查看更多>>摘要：? 2021 Elsevier B.V.In this paper we provide an alternative to create reference growth curves for female Hereford cattle breed based on the generalized additive models for location, scale and shape (GAMLSS) framework. The proposed methodology avoids some known problems present in the quantile regression, such as crossing quantiles and unsuitability in extreme centiles. Since GAMLSS are semi-parametric regression-type models, any statistical distribution can be considered to explain the behaviour of a given response variable (e.g., body weight) and we are able to model any and all of the parameters of the response variable distribution, it can easily deal with highly complex growth curves (e.g., presenting multiple cycles), heteroskedasticity and skewed data issues, commonly present in this field. We apply the abovementioned methodology, showing that the animal age directly affects median, variability and skewness characteristics of its growth curve. Finally, this approach may be applied in any other animal or plant growth, and it can be used as a powerful decision-making tool by producers.
查看更多>>摘要：? 2021 Elsevier B.V.In recirculating aquaculture system, the abnormal behavior of fish is usually caused by poor water quality, hypoxia or diseases. Delayed recognition of this behavior will lead to large number of fish deaths. Thus, real-time detection and tracking of fish that behaviors abnormally is an effective way to promote the fish welfare and to improve the survival rate as well as economic benefits of aquaculture. However, due to the high-density breeding, the targets in the fish images are often quite small and in occlusion, which causes high false detection and target loss rate. This article proposes a combined end-to-end neural network to detect and track the abnormal behavior of porphyry seabream. The detection algorithm passes the initial value of the target into the tracking algorithm, and the tracking algorithm tracks subsequent frames to achieve end-to-end abnormal fish behavior detection and achieve high-speed and accurate tracking of abnormal behavior individuals. In the target detection part, YOLOV5s is improved by incorporating multi-level features and adding feature mapping. Compared with the original network, the detection precision AP50:95 is increased by 8.8% while AP50 reaches 99.4%. In the target tracking part, this paper achieves multi-target tracking of abnormal fish based on single-target tracking algorithm SiamRPN++. The tracking precision is 76.7%. By combining the two approaches, individual fish with abnormal behavior can be detected precisely and tracked in real time.
查看更多>>摘要：? 2021 The AuthorsMediterranean grasslands are a cornerstone ecosystem to provide ecosystem services and sustain human societies. The sustainability and provision of ecosystem services by these systems rely on their management. One of the main attributes to perform sustainable and effective management is pasture quality, which is crucial for animal performance in rainfed extensive systems. Remote sensing of grasslands can be an effective tool to inform the management of grasslands. The forthcoming high-priority mission candidate of the European Space Agency, Copernicus Hyperspectral Imaging Mission for the Environment (CHIME) with continuous narrow bands of ≥10 nm spectral resolution could be an asset to provide accurate information on the pasture quality of high-diverse and heterogeneous grasslands. In this study, we investigated the potential of CHIME-like field spectroscopy data at 10 nm resolution to assess the quality of Mediterranean permanent grasslands. The pasture quality indicators used were: crude protein (CP), neutral detergent fibre (NDF), acid detergent fibre (ADF) and enzyme digestibility of organic matter (EDOM). To do so, two machine learning methods commonly used in remote sensing were implemented: Partial Least Squares (PLS) regression and Random Forest (RF) regression. The results using all bands in the 400–2300 nm spectral range and the results obtained by Backward Feature Elimination (BFE) were also compared. Finally, using importance measures of PLS and RF and the BFE approach, the importance and stability of the bands to assess the pasture quality indicators were explored. The results showed that field spectroscopy CHIME-like data at 10 nm of spectral resolution show potential to predict CP at “good” accuracy and NDF at “moderate” accuracy level in Mediterranean permanent grasslands. PLS outperformed RF to predict CP and NDF in terms of accuracy and certainty of the predictions. The BFE approach increased the accuracy of the predictions, especially in PLS, for which a percentage decrease of ΔRMSE = -12.5% was achieved in cross-validation to predict CP. The models built by BFE approach to predict CP using PLS provided a mean R2 value of 0.82 and a range of 0.68–0.90 in bootstrapped predictions. The RMSE was low (mean RMSE = 2.23%) and the mean RPD = 2.47 with values ranging from 1.81 to 3.23. RF models to predict CP produced mean R2 value of 0.68, mean RMSE = 3.00% and mean RPD = 1.82. ADF and EDOM were predicted with poor accuracy and similarly by both, PLS and RF. The bands located in the red-edge and NIR region showed high importance and stability to assess the best-predicted variables. Bands centred at 700, 710, 1160, 1170 and 1180 are highly stable and important to predict CP. The bands from the SWIR region had lower stability. This study provides insightful results on the use of hyperspectral data and future satellite missions such as CHIME to assess the pasture quality of Mediterranean grasslands that can be crucial to inform the management and monitoring of Mediterranean permanent grasslands.
查看更多>>摘要：? 2021 Elsevier B.V.Since the end of the 20th century, bees are suffering from increasing stress factors, leading domesticated colonies to die or at least be less productive. Precision beekeeping (PB) is an emerging field of agriculture that aims at protecting bees, supporting beekeepers, and optimizing apiary production thanks to digital infrastructures. The digitalization of apiculture first involves systems from the field of the Internet of Things (IoT), with the development of sensors to collect and transfer bee-related data. Then, data analysis comes into play, providing models that connect the data with the biological states of beehives, sometimes thanks to artificial intelligence (AI). In this paper, we describe the recent advances in precision beekeeping as systems and as services. Different types of sensors, networks, and power sources in PB are covered. The collection and use of data are described, and the performances of PB services are assessed. We also estimate the sustainability of the proposed solutions, taking into account their scalability, efficiency, and economic cost, because beekeepers need deployable research results.
查看更多>>摘要：? 2021 Elsevier B.V.Integrated mixed crop-livestock farming systems help improve farm sustainability by securing agricultural incomes through the diversification of productions and by enhancing farm autonomy regarding agricultural inputs. Based on interactions between crop and livestock productions within farms, such systems are complex to manage and to model. A one-to-one support methodology was developed to help farmers in their strategic thinking regarding the future of their farms in a redesign perspective. This methodology includes a three-step scenario process and is based on a spreadsheet simulation tool called CLIFS (Crop LIvestock Farm Simulator). CLIFS makes it possible to build scenarios of the evolution of a farm and assess them ex-ante by calculating several balances at the farm level (staple food, forage, manure) and their effects on the farm's economic results. The support process has been tested in several African and South American contexts and with French suckling cattle farms. The diversity of production contexts and issues addressed during the design process led to the development of a generic tool that can be applied easily to a large range of situations. A detailed description of the approach and the tool, with an illustration based on a Malagasy dairy farm, are presented here. Farmers appreciate the support process because it addresses their own questions within the context of their own farms. The process must now be transferred to advisory structures to assess its relevance in a professional context.
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