Establishing methods for rapid and early detection of pathogen-infected crops is crucial to improve plant disease management and reduce crop loss.
Typically, plant disease diagnosis involves a simple visual inspection of plants for illness signs and intensity. It is more reliable than existing strategies as it enables accurate recognition and early detection of bacterial infection, both of which are crucial to conserving crop plants that would otherwise be ruined,” describes Gajendra Pratap Singh, scientific director and principal private investigator at DiSTAP and co-lead author.
“The outcomes revealed that the Raman spectroscopy-based method can swiftly detect and quantify natural immunity reaction in plants contaminated with bacterial pathogens. Scientists from MIT, TTL, Nanyang Technological University, and National University of Singapore are collaboratively establishing new tools for the continuous measurement of crucial plant metabolites and hormonal agents for novel discovery, deeper understanding and control of plant biosynthetic pathways in ways not yet possible, especially in the context of green leafy vegetables; leveraging these brand-new strategies to engineer plants with extremely desirable properties for global food security, including high-yield density production, and dry spell and pathogen resistance; and applying these technologies to improve city farming.
Due to the increasing demand for worldwide food supply and security, there is a growing need to improve farming production systems and increase crop productivity. Globally, bacterial pathogen infection in crop plants is one of the major factors to agricultural yield losses. Climate modification also contributes to the problem by accelerating the spread of plant illness. Developing methods for fast and early detection of pathogen-infected crops is essential to enhance plant disease management and lower crop loss.
The advancement by SMART and TLL researchers uses a faster and more accurate method to identify bacterial infection in crop plants at an earlier stage, as compared to existing methods. The new outcomes appear in a paper titled “Rapid detection and metrology of plant inherent resistance reaction using Raman spectroscopy” published in the journal Frontiers in Plant Science.
Campestris (Xcc)) in the leafy vegetable choy sum utilizing quantitative Raman spectroscopy-based algorithm. On the right, the Infection Response Index is revealed, which can aid farmers to determine infections and take action.
” The early detection of pathogen-infected crop plants is a significant action to enhance plant illness management,” says Chua Nam Hai, DiSTAP co-lead principal investigator, professor, TLL deputy chair, and co-corresponding author. “It will permit the selective and fast elimination of pathogen load and curb the additional spread of disease to other neighboring crops.”
Typically, plant disease medical diagnosis involves a basic visual assessment of plants for disease signs and seriousness. “Visual examination methods are often inadequate, as disease symptoms generally manifest only at reasonably later phases of infection, when the pathogen load is reparative and already high steps are restricted. New techniques are needed for quick and early detection of bacterial infection. The idea would be similar to having medical tests to identify human illness at an early stage, rather of waiting on visual symptoms to reveal, so that early intervention or treatment can be used,” says MIT Professor Rajeev Ram, who is a DiSTAP principal investigator and co-corresponding author on the paper.
While existing methods, such as existing molecular detection approaches, can detect bacterial infection in plants, they are typically restricted in their usage. Molecular detection methods mostly depend on the schedule of pathogen-specific gene series or antibodies to determine bacterial infection in crops; the implementation is nonadaptable and likewise lengthy for on-site field application due to the high expense and large devices required, making it not practical for usage in agricultural farms.
” At DiSTAP, we have established a quantitative Raman spectroscopy-based algorithm that can help farmers to determine bacterial infection rapidly. The developed diagnostic algorithm makes use of Raman spectral biomarkers and can be easily carried out in cloud-based computing and prediction platforms. It is more reliable than existing strategies as it enables accurate identification and early detection of bacterial infection, both of which are vital to conserving crop plants that would otherwise be ruined,” discusses Gajendra Pratap Singh, clinical director and primary detective at DiSTAP and co-lead author.
A portable Raman system can be utilized on farms and supplies farmers with a precise and easy yes-or-no reaction when utilized to evaluate for the presence of bacterial infections in crops. The development of this rapid and noninvasive approach could improve plant illness management and have a transformative influence on farming farms by efficiently reducing farming yield loss and increasing efficiency.
” Using the diagnostic algorithm approach, we experimented on numerous edible plants such as choy amount,” says DiSTAP and TLL principal detective and co-corresponding author Rajani Sarojam. “The outcomes revealed that the Raman spectroscopy-based approach can swiftly detect and measure innate immunity response in plants infected with bacterial pathogens. We believe that this innovation will be beneficial for farming farms to increase their productivity by reducing their yield loss due to plant illness.”
The scientists are presently dealing with the development of high-throughput, tailor-made portable or hand-held Raman spectrometers that will allow Raman spectral analysis to be rapidly and quickly performed on field-grown crops.
Recommendation: “Rapid Detection and Quantification of Plant Innate Immunity Response Using Raman Spectroscopy” by Pil Joong Chung, Gajendra P. Singh, Chung-Hao Huang, Sayuj Koyyappurath, Jun Sung Seo, Hui-Zhu Mao, Piyarut Diloknawarit, Rajeev J. Ram, Rajani Sarojam and Nam-Hai Chua, 21 October 2021, Frontiers in Plant Science.DOI: 10.3389/ fpls.2021.746586.
Wise and TLL established and found the diagnostic algorithm and Raman spectral biomarkers. TLL likewise validated the detection and validated method through mutant plants. The research study is brought out by SMART and supported by the National Research Foundation of Singapore under its Campus for Research Excellence And Technological Enterprise (CREATE) program.
The first entity in CREATE established by NRF, SMART serves as an intellectual and innovation center for research study interactions between MIT and Singapore, carrying out cutting-edge research projects in locations of interest to both Singapore and MIT. Wise research study is funded by the NRF under the CREATE program.
Led by Professor Michael Strano of MIT and Professor Chua Nam Hai of Temasek Lifesciences Laboratory, the DiSTAP program addresses deep problems in food production in Singapore and the world by developing a suite of impactful and unique analytical, genetic, and biomaterial innovations. The objective is to essentially alter how plant biosynthetic paths are found, kept an eye on, engineered, and eventually translated to fulfill the worldwide demand for food and nutrients. Researchers from MIT, TTL, Nanyang Technological University, and National University of Singapore are collaboratively developing brand-new tools for the constant measurement of important plant metabolites and hormones for unique discovery, deeper understanding and control of plant biosynthetic paths in ways not yet possible, especially in the context of green leafy vegetables; leveraging these brand-new methods to engineer plants with extremely preferable homes for worldwide food security, including high-yield density production, and dry spell and pathogen resistance; and applying these innovations to enhance metropolitan farming.
The Raman spectroscopy-based method enables early detection and quantification of pathogens in plants, to boost plant disease management.
Researchers from the Disruptive and Sustainable Technologies for Agricultural Precision (DiSTAP) Interdisciplinary Research Group (IRG) of Singapore-MIT Alliance for Research and Technology (SMART), MITs research study business in Singapore, and their regional partners from Temasek Life Sciences Laboratory (TLL), have actually established a rapid Raman spectroscopy-based method for finding and quantifying early bacterial infection in crops. The Raman spectral biomarkers and diagnostic algorithm allow the noninvasive and early diagnosis of bacterial infections in crop plants, which can be vital for the development of plant illness management and farming efficiency.