Hollobiont Revolution: How Wheat Becomes Climate-Sensitivity Through Nature-Based Plant Breeding and Machine Learning

Machine Learning


Newswise – Nitrogen fertilizers used in agriculture have contributed greatly to global warming. The new breeding concept, especially specifically for wheat, helps reduce nitrogen fertilization. This holobion principle places the complex interactions between plants and soil microbiome at the heart of plant reproduction. In combination with machine learning, this could lead to the use of new wheat varieties, like other crops that are resilient due to climate change and contribute to soil health. Two recent studies, led by Wolfram Weckwerth at the University of Vienna, have been published in the journal Plant Biotechnology and Plant Science Trends.

Enhanced agriculture is increasingly dependent on nitrogen (N) fertilizers to increase food and feed supply. However, more than half of the nitrogen is applied to the spraying site every year, which means it is lost in the air and water. Such losses lead to serious problems such as air and water pollution, soil acidification, climate change, stratospheric ozone depletion, and biodiversity losses. As a result, reducing nitrogen losses from farmland could potentially enhance economic returns by reducing fertilizer requirements, improving human health and ecosystem services, and contributing to climate change mitigation.

Hollobiont concept: Think of plants and microorganisms as units

Wolfram Weckwerth emphasizes that sustainable improvements in crop resilience and benefits should focus not only on plants, but also on the microbiota surrounding roots and leaves. Soil microbiota also provide opportunities to increase soil fertility and reduce dependence on synthetic fertilizers. He states: “Plant evolution is driven primarily by plant miclove interactions, but the ecology of plant holobionts is not well understood at the molecular level. However, these relationships retain great advantages for sustainable agriculture. Soils.”

Wheat as a natural way to slow down nitrogen losses.

In a recent study, the international team investigated the possibilities of various wheat cultivars that produce BNIs that help control the soil nitrification process. They found significant natural variation in BNI activity in different elite wheat lines.

“Analysis of root exudates of complex compounds released from the root system shows significant variation among wheat cultivars,” explains Arindam Ghatak, the first author of the study. “These exudates promote or inhibit specific microbiome compositions, allowing for the selection of strains that are particularly highly BNI active.” By cultivating these Bni-active lines, farmers were able to significantly reduce the need for nitrogen fertilizers in the future. This is an important step to mitigate the overall nitrogen cycle destruction caused by the overuse of artificial fertilizers.

Data-driven plant breeding for a sustainable future

To effectively utilize this nature-based solution, the Molecular Systems Biology (MOSYS) Lab at the University of Vienna and the team of scientists around Wolfram Weckwerth at Archaea Biology and Ecogenomics Lab have developed a new breeding concept. Supported by partner institutions in Greece, Australia, India, Japan, Canada, the US and Mexico, the team places the holobiont concept at the heart of modern plant reproduction, focusing on the complex interactions of plants and soil microbiota. Plant genetics, microbiome research, and panomimics are integrated through an innovative data-driven approach to generate high-throughput data.

“Combined with machine learning algorithms, this opens up a promising breeding platform, develops new crop varieties with high potential for BNI, increasing resilience to climate change and improving soil health,” explains Weckwerth. Therefore, the concept of holobiont marks a paradigm shift. It combines ecology, systems biology and breeding techniques, highlighting ecosystem interconnectivity and opening new pathways to resource-efficient, climate-resistant agriculture.





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