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Animal biometric assessment using non-invasive computer vision and machine learning are good predictors of dairy cows age and welfare: The future of automated veterinary support systems
ارزیابی بیومتریک حیوانات با استفاده از بینایی کامپیوتری غیرتهاجمی و یادگیری ماشینی پیشبینیکننده خوبی برای سن و رفاه گاوهای شیری هستند: آینده سیستمهای پشتیبانی خودکار دامپزشکی-2022 Digitally extracted biometrics from visible videos of farm animals could be used to automatically assess animal
welfare, contributing to the future of automated veterinary support systems. This study proposed using non-
invasive video acquisition and biometric analysis of dairy cows in a robotic dairy farm (RDF) located at the
Dookie campus, The University of Melbourne, Australia. Data extracted from dairy cows were used to develop
two machine learning models: a biometrics regression model (Model 1) targeting (i) somatic cell count, (ii)
weight, (iii) rumination, and (iv) feed intake and a classification model (Model 2) mapping features from dairy
cow’s face to predict animal age. Results showed that Model 1 achieved a high correlation coefficient (R = 0.96),
slope (b = 0.96), and performance, and Model 2 had high accuracy (98%), low error (2%), and high performance
without signs of under or overfitting. Models developed in this study can be used in parallel with other models to
assess milk productivity, quality traits, and welfare for RDF and conventional dairy farms. keywords: هوش مصنوعی | فیزیولوژی گاو | ماستیت | بیومتریک حیوانات | سنجش از راه دور برد کوتاه | Artificial intelligence | Cows physiology | Mastitis | Animal biometrics | Short range remote sensing |
مقاله انگلیسی |
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Evaluation of infrared thermography combined with behavioral biometrics for estrus detection in naturally cycling dairy cows
ارزیابی ترموگرافی مادون قرمز همراه با بیومتریک رفتاری برای تشخیص فحلی در گاوهای شیری دوچرخه سواری طبیعی-2021 Low estrus detection rates (>50%) are associated to extended calving intervals, low economic profit and
reduced longevity in Holstein dairy cows. The objective of this study was to evaluate the accuracy of
infrared thermography and behavioral biometrics combined as potential estrus alerts in naturally (not
induced) cycling dairy cows housed in a tie-stall barn. Eighteen first lactation cows were subjected to
transrectal ultrasonography to determine spontaneous ovulation. The dominant follicle (DF) disappearance was used retrospectively as an indirect indicator of ovulation, and to establish the estrus period
(48–24 h prior the DF disappearance). Raw skin temperature (Raw IR) and residual skin temperature
(Res IR) were recorded using an infrared camera at the Vulva area with the tail (Vtail), Vulva area without
the tail (Vnotail), and Vulva’s external lips (Vlips) at AM and PM milking from Day 14 until two days after
ovulation was confirmed. Behavioral biometrics were recorded on the same schedule as infrared scan.
Behavioral biometrics included large hip movements (L-hip), small hip movements (S-hip), large tail
movements and small tail movements to compare behavioral changes between estrus and nonestrus
periods. Significant increases in Raw IR skin temperature were observed two days prior to ovulation
(Vtail; 35.93 ± 0.27 C, Vnotail; 35.59 ± 0.27 C, and Vlips; 35.35 ± 0.27 C) compared to d 5
(Proestrus; Vtail; 35.29 ± 0.27 C, Vnotail; 34.93 ± 0.31 C, and Vlips; 34.68 ± 0.27 C). No significant
changes were found for behavioral parameters with the exception of S-hip movements, which increased
at two days before ovulation (d 2; 11.13 ± 1.44 Events/5min) compared to d 5 (7.30 ± 1.02
Events/5min). To evaluate the accuracy of thermal and behavioral biometrics, receiver operating characteristic curve analysis was performed using Youden index (YJ), diagnostic odds ratio, positive likelihood
ratio (LR+), Sensitivity, Specificity and Positive predicted value to score the estrus alerts. The greatest
accuracy achieved using thermal parameters was for Res IR Vtail PM (YJ = 0.34) and L-hip PM
(YJ = 0.27) for behavioral biometrics. Combining thermal and behavioral parameters did not improve
the YJ index score but reduced the false-positive occurrence observed by increasing the diagnostic odds
ratio (26.62), LR+ (12.47), Specificity (0.97) and positive predicted value (0.90) in a Res IR Vtail PM, S-hip
AM, S-hip PM combination. The combination of thermal and behavioral parameters increased the accuracy of estrus detection compared to either thermal or behavioral biometrics, independently in naturally
cycling cows during milking.
Keywords: Combined-parameters | First-lactating | Movement-frequency | Preovulation | Skin temperature |
مقاله انگلیسی |
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Reimagining the milk supply chain: Reusable vessels for bulk delivery
Reimagining زنجیره تامین شیر: ظروف قابل استفاده مجدد برای تحویل به صورت عمده-2021 Milk packaging has been analysed multiple times in pursuit of finding the most appropriate vessel from an environmental point of view. Research has concentrated on commercially available containers of 0.5 –2.5 litres, usually made from High-Density Polyethylene (HDPE), Polyethylene Terephthalate (PET), paper- based cartons, or glass, with some studies considering a reuse scheme for glass bottles. Whilst applicable for household delivery, such a reuse scheme is not practical for delivery to cafés where large volumes of milk are used every day; little information is known about transportation of bulk volumes of milk in bigger vessels such as steel churns. This study compares a proposed milk supply chain using a mix of reusable stainless steel churns and reusable glass bottles with the current supply chain that uses single- use HDPE bottles, for transportation of milk to 10 cafés belonging to The University of Sheffield. A cradle- to-grave life cycle assessment (LCA) is conducted using data obtained from the university and Our Cow Molly, a local dairy farm which delivers milk to the university. Sensitivity analysis was performed around the recycling rate of plastic bottles, water consumption for churn cleaning, the reuse rate of glass bottles and churns and the source of the on-farm electricity. The study suggests that the greenhouse gas emission can be lowered by approx. 6.5 tons of CO2 equivalent annually if the reuse scheme is applied (this equates to a 65% reduction for the processes analysed). Considerable savings are also reported in cate- gories such as water consumption, fossil resources depletion and cumulative energy demand. The reuse scheme is, however, likely to induce a similar or higher mineral resource use and higher environmental damage in the marine eutrophication category due to water treatment. Production of plastic bottles in the plastic scenario and maintenance and transport on the reusable side are the main contributors to the environmental impact. Further improvements in the reuse scenario could be achieved by reducing the amount of water used for cleaning and hence the electricity demand for water heating. The reuse scheme could also benefit environmentally from using an electric refrigerated van instead of a diesel vehicle.© 2021 Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved. Keywords: Life cycle assessment | Milk | Reuse | Plastic | Impact assessment | Carbon footprint |
مقاله انگلیسی |
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Computer vision and weigh scale-based prediction of milk yield and udder traits for individual cows
Computer vision and weigh scale-based prediction of milk yield and udder traits for individual cows-2021 The measurement of the performance of dairy cow milk production contributes to improve the productivity and profitability of dairy farms. Milk yield is used on-farm for decisions around culling, drying off, heat detection and off-farm for estimation of sire breeding values. Milk yield is measured by herd testing at multiple times through a lactation and by individual milk meters, although the rate of herd testing is decreasing and only a minority of milking systems have milk meters. The goal of this study was to develop a non-contact computer vision and/or walk-over weigh scale technology based on cow 3D images and/or weights before and after milking to determine individual cow milk yield and the lactation milk yield for individual cows. This technology could provide some of the benefits of individual milk meters, although only 1–2 sensors would be required per milking apparatus as opposed to a milk meter per bale on the milking apparatus. An algorithm was developed to estimate the udder volume before milking, udder volume after milking and the difference in udder volume before and after milking. A calibration model based on in-line milk meter measured milk yield from 20 cows was developed to predict milk yield per milking. The model based on udder volume before milking and the difference in udder volume before and after milking had a calibration R2 = 0.92 and RMSE = 0.84 L. The algorithm RMSE was inferior to the in-line milk meter (RMSE = 0.5 L for this trial). This imaging technology provides an inexpensive method to determine the milk yield of individual cows, which can be used for better on-farm management of cows in the herd. The feasibility of determining lactation yield from walk-over weigh scale measurements of each cow before and after each milking was also demonstrated, with algorithm prediction (based on a 2.5% weigh scale error) of lactation milk yield estimated to be similar to that based on two herd tests per lactation. Furthermore, the potential of image-based phenotyping of udder traits such as front/rear teat placement, teat length and teat orientation were demonstrated, with an estimated model accuracy of 94% for front/rear teat placement on a 9-point scale. Average rear teat length was 39 ± 1.5 mm and average front teat length was 49 ± 1.3 mm. This highlights the potential for using computer vision for on-farm prediction of milk performance and udder traits from dairy cows. Keywords: Milk yield | Cow | Computer vision | Udder | Teat |
مقاله انگلیسی |
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Perishable material sourcing and final product pricing decisions for two-echelon supply chain under price-sensitive demand
تصمیم گیری برای تهیه مواد فاسدشدنی و تصمیمات قیمت نهایی محصول برای زنجیره تأمین دو طبقه تحت تقاضای حساس به قیمت-2021 This paper considers a single product supply chain involving a producer/processor and a retailer. The producer/ processor procures and processes perishable materials such as fruits and milk whose demand are often price- sensitive. We model the dyadic relationship as a Stackelberg game to understand how product perishability and the price-sensitive demand of such products can influence the procurement, production, and sale. The producer/processor is the leader and decides on the processing time of the materials and the wholesale price of the product to maximize profit. The retailer as the follower decides on the sale price of the product and order quantity to maximize profit under a price-sensitive demand setting. Propositions and lemmas for optimality are posed, and the model is validated numerically. Our results suggest that the retailer’s profit cannot be worse than the producer/processor under a price elastic demand. With a high deterioration rate or shrinkage, the producer/ processor should improve the storage conditions or processing capacity within certain constraints for better overall supply chain profitability. Finally, both the producer/processor and the retailer need to consider the price sensitivity of consumers when making pricing decisions. Keywords: Two-echelon supply chain | Perishable inventory | Deterioration rate | Price-sensitive demand | Stackelberg game |
مقاله انگلیسی |
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Colour assessment of milk and milk products using computer vision system and colorimeter
ارزیابی رنگ شیر و فرآورده های شیر با استفاده از سیستم بینایی ماشین و رنگ سنج-2021 A computer vision system (CVS) and a colorimeter were compared for their abilities to measure the colour of twenty-seven different milks and milk products. The frequency of similarity test showed that CVS-generated colour chips were similar to the actual sample colour in all trials (100%). The CVS- obtained colours were found to be more similar to the colour of sample visualised on the monitor, compared with colorimeter-generated colour chips, with values of 83.3e100.0% depending on the milk product. The third test showed that there was difference between colour measured by CVS and the colorimeter; colorimeter readings resulted in a darker and yellower colour based on average L*a*b* values, while CVS readings resulted in lighter and less yellow appearance. Compared with a colorimeter, measuring colour by CVS was, therefore, found to be reliable and should be considered as a superior tool for replacing traditional devices by offering improved representativeness and accuracy.© 2021 Elsevier Ltd. All rights reserved. |
مقاله انگلیسی |
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Shaping the sustainable supply chain of organic milk in Brazil
شکل گیری زنجیره تأمین پایدار شیر آلی در برزیل-2021 The aim of this paper is to contribute to the discussion about how a sustainable supply chain is implemented, and its effects on suppliers. The sustainable supply chain and the concept of upgrading were used to analyze the proposed phenomenon. One in-depth case study was conducted, based on fourteen interviews with multiple stakeholders involved in the process of converting the traditional milk production chain into the organic system of one of the global leaders in the food industry, and the largest buyer of raw milk in Brazil. This empirical effort allows us to examine how a focal company shapes the organic milk supply chain, and the effects this process bears on farmers, highlighting theoretical contributions which also relate to the paper’s contributions. The outcomes indicate that private governance shapes sustainable supply chain through captive and relational links leading to social upgrading.© 2021 Elsevier Ltd. All rights reserved. Keywords: Social upgrading | Relational governance | Captive governance | Suppliers | Organic milk | Focal company |
مقاله انگلیسی |
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A multi-stakeholder participatory study identifies the priorities for the sustainability of the small ruminants farming sector in Europe
یک مطالعه مشارکتی چند ذینفع اولویت های پایداری بخش کشاورزی کوچک نشخوارکنندگان در اروپا را مشخص می کند-2020 The European small ruminants (i.e. sheep and goats) farming sector (ESRS) provides economic, social and environmental benefits to society, but is also one of the most vulnerable livestock sectors in Europe. This sector has
diverse livestock species, breeds, production systems and products, which makes difficult to have a clear vision
of its challenges through using conventional analyses. A multi-stakeholder and multi-step approach, including
90 surveys, was used to identify and assess the main challenges for the sustainability of the ESRS to prioritize actions. These challenges and actions were identified by ESRS experts including farmers, cooperatives, breeding associations, advisers and researchers of six EU countries and Turkey. From the 30 identified challenges, the most
relevant were economy-related challenges such as ‘uncertainty of meat and milk prices’, ‘volatility of commodity
prices’, ‘low farm income’, ‘high subsidy dependency’ and ‘uncertainty in future changes in subsidies’ resulting in
‘a sector not attractive to young farmers’. Most of these challenges were beyond the farmer’s control and perceived as difficult to address. Challenges were prioritized using an index, calculated by multiplying the relevance
and the feasibility to address measures. The identified challenges had a similar priority index across the whole
sector with small differences across livestock species (sheep vs goats), type of products (meat vs dairy) and intensification levels (intensive vs semi-intensive vs extensive). The priorities were different, however, between
socio-geographical regions (Southern vs Central Europe). Some of the top prioritized challenges were linked to
aspects related to the production systems (‘low promotion of local breeds’ and ‘slow adaptability of high producing breeds’) and market practices (‘unfair trade/lack of traceability’). The majority of the priority challenges, however, were associated with a deficient knowledge or training at farm level (‘poor business management training’,
‘lack of professionalization’, ‘slow adoption of innovations’), academia (‘researchers do not address real problems’) and society as a whole (‘low consumer education in local products’, ‘low social knowledge about farming’,
‘poor recognition of farming public services’). Thus, improved collaboration among the different stakeholders
across the food chain with special implication of farmers, associations of producers, academia and governments
is needed to facilitate knowledge exchange and capacity building. These actions can contribute to make ESRS economically more sustainable and to adapt the production systems and policy to the current and future societal
needs in a more region-contextualized framework.
Keywords: Dairy | Goat production | Meat | Sheep production | Sustainability |
مقاله انگلیسی |
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Precision livestock farming, automats and new technologies: possible applications in extensive dairy sheep farming
دامداری دقیق ، اتومات و فناوری های جدید: کاربردهای احتمالی در دام گسترده تولید گوسفند شیری-2020 Precision livestock farming (PLF) technologies are becoming increasingly common in modern agriculture. They are frequently integrated with other new technologies in order to improve human–livestock interactions, pro- ductivity and economical sustainability of modern farms. New systems are constantly being developed for concentrated farming operations as well as for extensive and pasture-based farming systems. The development of technologies for grazing animals is of particular interest for the Mediterranean extensive sheep farming sector. Dairy sheep farming is a typical production system of the area linked to its historical and cultural traditions. The area provides roughly 40% of the world sheep milk, having 27% of the milk-producing ewes. Developed countries of the area (France, Italy, Greece and Spain – FIGS) have highly specialized production systems improved through animal selection, feeding techniques and intensification of production. However, extensive systems are still practiced alongside intensive ones due to their lower input costs and better resilience to market fluctuations. In the current article, we evaluate possible PLF systems and their suitability to be incorporated in extensive dairy sheep farming as practiced in the FIGS countries. Available products include: electronic identification systems (now mandatory in the EU) such as ear tags, ruminal boluses and sub-cutaneous radio-frequency identification; on-animal sensors such as accelerometers, global positioning system) and social activity loggers; and stationary management systems such as walk-over-weights, automatic drafter (AD), virtual fencing and milking parlourrelated technologies. The systems were considered according to their suitability for the management and business model common in dairy sheep farming. However, adoption of new technologies does not take place immediately in small and medium scale extensive farmer. As sheep farmers usually belong to more conservative technology consumers, characterized by average age of 60 and a very transparent community, dynamics which does not favor financial risk taking involved with new technologies. Financial barriers linked to production volumes and resource management of extensive farming are also a barrier for innovation. However, future prospective could increase the importance of technology and promote its wider adoption. Trends such as global sheep milk economics, global warming, awareness to animal welfare, antibiotics resistance and European agricultural policies could influence the farming practices and stimulate wider adoption of PLF systems in the near future.© 2020 The Authors. Published by Elsevier Inc. on behalf of The Animal Consortium. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).IThplicationsAs precision livestock farming systems become ever more permanent in modern agriculture, their adoption in extensive farming is gradually taking place. As extensive Mediterranean dairy sheep production holds global importance in agricultural economics, possible solutions and precision livestock farming options could be considered. However, as in many other parts of the world, farmers’ acceptance and openness towards new technologies remains relatively low. Possible developments such as global warming, consumer awareness, global and local economics and European Union policies could change the current status and increase the adoption of precision livestock farming systems in the sector. Keywords: Extensive farming | Farmers acceptance | New technologies | Precision livestock farming | Sheep |
مقاله انگلیسی |
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The Chinese milk supply chain: A fraud perspective
زباله زنجیره تامین شیر چین : چشم انداز تقلب-2020 Food fraud has become a serious concern all over the world and especially in China. The melamine contaminated
infant formula in 2008 has brought food fraud in the spotlights. This incident had grave consequences for the
Chinese citizens as well as the Chinese milk industry. Fraud vulnerability assessments are the first step towards
food fraud prevention and mitigation. To combat food fraud, one has to think like a criminal. In the current
study, we determined the most vulnerable points in the Chinese milk supply chain, and examined the underlying
causes. The fraud vulnerability perceived by 90 Chinese dairy farmers and 14 milk processors was evaluated
with the SSAFE food fraud vulnerability assessment tool. Overall, actors perceived the milk supply chain as low
to medium vulnerable to food fraud. Farmers appeared significantly more vulnerable than processors due to
enhanced opportunities and motivations, and less adequate controls. Both geographical location of the farms and
their size affected their perceived fraud vulnerability significantly. Keywords: China | Dairy farmer | Economically motivated adulteration | Fraud vulnerability assessment | Milk processor | Milk supply chain |
مقاله انگلیسی |