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Assessment of Black Rot in Oilseed Rape Grown under Climate Change Conditions Using Biochemical Methods and Computer

Mónica Pineda1, Matilde Barón1

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Global warming accelerates disease symptoms in oilseed rape, causing earlier onset and worsening leaf senescence. Advanced imaging techniques accurately detect bacterial infections in plants before symptoms appear.

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Area of Science:

  • Plant pathology
  • Climate change biology
  • Agricultural science

Background:

  • Global warming presents challenges for plant-pathogen interactions, necessitating adaptation to changing environmental conditions.
  • Oilseed rape and *Xanthomonas campestris* pv. *campestris* (Xcc) interactions were studied under various climatic conditions to predict future climate impacts.
  • Xcc races 1 and 4 exhibited similar symptoms, but bacterial counts varied, indicating race-specific responses.

Purpose of the Study:

  • To investigate the impact of climate change on oilseed rape and *Xanthomonas campestris* pv. *campestris* (Xcc) interactions.
  • To understand how climate change affects the onset and severity of Xcc symptoms in oilseed rape.
  • To develop early detection methods for Xcc-infected oilseed rape plants under different climatic scenarios.

Main Methods:

  • Assessed symptoms and bacterial counts of oilseed rape infected with Xcc races 1 and 4 under simulated climate change conditions.
  • Monitored pigment composition and oxidative stress markers in response to climate change and Xcc infection.
  • Employed green fluorescence imaging, vegetation indices, and thermography on symptomless leaves to train classification algorithms for early Xcc detection.

Main Results:

  • Climate change accelerated Xcc symptom onset by at least 3 days, linked to oxidative stress and altered pigment composition.
  • Xcc infection exacerbated climate change-induced leaf senescence.
  • Classification algorithms achieved accuracies above 0.85 for early Xcc detection, with k-nearest neighbor and support vector machines showing superior performance.

Conclusions:

  • Climate change significantly impacts oilseed rape-pathogen interactions, leading to earlier disease manifestation and increased plant stress.
  • Early detection of Xcc infection in oilseed rape is feasible using non-invasive imaging techniques and machine learning algorithms, even before visible symptoms emerge.
  • These findings provide valuable insights for developing disease management strategies for oilseed rape in a changing climate.