An Estimate of the Effects from Precision Livestock Farming on a Productivity Index at Farm Level. Some Evidences from a Dairy Farms’ Sample of Lombardy

Carillo, Felicetta; Abeni, F.

doi:10.3390/ani10101781

Cited by 15 publications

(4 citation statements)

References 27 publications

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“…While the initial cost of purchasing PLF systems may be unattractive to some enterprises, an improvement in financial performance could be expected through improvements in fertility, health, and the corresponding efficiency improvements if technology is exploited to its full potential (Carillo and Abeni, 2020). Previous work demonstrated that for an average yielding cow, like those in groups 1-2, the net cost of a day of delay in conception is £1.73 (at 2001 prices) when conception is delayed from 85 to 100 days post-calving, increasing to £3.55 per day if conception occurred at 146 to 175 days post-calving (Esslemont et al, 2001).…”

Section: Discussionmentioning

confidence: 99%

The impacts of precision livestock farming tools on the greenhouse gas emissions of an average Scottish dairy farm

Ferguson,

Bowen,

McNicol

et al. 2024

Front. Sustain. Food Syst.

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Precision livestock farming (PLF) tools are increasingly used in daily herd management to improve health, welfare, and overall production. While not intended to reduce greenhouse gas (GHG) emissions on farm, PLF tools can do so indirectly by improving overall efficiency, thereby reducing the emissions per unit of product. This work modelled the potential effects of commercially available PLF tools on whole enterprise and product emissions of two average Scottish dairy farm systems (an 8,000 L and 10,000 L herd) using the Agrecalc carbon footprinting tool. Scenarios modelled included an improvement in fertility and an improvement in fertility and yield from the introduction of an accelerometer-based sensor, and an improvement in health from introduction of an accelerometer-based sensor, with and without the use of management interventions. Use of a sensor intended to improve fertility had the largest reduction in total emissions (kg CO2e) of −1.42% for a 10,000 L farm, with management changes applied. The largest reduction in emissions from milk production (kg CO2e) of −2.31% was observed via fertility technology application in an 8,000 L farm, without management changes. The largest reduction in kg CO2e per kg fat and protein corrected milk of −6.72% was observed from an improvement in fertility and yield in a 10,000 L herd, with management changes. This study has highlighted the realistic opportunities available to dairy farmers in low and high input dairy systems to reduce their emissions through adoption of animal mounted PLF technologies.

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Section: Discussionmentioning

confidence: 99%

The impacts of precision livestock farming tools on the greenhouse gas emissions of an average Scottish dairy farm

Ferguson,

Bowen,

McNicol

et al. 2024

Front. Sustain. Food Syst.

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“…Additionally, it generates a labor substitution effect, leading to a gradual reduction in the long-term average cost of dairy farming. Consequently, this enhances production efficiency and profitability [37]. Dairy farmers, being rational economic actors, may choose to allocate the earnings generated from dairy farming towards the development of dairy farm infrastructure.…”

Section: Theoretical Basis and Research Hypothesismentioning

confidence: 99%

Digital Technology, Factor Allocation and Environmental Efficiency of Dairy Farms in China: Based on Carbon Emission Constraint Perspective

Liu,

Shi,

2023

Sustainability

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The emission of carbon pollutants stemming from dairy farms has emerged as a significant obstacle in mitigating the effects of global warming. China, being a prominent nation in the field of dairy farming, encounters significant challenges related to excessive component input and elevated environmental pollution. Digital technology presents an opportunity to enhance the factor allocation of dairy farms and thus increase their environmental efficiency. This study utilizes survey data from 278 dairy farms in China to examine the effect of digital technology on the allocation of land, labor, and capital variables in dairy farms. The IV-Probit model, IV-Tobit model, treatment effect model, and two-stage least square technique are employed to empirically analyze these impacts. Simultaneously, the intermediate effect model was employed to examine the mediating function of factor allocation in the effect of digital technology on environmental efficiency. The findings indicate that digital technology has the potential to greatly enhance land transfer and land utilization rates in dairy farms. Additionally, it has been observed that digital technology may lead to a decrease in both the proportion and time of labor input. Furthermore, digital technology has the potential to decrease short-term productive input while simultaneously enhancing long-term productive input within dairy farming operations. Digital technology has been found to have an indirect yet beneficial influence on environmental efficiency. This is mostly achieved through the facilitation of resource allocation, specifically in terms of land, labor, and capital aspects. The article presents a set of policy recommendations, including the promotion of extensive integration of digital technology within dairy farms, the facilitation of optimal allocation of production factors in dairy farms, and the implementation of specialized training programs focused on digital technology.

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“…With the development of livestock husbandry, precision livestock farming technology becomes more and more popular. In Europe, there are relevant policy requirements for the identification and traceability of farm animals, which mainly involved stress and welfare [53]. In particular, the technology has brought a lot of conveniences, greatly reduced the amount of labor and workload, improved production efficiency, and laid the foundation for large-scale operations.…”

Section: Application Of the Sow Target Detection Model And Its Perspectivesmentioning

confidence: 99%

Detection and Analysis of Sow Targets Based on Image Vision

et al. 2022

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In large-scale sow production, real-time detection and recognition of sows is a key step towards the application of precision livestock farming techniques. In the pig house, the overlap of railings, floors, and sows usually challenge the accuracy of sow target detection. In this paper, a non-contact machine vision method was used for sow targets perception in complex scenarios, and the number position of sows in the pen could be detected. Two multi-target sow detection and recognition models based on the deep learning algorithms of Mask-RCNN and UNet-Attention were developed, and the model parameters were tuned. A field experiment was carried out. The data-set obtained from the experiment was used for algorithm training and validation. It was found that the Mask-RCNN model showed a higher recognition rate than that of the UNet-Attention model, with a final recognition rate of 96.8% and complete object detection outlines. In the process of image segmentation, the area distribution of sows in the pens was analyzed. The position of the sow’s head in the pen and the pixel area value of the sow segmentation were analyzed. The feeding, drinking, and lying behaviors of the sow have been identified on the basis of image recognition. The results showed that the average daily lying time, standing time, feeding and drinking time of sows were 12.67 h(MSE 1.08), 11.33 h(MSE 1.08), 3.25 h(MSE 0.27) and 0.391 h(MSE 0.10), respectively. The proposed method in this paper could solve the problem of target perception of sows in complex scenes and would be a powerful tool for the recognition of sows.

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An Estimate of the Effects from Precision Livestock Farming on a Productivity Index at Farm Level. Some Evidences from a Dairy Farms’ Sample of Lombardy

Cited by 15 publications

References 27 publications

The impacts of precision livestock farming tools on the greenhouse gas emissions of an average Scottish dairy farm

The impacts of precision livestock farming tools on the greenhouse gas emissions of an average Scottish dairy farm

Digital Technology, Factor Allocation and Environmental Efficiency of Dairy Farms in China: Based on Carbon Emission Constraint Perspective

Detection and Analysis of Sow Targets Based on Image Vision

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