Image Analysis for Starch Quantification in Histochemically Stained Flower Tissues using FIJI (Image J) v1

Starch is the main storage carbohydrate in plants and plays an important role in flower development, being accumulated in specific tissues prior to development. Starch can be easily visualized in histological sections stained with IKI; however, quantifying this starch in such small and specific tissues remains challenging. This issue has previously been addressed by indirect quantification of starch through computer-based image analysis with proprietary software. In this protocol, we present a detailed step-by-step adaptation to perform an equivalent analysis using FIJI (ImageJ), an open-source software program for scientific image processing and analysis. The protocol is divided into three main stages:(i) sample preparation for microscopy: fixation, paraffin wax embedding, sectioning, staining, and mounting; (ii) image acquisition: microscopy and camera settings; and (iii) image analysis for starch quantification: selection of the measuring area, starch detection, black-and-white transformation, gray scale calibration for Optical Density, and measurement of the integrated density. This protocol provides a reproducible workflow for the relative quantification of starch in specific flower tissues over time or under different experimental treatments.

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Published
2025-09-26
DOI
https://doi.org/10.17504/protocols.io.q26g7ndy9lwz/v1
Primary Topic
Nuts composition and effects
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article
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article

Image Analysis for Starch Quantification in Histochemically Stained Flower Tissues using FIJI (Image J) v1

Erica Fadón, Javier Rodrigo Hitos
Nuts composition and effects
article

Image Analysis for Starch Quantification in Histochemically Stained Flower Tissues using FIJI (Image J) v1

Erica Fadón, Javier Rodrigo Hitos
article en

Abstract

Starch is the main storage carbohydrate in plants and plays an important role in flower development, being accumulated in specific tissues prior to development. Starch can be easily visualized in histological sections stained with IKI; however, quantifying this starch in such small and specific tissues remains challenging. This issue has previously been addressed by indirect quantification of starch through computer-based image analysis with proprietary software. In this protocol, we present a detailed step-by-step adaptation to perform an equivalent analysis using FIJI (ImageJ), an open-source software program for scientific image processing and analysis. The protocol is divided into three main stages:(i) sample preparation for microscopy: fixation, paraffin wax embedding, sectioning, staining, and mounting; (ii) image acquisition: microscopy and camera settings; and (iii) image analysis for starch quantification: selection of the measuring area, starch detection, black-and-white transformation, gray scale calibration for Optical Density, and measurement of the integrated density. This protocol provides a reproducible workflow for the relative quantification of starch in specific flower tissues over time or under different experimental treatments.

Centro de Investigación y Tecnología Agroalimentaria de Aragón (ES)
Openalex Percentile: Top 67%
Nuts composition and effects
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Image Analysis for Starch Quantification in Histochemically Stained Flower Tissues using FIJI (Image J) v1 — Erica Fadón, Javier Rodrigo Hitos · (2025) | TGRS Research Map | TGRS