Summary of Assinatura espectral do nematoide da haste verde em soja

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In the YouTube video "Assinatura espectral do nematoide da haste verde em soja" (Spectral signature of the green stem nematode in soybean), a research project is presented to develop a methodology for identifying symptoms of the green stem nematode (GSN) in soybean using spectral radiometry. Funded by FAPemat, the project aims to create a method for identifying GSN symptoms and obtain a spectral signature through spectral radiometry. The project is significant for Brazil, the world's leading soybean producer, and Mato Grosso, its principal producer. GSN, caused by the nematode Aelenchthus coides, is a recent problem with potential losses reaching up to 100% in affected areas. The researchers believe that hyperspectral sensing could aid in identifying infested areas. The project was proposed by Embrapa Agrosilvopastoral in partnership with Embrapa Soja, Universidade do Estado do Mato Grosso, Nemate Campos, Sinop, and students from IFMT and UFMT. The results showed that using a spectroradiometer to capture spectral signatures in soybean plants yielded records of healthy and infested plants, with interference in foliar reflectance in relation to nematode inoculation levels. The next step is to refine this methodology to develop a sensor for direct monitoring of soybean fields. The project aims to disseminate results to the productive sector and generate scientific applications, with the participation of students being crucial. The speaker expresses gratitude to all partners for their collaboration.

• 00:00:00 In this section of the YouTube video titled "Assinatura espectral do nematoide da haste verde em soja" (Spectral signature of the green stem nematode in soybean), a project was presented to develop a methodology for identifying symptoms caused by the green stem nematode (GSN) in soybean using spectral radiometry. The project was funded by FAPemat in an edital specifically for women and girls in computing, engineering sciences, and agriculture. The objective was to create a method for identifying GSN symptoms and obtain a spectral signature through spectral radiometry. The project was proposed to soybean production in Brazil, which is the world's leading producer, and the state of Mato Grosso, which is the principal producer of soybean in Brazil. GSN, caused by the nematode Aelenchthus coides, is a recent problem, and losses can reach up to 100% in affected areas. Monitoring nematode populations in the field is essential for managing crops, but it is a labor-intensive and time-consuming process. Symptoms of GSN in soybean are characterized by foliage deformation and discoloration, primarily observed in the plant's aerial parts. The researchers believe that hyperspectral sensing could potentially be used to monitor these symptoms in the field, aiding in the identification of infested areas. The project was proposed by Embrapa Agrosilvopastoral in partnership with Embrapa Soja, Universidade do Estado do Mato Grosso, Nemate Campos, Sinop, and the collaboration of students from IFMT and UFMT. The results showed that using a spectroradiometer to capture spectral signatures in soybean plants yielded records of healthy and infested plants. The researchers observed interference in foliar reflectance in relation to the nematode inoculation level, with similar symptoms observed for extreme levels of inoculation. The next step will be to refine this methodology to eventually develop a sensor for direct monitoring of soybean fields, identifying the occurrence of GSN. The project aims to disseminate these results to the productive sector through videos, interviews, and publications, as well as generating scientific applications. The participation of students was crucial in this process, and it was a pleasure to observe their enthusiasm and dedication to research.
• 00:05:00 In this section of the YouTube video titled "Assinatura espectral do nematoide da haste verde em soja" (Spectral signature of the green stem nematode in soybean), the speaker acknowledges the involvement of various institutions and individuals in a research project. The project, which was funded by Embrapa Agro Silvopastoral, saw contributions from Embrapa Soja, Unemat, UFMT, and IFMT. Embrapa Agro Silvopastoral's support was crucial in various sectors of the unit, leading to the project's success. Unemat played a significant role in remote sensing, while UFMT and IFMT provided scholarships for the project's development. The speaker expresses gratitude to all the partners for their collaboration.