Agrotechnics in Seed Quality: Current Progress and Challenges

A special issue of Agronomy (ISSN 2073-4395). This special issue belongs to the section "Plant-Crop Biology and Biochemistry".

Deadline for manuscript submissions: 25 September 2025 | Viewed by 2089

Special Issue Editors


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Guest Editor
Laboratory of Radiobiology and Environment, Center for Nuclear Energy in Agriculture, University of São Paulo, Piracicaba 13416-000, SP, Brazil
Interests: non-destructive methods; seed quality; imaging technology; multispectral imaging; radiography; fluorescence; seed-borne fungi
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Guest Editor
Department of Crop Science, College of Agricultural Sciences, São Paulo State University, Botucatu 18610-034, SP, Brazil
Interests: seed physiology; molecular biology; imaging technology
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Around the world, the seed industry has undergone many transformations driven by recent trends in digital agriculture, such as robust optical sensors, software, robotics, automation, and sophisticated data analyses. Sustainable methods have been developed based on non-destructive measurements without relying on human vision.

An important approach that has contributed to the implementation of digital solutions is the creation of machine learning models. These models can automatically diagnose the genetic, physical, chemical, physiological, and health attributes of seed quality. For example, knowledge of the electromagnetic properties of the seed tissues has enabled the non-invasive detection of mechanical damage, insects, and physiological disturbances in agricultural seeds.

This Special Issue focuses on the main technologies for autonomous seed quality screening, including spectroscopy, multispectral imaging, radiographs, and autofluorescence, among others, with an emphasis on agricultural challenges and current trends to assess seed quality parameters.

You may choose our Joint Special Issue in Seeds.

Dr. Clíssia Barboza Mastrangelo
Dr. Edvaldo Aparecido Amaral Da Silva
Guest Editors

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Keywords

  • multispectral imaging
  • spectroscopy
  • fluorescence
  • radiography
  • hyperspectral image
  • tomography
  • magnetic resonance
  • machine learning
  • seed vigor
  • fungi

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Published Papers (1 paper)

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Research

17 pages, 2967 KiB  
Article
Spectroscopy Technologies to Screen Peanut Seeds with Superior Vigor Through “Chemical Fingerprinting”
by Gustavo Roberto Fonseca de Oliveira, Welinton Yoshio Hirai, Dennis Silva Ferreira, Karolyne Priscila Oliveira Mota da Silva, Giovani Chaves Silva, Tiago Bueno Moraes, Clissia Barboza Mastrangelo, Fabiola Manhas Verbi Pereira, Edenir Rodrigues Pereira-Filho and Edvaldo Aparecido Amaral da Silva
Agronomy 2024, 14(11), 2529; https://doi.org/10.3390/agronomy14112529 - 28 Oct 2024
Viewed by 1366
Abstract
Peanut seeds are harvested at different development stages (early and late) due to their uneven maturation. At the time of harvest, approximately 30% of the seeds are still immature, meaning they are not completely filled with compounds (e.g., oil and minerals) and exhibit [...] Read more.
Peanut seeds are harvested at different development stages (early and late) due to their uneven maturation. At the time of harvest, approximately 30% of the seeds are still immature, meaning they are not completely filled with compounds (e.g., oil and minerals) and exhibit reduced vigor. Hypothetically, these compounds can be detected as a “chemical fingerprinting” to classify seed maturation stages. Here, we investigated whether non-destructive techniques such as benchtop nuclear magnetic resonance (NMR), laser-induced breakdown spectroscopy (LIBS), and energy-dispersive X-ray fluorescence (ED-XRF) can identify chemical patterns unique to mature seeds with superior vigor. Field-grown seeds were classified into early (R5 and R6) and late (R7, R8, and R9) stages. Seed weight, germination, vigor, H2O2, and MDA (oxidative stress) were analyzed. Oil, potassium (K), and calcium (Ca) were measured digitally using spectroscopy techniques. We found that: (i) oxidative stress and K levels were higher in seeds from the early stages; (ii) seed oil and Ca were proportional to high-vigor seedlings and successful plant establishment in the field; and (iii) the seed chemical composition could be identified autonomously with 87% to 100% accuracy. In conclusion, LIBS, ED-XRF, and NMR technologies can effectively screen peanut seeds with superior vigor through “chemical fingerprinting”. Full article
(This article belongs to the Special Issue Agrotechnics in Seed Quality: Current Progress and Challenges)
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