The production of milk in Lombardy towards digital and precision animal husbandry
Development of an analysis tool capable of generating summary information with which milk producers are able to improve the economic, environmental and social performance (including the quality of life in the workplace) of the farm. Specific objectives of the project are: 1. the enhancement of all the data generated by the software related to the different technologies present on the farm; 2. the identification of a series of indicators with which the milk producer is able to monitor the production and reproductive performance of the herd, environmental sustainability, the state of animal welfare and the company's economic performance.
Development of a digitalized monitoring system for economic, environmental and animal welfare management from the data and consequent information obtainable from the digital management systems of the detections made by sensors or other available data sources.
In the next few years, milk producers are called to improve the environmental sustainability of livestock and the welfare of animals, maintaining their competitiveness on the market through increasing technical and economic efficiency of production. Farmers must adapt to the consequences of climate change and mitigate the contribution of dairy cows to emissions of greenhouse gases and agents that alter the quality of air and water. The companies are equipped with sensors to measure the main microclimatic parameters (temperature and relative humidity of the air, wind speed); other technologies are designed to improve the feeding efficiency of the herd, such as automatic feeding systems (AFS) or ruminal activity detectors. Great relevance are also the milking technologies, which see more and more sophisticated and performing conventional milking parlors and the new frontiers of robotic milking (AMS). Many of these technologies are equipped with sensors connected to specific software provided by companies, which collect a huge amount of data (big data).
The data used for farm management are often a small part of the many data collected, so there is a risk of losing important information. There is no decision support system capable of highlighting the synergies and contradictions between the various sustainability (environmental, social, economic, etc.). There is a need for effective transmission of the most important information in order to make quick and targeted decisions. An efficient connection between the data collected by the different systems is missing.
Action 1 - A fact-finding survey at regional level on the spread of latest generation technologies in dairy farms and the degree of use of information by farmers. For the detection of the state of introduction of the innovations in support of precision animal husbandry for the management of the company, a survey questionnaire will be prepared on two levels: one to be administered by e-mail to as many Lombard breeders as possible (thanks to the address book ARAL), to create the widest possible "photograph" of the adoption of precision zootechnics in Lombardy; one more extensive, with structural and economic elements of the farms, on a sample planned through a stratification within all the breeders who will have responded to the first level, to reach a number of about 600 farmers distributed in representative measure in the various geographical areas present in Lombardy. This second level will include the registration, if already implemented, of the level of animal welfare assessed with at least one of the main methods of recognized validity at national level (Iba-CRPA, CReNBA-IZS).
"Action 2 - Analysis of data produced by software related to the technologies used. Sub-action 2.1 Characterization of the records. Within Action 2, the record structures used for corporate digitization will be characterized. We will verify the methods of digitization (automatic or through data entry) in order to assess its adequacy. The variables representing fixed factors (year, month, season, etc.) or random (cows, ...) will then be identified in order to perform multivariate statistical studies aimed at identifying the components of greatest informative interest in the characterization of the animal welfare, environmental sustainability and corporate profitability. Predictive models will be developed preferring general linear models. The characteristics of the digital reporting of each device will be assessed, also based on what is required in the implementation of Action 3 for the integrated management of information.
In each farm the possible interactions already present between the different devices will be assessed and valued (especially when supplied by the same company or in any case in a collaborative situation, such as that of the case of mixer wagons and in-line analysis systems of the foods to be loaded ). All data relating to the management of the herd will be collected in digital form, both generated within the company and from outside (for example, those of the functional controls)."
Action 2 - Analysis of data produced by software related to the technologies used. Sub-action 2.2 Environmental analysis. An initial environmental analysis of the farms participating in the project will be carried out. This analysis will be performed before the proposed innovations are introduced. The following year a second analysis will be performed, which will allow a first estimate of the reduction of the environmental impact. A third analysis will be carried out to estimate the effect at a stabilized situation. The analysis will be carried out by adopting the Life cycle assessment (LCA) approach which considers all inputs (such as purchased food, fuels, fertilizers) and all outputs (milk, meat, emissions into the atmosphere and in the waters). The primary data (under the control of the entrepreneur) will be collected through an interview with the breeders; the secondary ones will be obtained from specific databases or from bibliographical sources. The data will be processed with calculation tools dedicated to the livestock sector, such as LatteGHG (Pirlo and Carè, 2013) or CAP2ER® of IDELE. The categories of impact considered will be: global warming, acidification, eutrophication, energy consumption. Given that the productive (Pirlo and Lolli, 2018) and reproductive (Zehetmeier et al., 2014) performances are among the main drivers of the environmental impact, the regressions between the environmental performances and the productive and reproductive indices obtainable from the dashboard of the farms.
Action 2 - Analysis of data produced by software related to the technologies used. Sub-action 2.3 Evaluation of animal welfare. In the project companies the evaluation of animal welfare will be carried out using the IBA 2.0 model of the FCSR. The parameters of this evaluation system concern both indirect measurements relating to management, structural and housing aspects, and direct measurements on all bovine categories for a total of 280 parameters. Specifically, these are: 1. analysis of direct measurements on animals (body condition score, time to go to bed, body soiling condition, lameness score, changes in the integument, coughs, nasal, ocular and vulvar drains, difficult breathing, diarrhea, mutilations, approach tests, qualitative assessment of behavior). 2. analysis of indirect measurements on usable breeding structures (construction characteristics of the barn, type of housing, housing surfaces, dimensional parameters of the bunks and of the housing races, flooring and bedding materials, food and drinking water, natural ventilation, dust and the presence of harmful gases, summer rescue systems against the heat, presence of external operating areas, milking and automated herd management systems); 3. analysis of the measurements on the usable management and health aspects (mastitis prevalence, foot lesions and other pathologies, quantity of milk produced, reproductive efficiency indices).
Action 2 - Analysis of data produced by software related to the technologies used. Sub-action 2.4 Economic evaluation. 2.4.1. Cost and benefit evaluation of new technologies. In the project companies the economic evaluation will be carried out using the Milk Money model of the FCSR. The following activities are foreseen: the following information is collected in each pilot company: use of agricultural land, consistency of the herd, sale of animal production, food rations, technical efficiency of the farm, types and surfaces of buildings used for the activity agricultural, types of machines used for agricultural activity and their value as new, work units present on the farm and their commitment on the farm, cash flows (income and monetary disbursements actually incurred by the agricultural entrepreneur); input of the collected data and calculation of the business costs of milk production through Milk Money, an internet service that offers the possibility to compare the indexes of one's own farm within a network of companies that, in an absolutely anonymous way, share the fundamental parameters of the production cost calculated with the same methodology. 2.4.2. Economic analysis on a larger sample of companies. To verify the results of the costs and benefits on a larger group of farms, a simulation is carried out on a stratified sample of 30 Lombard dairy farms, which are part of the group of 600 "second level" farmers foreseen in action 1 of the plan . Data is collected that feeds the Milk Money software for the purpose of calculating the production cost and profitability of the dairy farm.
Action 3 - Design and definition of the logics of the dashboard application system for farm management. PLF applied to animal husbandry is a technology that has great potential but still requires intense research and development before it can be fully used. In particular, many of the systems for the automatic detection of biological parameters on animals or the environment are characterized by ""closed"" commercial software that does not allow the breeder to add or manage additional sensors, except those of the manufacturer. This prevents the enhancement of all possible sources of information which, if they were truly integrated, could provide a more ""precise"" management of the company. The main objective of this action lies in this context, which consists in creating an ""open"" and modular dashboard capable of managing different sensors, produced by different commercial companies and capable of evolving with the arrival on the market of new technologies. Examples of free and modular platforms have already been successfully developed in other sectors.
To achieve this goal, CREA-ZA researchers, with the support of an engineering-IT profile figure acquired during the project, will create a database for the management and analysis of sensor data based on what has been collected in 2.1 which , starting from a common structure, it can be populated with the data of the partner companies and is able to return specific reports for the targeted needs of each farm.
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