Data collection and analysis is playing an increasing role in modern crop production. Farmers Weekly explores how a digital tool and expert-led training can help improve yields and cut waste in the fresh potato sector

The latest smart technology combined with the relevant grower training can help improve on-farm potato yields and cut waste in the supply chain, according to a recently completed research project.

Loss of “marketable yield”, or the amount of crop meeting the desired packer specification, is a big problem for the fresh potato sector.

When tubers fall out of spec due to size or having quality issues such as bad skin finish, there is a considerable cost to growers and others in the supply chain.

See also: How to stop sprouting in potato stores without CIPC

To find a solution to this problem, a trial was set up by retailer Asda’s Integrated Procurement & Logistics (IPL) fresh produce business, and sustainability experts Wrap.

It tracked a number of salad and fresh potato crops from 14 of IPL’s suppliers across East Anglia, from planting in spring 2017 through to harvest and storage into 2018.

Destined for Asda supermarkets, varieties included salad type Belana, along with pre-pack all-rounders Nectar and Maris Piper.

Inconsistent performance

The study uncovered significant inconsistencies between crop performance of the 14 participants, all of which are operating in the same region of the country.

The disparity was most marked in the salad crop Belana, where the highest total yield (recorded as all harvested tuber tonnage) was a massive 2.5 times the lowest total yield.

It is thought that this significant yield difference was down to the three-fold variation in tuber numbers, which is a key component of big marketable yields in salad crops.

For Belana, this saw the best-performing crop generate nearly £10,000/ha more revenue than the lowest.

For Nectar, although differences were less pronounced, variation was still £2,000/ha in some instances and based on an average field size of 10ha, the difference could be worth in the region of £100,000 and £20,000 respectively, in terms of revenue.

Farm-specific factors such as weather or soil type go some way towards explaining these differences.

However, as the growers were close geographically, Wrap believes the variation seen across crops points to widescale differences in productivity across the UK.

This is a problem for both farm profitability and for packers such as IPL, who require a predictable and consistent supply of quality potatoes to meet customer needs.

What solutions?

As part of the project, the 14 growers were provided with tools to help improve performance, including training sessions from NIAB’s Artis training platform on the following subjects:

• Improving potato yields and profitability by measuring and monitoring performance.
• Understanding and optimising potato nutrition.
• Scheduling irrigation to optimise yield and quality in potatoes.
• Understanding potato crop growth stages.

In addition, each was instructed to use potato agronomy research group Niab Cuf’s Potato Yield Model (PYM) to monitor crop performance.

The PYM has been available and used extensively in commercial situations for some time and sees growers enter basic setup information such as variety and geographical location.

Date of emergence is then inputted and canopy development monitored by uploading pictures to the platform via a smartphone app.

Finally, test digs are carried out 50 days post-emergence to establish tuber number, tuber size distribution and yield in each size grade.

The model then uses in-season and historical data from commercial crops to provide a forecast of total and graded yield up to 10 weeks before harvest. This aids earlier decisions around supply and demand, helping both the farmer and supply chain.

It also informs growers on when to destroy the crop canopy to maximise the number of tubers in the correct size grade for a specific contract.

Finally, the PYM allows for the evaluation of crop performance on key metrics such as stem counts, tuber population and crop canopy performance against a benchmark for specific varieties.

Did the solutions work?

Feedback from growers showed a 33% improvement in understanding of each subject area and 85% would make or consider changes to their practices after attending the Artis training sessions, with key areas including fertiliser application, seed rates and irrigation efficiency.

In addition, several meetings used the results from the PYM to drive a discussion on how crop performance could be improved in-season, and this proved fruitful for both growers and IPL.

When presented with clear metrics on each crop from the digital decision support tool, healthy debate and questioning about why variation had occurred quickly followed.

Although such discussion is useful to tweak in-season management, David Firman, head of Niab Cuf, believes the greatest benefit of using the PYM comes from its facilitation of year-on-year improvements as data builds over time.

“The discipline of accurately recording information enables fine-tuning of production practices, less waste and better achievement of marketable yield,” he adds.

Data quality

With growers extremely busy at times when key data are collected, the quality and quantity of information gathered on crop performance is an area of concern and was highlighted in the project.

At present, there is no substitute for getting out in the field with a fork and conducting test digs and Dr Firman says any tools which might increase the speed and accuracy of data gathering are welcome.

He is hopeful new digital imaging tools that can accurately count and size grade tubers will soon be available, but attempts so far have not been accurate enough for commercial success.

“In the future you can envisage robots going out to do the sampling, which is the ultimate aim. I don’t know how far away we are from that reality, but I’m sure it will happen.”

In the meantime, growers should implement defined protocols for gathering crop performance data and use more basic tools such as tablets or smartphones for recording the information.

“Be clear on your protocol, write it down and follow it each time, so you are always sampling in the same way. Also, get some advice from someone who has experience [in data collection],” notes Dr Firman.