看国外 | 五步法获取猪场大数据

看国外 2019-05-13 09:23:34

A new study on precision farming has demonstrated the importance of collecting big data on swine farms, having those transformed into decision making tools and thus maximising profitability. Essentially, such a management system needs to be developed in 5 steps.


The study was recently published in the scientific publication Animal Frontiers, a journal of the American Society of Animal Science. The article was authored by a range of pig experts from Spain, Ireland and Japan.


In the article, the authors explain that key in these developments are new technologies such as electronic feeders and artificial intelligence systems capturing big data will provide a better understanding of animal requirements and behaviour, increasing efficiency and sustainability.



Big Data can be of great value for swine producers. Photo: Shutterstock


In addition, biosecurity can be improved using tracking devices for farm staff, recording movements real-time to decrease disease risks and consequently, improve health and productive performance.


No strong farm analysis purpose


The authors explain that most of the data used by farmers have been related to the management of farm tasks, but not too much for analysis purposes. Most of them related to sow reproductive data or basic production summaries. Integration of data from different sources, think of slaughterhouse, lab, reproduction, health, or medicine use, was difficult and rare, according to the authors. And on top of that, there were few data support services assisting swine producers to get any further.


Examples of using data in arable farming has shown that it is possible, the authors wrote. Ideally, such a management system should consist of 5 steps:


1 Data collection

The authors wrote that data are the raw material of the system and can come from human inputs or sensor-robots. Until now, data consisted only of numbers, but the sector is coming closer to the use of images and sounds.

1 数据采集


2 Data processing

Data processing is related to the manipulation of data, including several tasks such as validation, sorting or aggregation, management of outliers and missing data. The objective is the correct set-up of databases that allows proper information generation, overcoming interoperability problems.

2 数据处理


3 Reporting

From sow cards or working lists up to multivariate regression analysis to define the optimum value for a certain key performance indicator, every farm or company must decide the information needed from every work level, not forgetting that this could be either technical, economical, or a combination of the 2.
3 数据报告

4 Distribution

The objective of this step is sending the right information to the right person at the right time. User preferences must also be considered and can include various types.

4 数据分配


5 Analytics and decision making

Information must be readable and understood by the recipient, and the recipient must have sufficient time to make key decisions. Until now, analytics were aimed at being mainly explanatory, but due to the amount of quality data available, predictive analytics is becoming a key step.

5 数据分析及决策


The authors mentioned much technology which can help acquire and interpret data. They mentioned for instance:


Data collection performed by robots and sensors


This technology includes a range of technology that can measure, observe and interpret pig and sow behaviour. Some are well-known, others are brand new. Think of:


Oestrus behaviour: PigWatch, by Canadian company Ro-Main is a computerised artificial insemination management system designed to predict the best time to inseminate recently weaned sows. It consists of motion sensors installed on the top of every stall in the breeding area, a data analysis module and a software user interface.


Eating behaviour in gestating sows: This behaviour is usually monitored using an ear transponder with radio frequency identification (RFID) that identifies the individual animal at each visit to the feeder.


Eating behaviour in lactating sows: Similar electronic sow feeder systems are also available for lactating sows, which are individually housed. New options allowing the sow to choose how much and when to eat have recently arrived at the market (Gestal Solo, Jyga Technologies), thus enabling the farmer to know the lactation intake pattern. ESF systems are also available for grow-finishing pigs.

哺乳期母猪的进食行为:类似的电子喂猪系统也可用于单独饲养的哺乳期母猪。最近市场上出现了允许母猪选择吃多少和什么时候吃的新产品(Gestal Solo, Jyga Technologies),养猪户因而有机会了解哺乳期的饲喂模式。电子母猪饲喂(ESF)系统也可用于生长肥育猪。

Early disease detection based on image analytics: A motion-based video system for early disease detection has recently been described.


Environment-oriented data


Thanks to the development of new technologies, farmers are now able to continuously monitor, air quality, temperature, and humidity in real time via sensors. Recently, EU-funded ProHealth project showed how big data could be used to fight diseases.


Real-time biosecurity control


Models to assess biosecurity are based on scoring systems or survey forms. A new approach addresses biosecurity is the use of real-time devices (B-eSecure System) to control the internal movement of farm staff.


The article was written by Carlos Piñeiro, Maria Aparicio, Joaquín Morales and María Rodríguez, PigChamp Pro Europa, Spain; Edgar García Manzanilla, Teagasc, Ireland; Yuzo Koketsu, Meiji University, Japan.

这篇文章是由西班牙的Carlos Pineiro、Maria Aparicio、Joaquin Morales、Maria Rodriguez、PigChamp Pro Europa;爱尔兰的Edgar García Manzanilla,、Teagasc,以及日本明治大学的Yuzo Koketsu共同撰写而成。


来源:Pig Progress