Advancing global food security by harnessing AI and 3D printing to combat hidden crop killers

The challenge of global food security is vast, but a significant part of it revolves around understanding and mitigating crop losses caused by pests and pathogens. Crop diseases and pests are major constraints, causing yield losses that can vary from small to total crop loss. These losses and their severity are due to sporadic incidences of pests and disease that ultimately can lead to severe food insecurity in some regions. Notably, there are “orphan diseases”, diseases that even though are important due to their effect on crop yield, are underappreciated, even by farmers. Among these, plant parasitic nematodes are a prime example and the subject of Dr Sebastian Eves-van den Akker’s research, head of the plant-parasitic interactions research group. These root-parasitic, soil-borne nematodes are challenging to detect and thus often overlooked by farmers and researchers, yet they significantly impact crop health by draining plant resources from within the roots.

Sebastian’s lab focusses on understanding and combating these hidden threats. One of the significant obstacles in this research field is phenotyping: determining the extent of nematode infection (i.e. how many nematodes are currently infecting a given plant?) and their effects on plants (i.e. how many nematodes will there be in the next generation?). Traditionally, this has been a painstaking manual process where researchers must physically look at plants and visually quantify whether a given plant is diseased at any specific point in time. To address this, Sebastian’s team developed a four-step process that allows researchers to (1) see the roots, (2) see the nematodes, (3) measure the number of nematodes present and (4) do this in tens of thousands of plants, in real-time and without using destructive processes. They developed an innovative, high-throughput phenotyping system using 3D printing and Artificial Intelligence (AI). This system allows the rapid visualisation and analysis of tens of thousands of plants (in only 3 hours), thus significantly accelerating the ability to study nematodes in situ.

The approach involves infecting the model plant Arabidopsis thaliana with beet cyst nematodes (Heterodera schachtii) and using the custom-designed machines to capture detailed images of infected roots. These images are then analysed using AI-driven software, developed in collaboration with Prof Ji Zhou’s labs at NIAB and Nanjing Agricultural University, which accurately counts nematodes and assesses various phenotypic traits such as size, shape, and colour. This non-destructive method allows the team to track the dynamics of nematode infections over time, providing a holistic view of the entire infection process.

One of the most significant findings from this study is the competitive interaction between nematodes, infecting the same root area. Contrary to the initial hypothesis that nematodes might assist each other, this study revealed that nematodes compete for resources, negatively impacting each other’s growth. This was further confirmed through extensive biological replicates, providing robust new insights into nematode behaviour.

This study is the largest nematode infection trial conducted to date, measuring millions of nematodes, infecting thousands of Arabidopsis plants (using a mapping population consisting of 550 different ecotypes or varieties of Arabidopsis), to map the genetic basis of nematode resistance. By correlating phenotypic data (size, shape, and colour) with genotypic information, specific regions of the Arabidopsis genome have been shown to be associated with resistance traits. This comprehensive genetic mapping is extremely important as it can inform the development of crop varieties with enhanced resistance to nematodes.

This type of innovative research underscores the importance of a dynamic approach to plant pathology, moving beyond static measurements to consider the growth rates and interactions of pathogens over time. By leveraging advanced technologies such as AI and 3D printing, the collaboration between researchers at The University of Cambridge and NIAB, joined at the Crop Science Centre, are not only uncovering new biological insights, but also paving the way for innovative crop protection strategies. This holistic and dynamic understanding of plant-nematode interactions holds promise for improving global food security by developing crops that can withstand these hidden, yet devastating pests.

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