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A protocol for Chenopodium quinoa pollen germination.

S Elizabeth Castillo1, Jose C Tovar1, Anastasia Shamin1

  • 1Donald Danforth Plant Science Center, St. Louis, MO, 63132, USA.

Plant Methods
|May 18, 2022
PubMed
Summary
This summary is machine-generated.

This study developed an in vitro quinoa pollen germination method to assess fertility and identify breeding lines. The optimized method, including specific media and pollen collection timing, achieves high germination rates and aids in understanding stress impacts on seed yield.

Keywords:
Pollen germinationProtocolQuinoa

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Area of Science:

  • Agricultural Science
  • Plant Biology
  • Crop Science

Background:

  • Quinoa is a popular crop facing heat stress, with variable pollen viability data from staining methods.
  • In vitro germination offers a more reliable alternative for assessing quinoa pollen viability.
  • Understanding pollen viability is crucial for quinoa fertility, seed yield, and breeding programs.

Purpose of the Study:

  • To establish a reliable in vitro method for quinoa pollen germination.
  • To optimize conditions for maximizing quinoa pollen germination rates.
  • To develop tools for semi-automating pollen viability assessment in quinoa.

Main Methods:

  • Optimized pollen collection at 4 days post-anthesis, zeitgeber time 5.
  • Determined optimal incubation period of 48 hours to balance germination and contamination.
  • Fine-tuned pollen germination medium: 16% sucrose, 0.03% boric acid, 0.007% calcium nitrate, pH 5.5.
  • Developed a semi-automated image analysis tool using PlantCV for counting germinating pollen.

Main Results:

  • Achieved average germination rates of 68% for accession QQ74 and 64% for 'cherry vanilla'.
  • Identified optimal medium composition and incubation time for high germination efficiency.
  • Demonstrated the utility of the developed method across different quinoa accessions.

Conclusions:

  • The established in vitro method provides a robust tool for quinoa pollen viability assessment.
  • This method aids in evaluating the effects of various stresses on quinoa fertility and seed production.
  • The semi-automated image analysis tool enhances the efficiency of pollen viability studies in quinoa breeding.