dose exceeding the limit may affect the quality and texture (Dhital & Vangnai, 2019; Wang et al., 2020).…”

Section: Introductionmentioning

confidence: 99%

Prediction of top round beef meat tenderness as a function of marinating time based on commonly evaluated parameters and regression equations

Rostamani

Baghaei

Bolandi

2021

Food Science & Nutrition

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Tenderness is greatly impacted the organoleptic and quality characteristics of meat and its products (Bojorges et al., 2020;Brito Lopes et al., 2020;Ma & Kim, 2020). Inconsistency and nonuniformly texturized meat products are the major problems encountered by the meat industry that affecting tenderness and also customer satisfaction (Stadnik & Dolatowski, 2011;Uyarcan & Kayaardi, 2019;Zhou et al., 2020). Hence, over the past few decades, the industrial sections concentrated on discovering safe and innovative ingredients and methods to solve this issue. In aged animals, firmness is accompanied by the development of perimysium, endomysium thickness, and the generation of cross-links between collagen molecules.

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“…It has been used by a large scientific community to build real time embedded systems. Abdelkareem et al [10] have developed high performance software that requires real-time embedded systems for emerging technology areas like 5G Wireless and software defined [11][12][13][14][15] have developed an embedded system based on the C6678 DSP for beef meet freshness evaluation.…”

Section: Introductionmentioning

confidence: 99%

Parallel implementation of pulse compression method on a multi-core digital signal processor

Klilou

2020

IJECE

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Pulse compression algorithm is widely used in radar applications. It requires a huge processing power in order to be executed in real time. Therefore, its processing must be distributed along multiple processing units. The present paper proposes a real time platform based on the multi-core digital signal processor (DSP) C6678 from Texas Instruments (TI). The objective of this paper is the optimization of the parallel implementation of pulse compression algorithm over the eight cores of the C6678 DSP. Two parallelization approaches were implemented. The first approach is based on the open multi processing (OpenMP) programming interface, which is a software interface that helps to execute different sections of a program on a multi core processor. The second approach is an optimized method that we have proposed in order to distribute the processing and to synchronize the eight cores of the C6678 DSP. The proposed method gives the best performance. Indeed, a parallel efficiency of 94% was obtained when the eight cores were activated.

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The assessment of fresh and spoiled beef meat using a prototype device based on GigE Vision camera and DSP

Cited by 11 publications

References 31 publications

Discriminant analysis as a tool to identify bovine and ovine meat produced from pasture or stall-fed animals

Discriminant analysis as a tool to identify bovine and ovine meat produced from pasture or stall-fed animals

Prediction of top round beef meat tenderness as a function of marinating time based on commonly evaluated parameters and regression equations

Parallel implementation of pulse compression method on a multi-core digital signal processor

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