From those who are involved in cotton growing to those involved in shipping it, all our cotton industry businesses are generating a wealth of information and data. CRDC is simplifying the path to harnessing the value of this information, helping those who create it to realise its true value.
CRDC is progressing plans to create a safe, useful and world-leading data platform for the Australian cotton industry and its information. In this issue of Spotlight, we focus on the start of the chain, the crop growing stage, and how crop managers, be it growers, farm managers or agronomists, can prepare to harness the potential of their data on-farm.
Firstly, a recap on what the data platform is and why it’s being developed by CRDC, led by CRDC General Manager, Innovation, Dr Meredith (Merry) Conaty and a committee of people from across the industry, including growers and consultants.
What’s a platform?
No longer just where we wait for a train. A data platform is a technology solution that enables the collection, storage, cleaning, transformation, analysis and governance of data. Data platforms can include both hardware and software to make it easier for businesses to use their data to improve decision-making and operations.
Many businesses today already rely on platforms with complex data pipelines, which draw raw data from various sources to support data analytics and data-driven decisions. A modern data platform provides the tools that users need to safeguard data quality and unlock the value of their data. Specifically, data platforms can help identify actionable insights, reduce data silos, enable self-service analytics for crop managers, streamline automation and power artificial intelligence applications.
A data platform incorporates data storage and processing, which includes the functions:
data ingestion, the process of collecting and importing data files from various sources into a database for storage, processing and analysis, with the aim of cleaning and storing data in an accessible and consistent central repository to prepare it for use; and
data transformation, a critical part of the data integration process in which raw data is converted into a unified format or structure. Data transformation ensures compatibility with target systems and enhances data quality and usability.
The cotton industry platform will contain both these functions.
As a crop manager, why use it?
The platform is being created so crop managers can get the most value from the vast amount of data they are creating and collecting (either intentionally or unintentionally) through their daily business operations. It will make the task of emission reporting/credentialing automated and streamlined. CRDC will build and remain the ‘owner’ of the platform, so it can’t be sold to larger entities or go out of the hands of the Australian cotton industry. Automation of data delivery from other platforms that crop managers use means it won’t add another task or complexity to the user.
How does it differ from platforms I’m already using?
It’s an industry-wide data platform where on-farm data can be automatically sent, analysed and returned with the results only accessible to the owner of the data. Unlike other platforms, the cotton industry platform will connect the entire supply chain (including ginners and shippers) and so create more opportunities for leveraging farm data to create value for growers down the value chain. It will focus on actual completed operations or tasks, as opposed to recommendations.
The platform will have processing and data handling capabilities that may currently be inaccessible to many growers. By standardising data language from different sources (data transformation) the platform can correctly aggregate it. You’ll be able to layer your Greenstar over your variable fertiliser maps, weather conditions, irrigation timing and whatever data you choose to collect.
How to get on board to ride the data train
As the old saying goes, “garbage in, garbage out” so firstly, make sure the data you collect is quality ‘clean’ data and automate or digitise files. Regardless of whether crop managers choose to use the platform or not, to make the most of their data, as with everything, quality is paramount.
Data quality is critical to all data governance initiatives in a business. Data quality measures how well a dataset meets criteria for accuracy, completeness, validity, consistency, uniqueness, timeliness and fitness for purpose.
Data quality standards ensure that businesses are making data-driven decisions to meet their goals. If data issues – such as duplicate data, missing values, outliers – aren’t properly addressed, businesses increase their risk for negative business outcomes. According to a recent global report, poor data quality costs organisations in the US an average of US$12.9 million each year.
Crop Consultants Australia (CCA) have highlighted the importance of data quality in recent editions of Spotlight.
“Most Australian cotton farms will have already accumulated their own extensive sets of data,” CCA’s Leisl Coggan said.
“The challenge for growers and managers is to ensure that data set is as accurate (or ‘clean’) as it could be, and just as importantly, that they make the most of that data and the story that data tells.
“Farm data has long been used for benchmarking seasonal performance on many levels, particularly production and economics, and it’s evident that this data is becoming even more crucial as growers and the industry are called upon to demonstrate accountability and improvement in sustainability.
“For more than 30 years, CCA has been collating data from Australian cotton farms on behalf of CRDC to track the progress of our evolving industry.
“It’s this data that has proven vital in conveying the industry’s improvements from water efficiency to pesticide and herbicide usage.
“Without this hard data, the Australian cotton industry would find it difficult to prove its commitment to continual improvement and demonstrate its social licence to farm.
“Data-driven agriculture is a reality. All growers should be using their data, not just to understand where they have been, but to plan for the future.”
CCA canvassed its members for their tips to ensure that the value of on-farm data can be realised. Here are the top 10:
- Regardless of the data storage system that you use, take some time to do some training and upskilling. This will minimise mistakes and maximise the benefits that the software will bring to your enterprise. One hour of online training may save you hours over the season and produce end figures that you didn’t think possible.
- Make sure that you record every important item – every operation, every application and every detail even if it seems minor at the time.
- Have a consistent system for data entry especially when there are two or more people entering data for one enterprise. Communication is key here to avoiding double entries or missing entries entirely.
- Double check the units that you are entering every time. This is particularly applicable to product rates where it is easy to make typo mistakes in data entry.
- Choose the correct brand and name of the product applied (not just recommended). Active loadings differ between products and accuracy is key.
- Make use of activity description fields in your operations. This may be an optional field, but additional information may give clarity to someone trying to explain an anomaly in data or understand the intention behind a management decision. This detail for example will enable the user to understand that they are looking at a replant situation, rather than a double-up.
- Always input the data assuming that you are not the end user. That way you will input the information required for the data to ‘stand-alone’ without your input or explanation.
- Run a quick comparison of your data with that from prior years to see if there are any obvious differences. If it looks ‘wrong’, chances are that it could be.
- Back up your data. Check the backup protocols of any online storage platform, but also make sure that data stored locally is backed up adequately. Your data is valuable.
- From CCA Director and digital ag consultant Sally Poole (who is completing a PhD in digital agriculture): never delete a data set just because it doesn’t look ‘right’ or it represents an abnormal production year.
“Just because a data set looks out of place doesn’t mean that it doesn’t belong and isn’t useful in looking at the bigger picture of what is happening in the field,” Sally said.
“Those years that aren’t ‘normal’ are part of farming, and we need to make sure that they are included.”
As the complexity of data collection, its ownership and its interpretation becoming ever increasing, it can become overwhelming for growers.
“It is also easy to dismiss new opportunities believing that they are not within our economic reach or personal ability to interpret,” Liesl said.
“This is where your consultant can assist: they have the skills and expertise to assist you collate that data that is ready on hand, assess your gaps in data collection and collation, and integrate the application of your data into your future planning.
“Gone are the days when your consultant only provides agronomic advice and you may be surprised by the suggested small changes, that will make all the difference to your next crop.”
For more
Dr Merry Conaty
[email protected]
This article appears courtesy of the Cotton Research and Development Corporation (CRDC). It was published in the (Winter 2025) edition of CRDC’s Spotlight magazine: www.crdc.com.au/spotlight
