The challenges posed by global broadacre crops in delivering smart agri-robotic solutions: A fundamental rethink is required

Research output: Contribution to journalArticle

  • External authors:
  • Tom Duckett
  • Martin Collison
  • Lesley Boyd
  • Jon West
  • Simon Pearson

Abstract

Threats to global food security from multiple sources, such as population growth, ageing farming populations, meat consumption trends, climate-change effects on abiotic and biotic stresses, the environmental impacts of agriculture are well publicised. In addition, with ever increasing tolerance of pest, diseases and weeds there is growing pressure on traditional crop genetic and protective chemistry technologies of the ‘Green Revolution’. To ease the burden of these challenges, there has been a move to automate and robotise aspects of the farming process. This drive has focussed typically on higher value sectors, such as horticulture and viticulture, that have relied on seasonal manual labour to maintain produce supply. In developed economies, and increasingly developing nations, pressure on labour supply has become unsustainable and forced the need for greater mechanisation and higher labour productivity. This paper creates the case that for broadacre crops, such as cereals, a wholly new approach is necessary, requiring the establishment of an integrated biology & physical engineering infrastructure, which can work in harmony with current breeding, chemistry and agronomic solutions. For broadacre crops the driving pressure is to sustainably intensify production; increase yields and/or productivity whilst reducing environmental impact. Additionally, our limited understanding of the complex interactions between the variations in pests, weeds, pathogens, soils, water, environment and crops is inhibiting growth in resource productivity and creating yield gaps. We argue that for agriculture to deliver knowledge based sustainable intensification requires a new generation of Smart Technologies, which combine sensors and robotics with localised and/or cloud based Artificial Intelligence (AI).

Bibliographical metadata

Original languageEnglish
Pages (from-to)116-124
Number of pages9
JournalGlobal Food Security
Volume23
Early online date3 May 2019
DOIs
Publication statusE-pub ahead of print - 3 May 2019