Prospect and scope of artificial neural network in livestock farming: a review

Rahman, Mohibur; Mandal, Ajoy; Gayari, Indrajit; Bidyalaxmi, Kangabam; Sarkar, D.; Allu, Teja; Debbarma, Asish

doi:10.1080/09291016.2022.2139389

Cited by 2 publications

(1 citation statement)

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“…Usage of artificial intelligence in the form of artificial neural networks (ANNs) in modelling dairy cow herd parameters is relatively new, but promising [19,31]. ANNs are employed to forecast various production [23,32,33], health [34,35], and behaviour indicators [36] that are essential for managing dairy cow herds [37,38].…”

Section: The Use Of Neural Network In Modelling Several Cattle Herd P...mentioning

confidence: 99%

Neural Modelling in the Study of the Relationship between Herd Structure, Amount of Manure and Slurry Produced, and Location of Herds in Poland

et al. 2023

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In the presented study, data regarding the size and structure of cattle herds in voivodeships in Poland in 2019 were analysed and modelled using artificial neural networks (ANNs). The neural modelling approach was employed to identify the relationship between herd structure, biogas production from manure and slurry, and the geographical location of herds by voivodeship. The voivodeships were categorised into four groups based on their location within Poland: central, southern, eastern, and western. In each of the analysed groups, a three-layer MLP (multilayer perceptron) with a single hidden layer was found to be the optimal network structure. A sensitivity analysis of the generated models for herd structure and location within the eastern group of voivodeships revealed significant contributions from dairy cows, heifers (both 6–12 and 12–18 months old), calves, and bulls aged 12–24 months. For the western voivodeships, the analysis indicated that only dairy cows and herd location made significant contributions. The optimal models exhibited similar values of RMS errors for the training, testing, and validation datasets. The model characterising biogas production from manure in southern voivodeships demonstrated the smallest RMS error, while the model for biogas from manure in the eastern region, as well as the model for slurry in central parts of Poland, yielded the highest RMS errors. The generated ANN models exhibited a high level of accuracy, with a fitting quality of approximately 99% for correctly predicting values. Comparable results were obtained for both manure and slurry in terms of biogas production across all location groups.

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Section: The Use Of Neural Network In Modelling Several Cattle Herd P...mentioning

confidence: 99%

Neural Modelling in the Study of the Relationship between Herd Structure, Amount of Manure and Slurry Produced, and Location of Herds in Poland

et al. 2023

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The economic optimization of lactation and fertility in dairy cows

Tohumcu,

Tulan Tohumcu

2024

CABI Reviews

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Lactation and fertility are recognized as fundamental factors that directly influence the sustainability of dairy farming. For farms working with high-yielding dairy cows in particular, maintaining fertility parameters at economically optimal levels is crucial to ensuring the continued viability of such operations. This review underscores the necessity of implementing multifaceted strategies to attain optimal lactation and fertility outcomes, elucidating the requisite steps involved in the execution of these strategies. These include the careful execution of estrus monitoring plans, comprehensive staff training, systematic record-keeping, ensuring optimal fertility parameters, and the judicious interpretation of herd management mathematics. Accurate forecasting and investment necessitate consideration of current market dynamics. Understanding the complex interplay between lactation and fertility in dairy cows is a critical prerequisite for improving overall economic productivity through herd management. To this end, the review presented simulates how the optimization of these two parameters can be achieved and their target values, based on a 100-head herd. While the exemplary model is based on costs in Türkiye, readers can adapt this simulation to calculate according to their own country’s standards. Furthermore, the simulation evinced that dairy farms relying solely on milk production incur losses, highlighting the need for diversification to ensure sustainability. In conclusion, the symbiotic relationship between lactation and fertility demands a mathematical approach, and the adoption of these integrated strategies is essential for the sustainability of dairy farms. In this context, profitability can be attained by heeding all cautions regarding the optimization of fertility and lactation, while closely monitoring current market costs.

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Prospect and scope of artificial neural network in livestock farming: a review

Cited by 2 publications

References 76 publications

Neural Modelling in the Study of the Relationship between Herd Structure, Amount of Manure and Slurry Produced, and Location of Herds in Poland

Neural Modelling in the Study of the Relationship between Herd Structure, Amount of Manure and Slurry Produced, and Location of Herds in Poland

The economic optimization of lactation and fertility in dairy cows

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