Record Details

Future Farm project

CSIRO RDS Repository

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Title Future Farm project
 
Creator Rob Bramley
 
Subject Agricultural systems analysis and modelling
 
Description The Future Farm Project was established to re-examine and improve the way in which soil and crop sensors, supplemented by other sources of useful/available data, are used to inform decisions about input management and to provide a way of automating the process from data acquisition, through analysis, to the formulation and implementation of decision options. In particular, using nitrogen (N) fertilizer management as a ‘use-case’, the project sought to enable enhanced grower confidence in N decision making through the adaptive generation of site-specific management models. A key element of these is their increased and improved use of in-season field monitored data (soil, crop, climatic), historic on-farm data, external public and private data and automation of decision rules in software that may potentially be linked to real-time application equipment. This was considered important given the pre-project perception that a lack of farmer confidence in precision agriculture-based decision making was constraining adoption of precision agriculture (PA) approaches to management of grains-based farming systems. This lack of adoption was in spite of the potential of PA approaches as a counter to farm labour shortages, the need to optimise resource use efficiency as a means of maintaining or enhancing farm profitability and the finding through an exhaustive modelling exercise, that the error associated with prediction of N fertilizer requirement based on expected yield was of the order of 50 kg N/ha.
Future Farm was co-funded by GRDC and involved CSIRO (as lead research organisation) along with the University of Sydney, University of Southern Queensland, Queensland University of Technology and Agriculture Victoria.
The project made us of both 'core' and 'satellite' field sites across the major grain-growing regions; core sites were the major project resource, whereas satellite sites were those where we collaborated opportunistically with farmers running their own strip trials. The dataset comprises data collected in-field at these various sites (using soil and crop analysis or through the use of proximal crop or soil sensors) or acquired through remote sensing or from publicly available sources (eg weather data, soil information systems); historical data were also acquired. It also includes data gathered through the use of yield monitors and protein sensors on the farmers' harvesters. For the latter reason along with other privacy issues, access to the dataset is restricted.
Further information about Future Farm is available at https://grdc.com.au/resources-and-publications/grdc-update-papers/tab-content/grdc-update-papers/2022/02/better-targeted,-more-precise-fertiliser-decisions-as-a-counter-to-rising-fertiliser-prices-focussing-on-3-of-the-6-rs and on other relevant GRDC webpages.
Code is available at: https://bitbucket.csiro.au/projects/FUTUREFARM
 
Publisher CSIRO
 
Contributor Brett Whelan
André Colaço
Alison McCarthy
Jonathan Richetti
Roger Lawes
Mario Fajardo
Asher Bender
Glenn Fitzgerald
Peter Grace
 
Date 2023-04-11
 
Type —
 
Format —
 
Identifier csiro:57385
 
Language —
 
Coverage —
 
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