New Method for Early Detection of Tomato Diseases Using Israeli Technologies
Scientists from the Hebrew University of Jerusalem have developed an innovative method for diagnosing tomato diseases at early stages, allowing for the detection of diseases even before characteristic visual symptoms appear. This discovery opens new possibilities for preserving crops and enhancing the resilience of agricultural products.
This is reported by AgroReview
How the New Early Detection Method Works
Fusarium wilt, caused by the soil fungus Fusarium oxysporum, is one of the most dangerous diseases for tomatoes and other crops, leading to significant economic losses. Traditional diagnostic methods are based on visual assessment of symptoms, which often delays response and causes considerable losses. The researchers applied modern technology to monitor water processes in plants, enabling the detection of signs of infection several days or weeks before the first symptoms appear.
According to a study published in the journal Plant Disease, specialists observed the rate of water evaporation and changes in plant biomass.
“This research shows that physiological signs related to water can serve as reliable early indicators of infection,” explained co-author Shani Friedman. “We were able to quantitatively measure how plants respond to the pathogen long before they exhibit traditional visible symptoms of disease.”
Advantages and Future Prospects
The new method not only allows for quick and accurate disease detection but also assesses the level of risk to plants. This provides farmers and researchers with specific numerical data regarding the aggressiveness of pathogens and the ability of different tomato varieties to resist disease. Co-author of the study, Professor Menachem Moshelion, noted that this approach can be applied to various agricultural crops: “Our method opens up broad opportunities for monitoring plants not only tomatoes but also other crops. Early disease detection through physiological monitoring can significantly reduce crop losses and enhance agricultural management efficiency.”
Currently, the research group has applied this method to monitor potato diseases, demonstrating its versatility and potential for widespread use in agriculture.