Environment and knowledge

Business intelligence - system

A system for connecting farms: XFarm

In 2017, Matteo Vanotti was looking for a technological solution to manage his family farm. Together with the other co-founders of xFarm Technologies, a platform tailored to his needs was developed and now in more than 100 countries around the world.

American-style software didn't fit the needs of small European farms, and local suppliers were unintuitive and very limited. So he and the other co-founders of xFarm Technologies developed a platform tailored to his needs. The aim of the platform is to provide innovative tools that can support farmers and stakeholders in managing their business. The platform is both
web and app-based and self-instructional. The platform will help the farmer and any employees to organise their work in an easy and efficient way. One area of use is how the farm can save on resources.

Via sensors and satellites, it is possible to obtain information and support in optimising irrigation, defence and fertilisation. Another area of use is the monitoring of fields and fields, where the support concerns the optimisation and development of an irrigation strategy, the protection of crops and the management of agricultural machinery. Overall, xFarm is a simple and user-friendly platform to monitor and improve the sustainability of a farm.

xFarm Technologies currently supports the work of 300,000 farms, belonging to more than 50 supply chains and located on 3 million hectares in more than 100 countries around the world. They sell their services to a variety of audiences such as agribusinesses, machinery manufacturers, contractors, co-operatives, input producers, agronomists, insurance and banks. These include farm management applications, connected sensors, support for digital transformation initiatives, agricultural algorithms and specialised training for the whole sector.

xfarm
xfarm

Product information

Name of product or concept: xFarm Connect and xFarm Analytics
Company or other organisation: xFarm
Category: Connected farm
Observers: Per Frankelius and Sofia Nyström

Business intelligence products

Farm laboratory

An automated system for soil sampling and analysis of soil samples. The cloud-based software integrates sampling, mapping and analysis in a single plattform.

Radicle Agronomics is an automatic system for soil sampling and analysis of soil samples. The soil is collected manually by a person driving e.g. a quad bike and placed in round plastic containers equipped with RFID tags by a special equipment mounted on the quad bike. The containers are automatically tagged with coordinates. No labels or handling of sampling bags or paper boxes are needed.


In a mobile soil laboratory of only 3x3 meters, named Radicle Lab, the analyses are then completed, fully automatically. In addition to P, K and pH, the lab also handles magnesium, calcium, cation exchange capacity (CEC) and base saturation level. Nitrogen, however, is not included. The cloud-based software integrates sampling, mapping and analysis in a single platform. The target audience is said to be agronomists who want to deliver better nutrient management recommendations as well as end-users, farmers.

The capacity is 200 samples per day. The business model is a combination of leasing ($13,000 USD per year) and cost per sample ($5.50). The concept was tested in 2022 and presented at Agritechnica 2023. No one in Sweden has yet tested the concept. The quality of the analyses is still unknown, but the company says that they have methods for calibration and points out that quality is also about taking many samples and preferably more often than is usually the case with regular soil sampling. Precision Planting is based in Tremont, Illinois, USA.
Radicale Agronomics
Radicale Agronomics

Product information

Name of product or concept: Radicle Agronomics
Company or other operator: Precision Planting LLC
Category: Crop production, digital support for soil sampling
Source: www.precisionplanting.com

Business intelligence products

System for continuous control of silo contents

By attaching a sensor and transmitter to one of the legs of the container, the Binconnect system can calculate how much content there is in kilograms in the silo and forecast when it is expected to be empty.

Binconnect is a system for continuous monitoring of silo contents. The installation does not require extensive intervention in the silo, but simply attaches a sensor and transmitter to one of the legs of the container. This then senses the strain in the metal and calculates how much content there is in kilograms and gives a forecast for when it is expected to be empty. You can monitor this via the web or app, and you can also connect your feed supplier to the system, or place orders directly in the app.

The price is around SEK 16500 and includes 5 years of service and subscription. The calibration is done by mounting the sensor on the leg of the silo, preferably when the silo is empty or as close to zero as possible. It must be there for at least 24 hours for zero mapping. Then you fill up with feed from a truck with known weight according to the consignment note. This is registered by the system and you get an initial weight check. The next time you fill after a completely empty silo, you calibrate again. The more times you do this, the better it gets.
BinConnect
BinConnect

Product information

Name of product or concept: Binconnect
Company or other operator: RAIS AB (Rongers Agro & Industry Service)
Category: Silo control
Date of reporting of observation: 2014-06-14

Sources: Personal communication with Robrt Robertsson and Anders Thorstensson, RAIS AB
Observer: Per Frankelius, Linköping University

Products in pig production

Pigsty

RFID-readers

Electronic ear tag readers are used to facilitate the identification and counting of animals in an efficient and reliable manner. These readers come in two main types: handheld and stationary.

Pig snorkellers

Eating time management

A growing number of wet feed suppliers now offer advanced systems that integrate sensors to monitor and measure pig appetite.

Pig in a yard

Digital pig counter

With a pig counter, pig farmers can count pigs of all sizes and colours with a very high accuracy. This is done with a camera that is mounted where pigs pass during a move, for example in a corridor.

Products in sheep production

Sheep in group, out to pasture

Change in activity

Motion sensors on the collar, in the rumen or around the sheep's legs can provide valuable information on the animals activity and behaviour, making it easier to diseases, injuries or predator attacks.

Close up on a sheep

automatic weighing

Automatic weighing of animals provides valuable information on growth, pasture quality and animal health without requiring much labour.

Sheep grazing

digital grazing measurement

Measuring pasture growth is crucial or predictability in pasture-based production. Traditional pasture meters can be complemented by apps like Aimer farming.

Products in nut production

Cows on summer grazing

Growing food bacteria on farm with AI

The Bacticam technology provides a clear overview of the presence of bacteria at both herd and individual level, which simplifies preventive animal health programmes on the farm.

Close-up of a cow

Grazing Scanner

Regular use of grazing scanners improves the possibility of having grazing strategies adapted to the needs of the animals, such as growth and milk production.

Cows grazing in the distance

Monitoring of animals

The technology of GPS monitoring of grazing animals has enormous potential to more effectively monitor the position and health status of animals.

Research endeavours

Gigacow

Can genomic selection help dairy cows cope with warmer temperatures? By integrating data from dairy farms, Växa Kokontrollen and Nordic Breeding Evaluation, SLU's cow data infrastructure, Gigacow, creates new opportunities for research on heat stress in cows.

The variation in heat tolerance in cows is large and varies from farm to farm. The most sensitive cows start to react already when the external temperature exceeds 15ºC, which is reflected, among other things, by a decrease in their milk production likely due to a reduced feed intake. The results come from the project ‘From sensitive to robust athlete - can genomic selection help dairy cows face warmer temperatures?’ and are a continuation of previous research from SLU which reported that a 7-day average of daily maximum temperatures above 20ºC was associated with sharp declines in milk production.

Another recently published study in the project led by Lena-Mari Tamminen at SLU also shows that fertility is often de-prioritised by dairy farmers in favour of feed production. This neglect is problematic, especially as extended calving intervals and keeping older cows can increase the risk of heat stress and mastitis. The research emphasises the need for greater awareness of uneven calving patterns and the long-term effects of heat stress. In addition, cooling systems in barns need to be re-evaluated. This could involve redesigning existing and future barns to provide a more efficient cooling system, e.g. by utilising cross draughts, fans and sprinklers in the barns, to mitigate the increasing challenges of heat stress.

Part of the project supported by SLU Gigacow is to evaluate breeding objectives to manage heat stress in cows and the possibility to select animals with higher heat tolerance, improved thermoregulation and/or reproductive performance under high temperatures. By taking heat stress into account in breeding selection, it would be possible to obtain a genetic advance that means production, fertility and health remain stable even in heat-stressed environments, which will become more common with a warmer climate.

Global methane hub and Nordic work to reduce methane emissions from cows

According to the Global Methane Hub, global methane emissions will increase by 35% by 2030 and by 50% by 2050 compared to 2010 levels. The scientific part of coordinating efforts to reduce emissions from livestock is led by Wageningen University. Work is currently underway to allocate donated research funds to strengthen existing projects in the sector. In August, the Global Methane Hub presented a strategy to reduce emissions from ruminant digestion.

In Sweden, close co-operation is underway between Växa Sverige and SLU in order to prepare our participation in the Nordic breeding work. SLU's infrastructure for cow data, Gigacow, will form the technical backbone for collecting data that will then be analysed in collaboration between researchers at Växa Sverige and SLU. Measuring methane gas emissions from a cow is complex and can be done in three ways. With respiration chambers where the cow is confined for a period of time and the exhaled air is measured, Greenfeeds where cows are lured with concentrated feed and the exhaled air is measured in a controlled air flow and ‘sniffers’ are installed in the feed trough of a milking robot which then measures the exhaled air. SLU has a long history of research in this area and has contributed to the validation of the methods used in the research.

DKK 518 million in funding to reduce methane gas emissions

In Denmark, the government has invested DKK 518 million to fund the reduction of methane emissions through the use of feed additives. In the Nordic breeding work, the aim is to be able to implement low methane production as a breeding goal using cost-effective measurement tools. SimpleScan from C-Lock and MooLoggers from Tecnosens are the market leaders in ‘sniffers’, which is the technology deemed cost-effective enough to measure methane emissions from enough animals to be used in a breeding programme. This will be used in combination with calculated values from milk spectra calibrated with data from sniffers or Greenfeeds. To finance the purchase and installation of equipment in Sweden, researchers at SLU and Växa Sverige have written several research applications that are under review. The Swedish Board of Agriculture has also funded adaptations of SLU Gigacow to support the project.

Technically, Växa Sverige staff will install equipment and move it between farms, while SLU Gigacow is responsible for data collection and storing data that is then analysed by researchers at Växa and SLU. Since a sniffer cannot itself identify which cow is breathing on it, data collection from the sniffer needs to be synchronised with registrations in the milk robot. This will be done in SLU Gigacow based on a model developed at Aarhus University. At the Nordic level, a research application to the Global Methane Hub is currently being processed, focusing in particular on the red breeds, VikingRed and Norwegian red cattle. In this work, Växa Sverige, SLU, Luke (Finland), Aarhus University (Denmark), Norwegian University of Life Sciences (Norway), Viking Genetics (Denmark) and Geno (Norway) will collaborate to collect and analyse data and share it with colleagues at Scotland's Rural College (Scotland), University of Guelph and Lactanet.
Collage for Gigacow, over Lövstad
Picture: Per Frankelius

The report focused on 7 focus areas:

  • Inhibitors - Feed additives that inhibit methanogenesis or the microbes that produce methane.
  • Genetics - Breeding programmes to develop low-emitting animals.
  • Measurement tools - Develop cost-effective tools that measure animal methane emissions.
  • Vaccines - Causing the animal's immune system to produce antibodies that suppress methane production.
  • Anti-methanogenic feeds - Feeds and forages that contain compounds that reduce methane production.
  • Rumen microbiome - Explore the microbes and processes that occur within the rumen ecosystem.
  • Physiology and behaviour - Understand the impact of animal behaviour and physiology on the rumen microbial ecosystem.

Source

Research endeavours

VallOptimal - Direct analysis of the wheat both before and after harvest

VallOptimal is a project run by SLU and Växa Sverige with the aim of investigating whether handheld spectrometer can be used for reliable determination of feed quality, funded by the Seydlitz MP Foundation. The project consisted of two parts with measurements in growing grass and in finished silage.

Before harvest

Handheld spectrometers with NIR technology (e.g. Yara N-sensor) measure reflections from the crop in the near-infrared part of the light spectrum. This can provide information on stand characteristics. This technology has been shown to be able to predict nutrient quality and crop yield and can be a good complement to current tools such as Vallprognos.se. The latter forecasts are based on sample clippings in the wheat and temperature totals, a model that can only be used for first harvest. There is a need to be able to determine the optimal harvest time also in later harvests. In addition, it takes a few days before the results of the analyses of the test cuts are available. With a portable meter, you get the answer directly in the field.

In the project, data from several years and locations across the country have been collected in growing grassland before three harvests, both through measurements with handheld Yara N-sensor and through chemical analyses of cut reference samples. Yield, crude protein, dry matter, fibre (NDF), digestibility and energy content were measured. Data from the spectrometer were compared with the chemical analyses and used to create statistical models using machine learning (a type of AI). The results showed good agreement between field scans and lab results. Thus, there is great potential for handheld spectrometers to contribute to effective estimates of nutrient quality and crop quantity. However, there is a future need for sensors for growing grasses at an affordable price that is not dependent on weather and the position of the sun.

After harvest

Hand-held scanners with NIR technology were also used here, but the measurements were made on silage. Some of the silage samples were taken in co-operation with a project funded by Nötkreatursstiftelsen Skaraborg. Calibrations were done in a similar way to pre-harvest, using data from scans and chemical analyses of the same silage samples to develop computational models using machine learning. A handheld meter (in this case a NeoSpectra scanner) can deliver reliable results on forage quality in the silage directly on farm instead of having to wait for analysis results from the laboratory. Dry matter, NDF, digestibility and crude protein were measured with good precision.
VallOptimal

Product information

Name of product or concept: VallOptimal
Company or other organisation: SLU and Växa Sverige
Category: Crop production and feed
Observers: Camilla Oskarsson, Växa Sverige and Johanna Karlsson, Växa Sverige

Date of observation: 7 November 2024

Source