On-line weight estimation of broiler carcass and cuts by a computer vision system

Nyalala, Innocent; Okinda, Cedric; Makange, Nelson Richard; Korohou, Tchalla; Chen, Qi; Nyalala, Luke; Zhang, Jiayu; Zuo, Yi; Yousaf, Khurram; Liu, Chao; Chen, Kunjie

doi:10.1016/j.psj.2021.101474

Cited by 10 publications

(8 citation statements)

References 25 publications

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“…When negative values were found for the Performance Index, it was an indication that variables were above or below the thermoneutral limits found in the literature [5,7,[27][28][29][30].…”

Section: Discussionmentioning

confidence: 93%

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A Mobile Application to Follow Up the Management of Broiler Flocks

et al. 2021

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Broiler meat is one of the most consumed meats worldwide. The broiler production system poses several challenges for the producer, including maintaining environmental conditions for rearing. The popularization of mobile devices (smartphones) among people, including those with lower incomes, makes it possible for specialist systems to be developed and used for diverse purposes through Apps (mobile application). The present study proposed the development of a mobile application to help farmers follow up on-farm flock management. We retrieved rearing environment and flock data from commercial broiler farms that complied with broiler-producing standards and followed the breeders’ recommendations. Data were organized and normalized to serve as the basis for the software. We specified a performance index based on the average environment and flock-based data. The language used for the application development was Python compatible with the GNU GPL (General Public License), which has a vast library of ready-made functions. For the graphical interface, we selected Kivy and KivyMD framework. The developed mobile application might help farmers evaluate broiler rearing conditions on-farm during the flock’s growth and grade the flock using a performance index.

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“…When negative values were found for the Performance Index, it was an indication that variables were above or below the thermoneutral limits found in the literature [5,7,[27][28][29][30].…”

Section: Discussionmentioning

confidence: 93%

“…The language in which the application was developed was Python. This language has a vast library of ready-made functions and extensive literature to support it [25][26][27]. It provided us with a great arsenal to perform data analysis in many possible ways.…”

Section: Calculation Of the Normalized Performance Index (Pi)mentioning

confidence: 99%

A Mobile Application to Follow Up the Management of Broiler Flocks

et al. 2021

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show abstract

“…In contrast, cameras can be easily installed and suitable for the production line. Two types of computer-vision enabled noncontact weighing methods have also been extensively studied: classification and regression ( Lotufo et al, 1999 ; Nyalala et al, 2021 ; Teimouri et al, 2018 ). In classification methods, the carcass weight is classified into one of the evenly divided grades (weight ranges) ( Chen et al, 2017 ; Koodtalang and Sangsuwan, 2019 ; Qi et al, 2019 ).…”

Section: Introductionmentioning

confidence: 99%

“…The current image weighing methods are based on regression models using 3D images ( Adamczak et al, 2018 ; Jørgensen et al, 2019 ) or 2D images ( Lotufo et al, 1999 ; Nyalala et al, 2021 ). In these methods, a weight prediction model was built based on several manually extracted features.…”

Section: Introductionmentioning

confidence: 99%

“…It thus is still attractive to estimate the weight of small animals using 2D images. Nyalala et al (2021) segmented the depth images of broiler carcass into 5 parts, extract 2D features, and estimated the weights of different parts using different regression models. We found that most methods require handcrafted features which will determine the upper bound of the model performance ( Chen et al, 2021 ).…”

Section: Introductionmentioning

confidence: 99%

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