Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Fruit Development, Structure, and Function01:58

Fruit Development, Structure, and Function

24.8K
Fruits form from a mature flower ovary. As seeds develop from the ovules contained within, the ovary wall undergoes a series of complex changes to form fruit. In some fruits, such as soybeans, the ovary wall dries; in other fruits, such as grapes, it remains fleshy. In some cases, organs other than the ovary contribute to fruit formation; such fruits are called accessory fruits.
24.8K
Light Acquisition02:16

Light Acquisition

9.3K
In order to produce glucose, plants need to capture sufficient light energy. Many modern plants have evolved leaves specialized for light acquisition. Leaves can be only millimeters in width or tens of meters wide, depending on the environment. Due to competition for sunlight, evolution has driven the evolution of increasingly larger leaves and taller plants, to avoid shading by their neighbors with contaminant elaboration of root architecture and mechanisms to transport water and nutrients.
9.3K
Plant Breeding and Biotechnology01:59

Plant Breeding and Biotechnology

21.4K
Crop cultivation has a long history in human civilization, with records showing the cultivation of cereal plants beginning at around 8000 BC. This early plant breeding was developed primarily to provide a steady supply of food.
21.4K
Raman Spectroscopy Instrumentation: Overview01:26

Raman Spectroscopy Instrumentation: Overview

1.0K
A conventional Raman spectrophotometer includes a laser source, a sample holding system, a wavelength selector, and a detector.
The monochromatic laser source, typically using visible or near-infrared radiation, generates a highly focused beam of light. This light interacts with the molecules of the sample, scattering some of the light. Liquid and gaseous samples are usually tested in ordinary glass capillaries, while solids can be analyzed as powders packed in capillaries or as potassium...
1.0K
Development of Analytical Methods01:21

Development of Analytical Methods

1.6K
An analytical methodology can be divided into four sequential steps: technique, method, procedure, and protocol. A technique is a scientific principle that rationalizes a specific phenomenon through chemical measurements. Adapting a technique for analyzing a sample of interest is termed a method. The procedure outlines the directions for performing the analysis via an analytical method. The protocol is the detailed guidelines on the procedure, which should be strictly followed to obtain the...
1.6K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Effects of herbaceous root development on soil water infiltration and hydraulic properties in loess.

Scientific reports·2026
Same author

Structural analysis and optimization of an autonomous robot designed for greenhouse roof cleaning.

Scientific reports·2026
Same author

Eu-proanthocyanidin/lactoferrin amyloid composite coating: interfacial microenvironment modulation for integrated enhancement of anti-inflammatory, antibacterial, and osteogenic effects.

Colloids and surfaces. B, Biointerfaces·2026
Same author

Self-assembly of non-close-packed photonic crystal hydrogels enables robust point-of-care detection of microRNA in body fluids.

Biosensors & bioelectronics·2026
Same author

Gestational diabetes status modifies pre-pregnancy BMI associations with large for gestational age: A prospective cohort study in central China.

International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics·2026
Same author

Simulation and prediction of post-harvest ripening processes for tomatoes with different ripeness levels based on electrical characteristics.

Food chemistry·2026

Related Experiment Video

Updated: Jan 10, 2026

Construction of Models for Nondestructive Prediction of Ingredient Contents in Blueberries by Near-infrared Spectroscopy Based on HPLC Measurements
10:25

Construction of Models for Nondestructive Prediction of Ingredient Contents in Blueberries by Near-infrared Spectroscopy Based on HPLC Measurements

Published on: June 28, 2016

11.1K

SpectralFlow: an integrated platform for spectral data preprocessing and predictive modeling analysis in fruit

Zhikai Chen1,2, Guanzhi Lyu1,2, Xiaochan Wang2

  • 1Sanya Institute of Nanjing Agricultural University, Sanya, Hainan, 572025, China. xlzhang@njau.edu.cn.

The Analyst
|November 24, 2025
PubMed
Summary

SpectralFlow software enhances fruit quality analysis using near-infrared spectroscopy and hyperspectral imaging. It simplifies complex spectral data preprocessing and deep learning model training for accurate predictions.

More Related Videos

Fruit Volatile Analysis Using an Electronic Nose
11:02

Fruit Volatile Analysis Using an Electronic Nose

Published on: March 30, 2012

22.3K
PTR-ToF-MS Coupled with an Automated Sampling System and Tailored Data Analysis for Food Studies: Bioprocess Monitoring, Screening and Nose-space Analysis
08:43

PTR-ToF-MS Coupled with an Automated Sampling System and Tailored Data Analysis for Food Studies: Bioprocess Monitoring, Screening and Nose-space Analysis

Published on: May 11, 2017

12.9K

Related Experiment Videos

Last Updated: Jan 10, 2026

Construction of Models for Nondestructive Prediction of Ingredient Contents in Blueberries by Near-infrared Spectroscopy Based on HPLC Measurements
10:25

Construction of Models for Nondestructive Prediction of Ingredient Contents in Blueberries by Near-infrared Spectroscopy Based on HPLC Measurements

Published on: June 28, 2016

11.1K
Fruit Volatile Analysis Using an Electronic Nose
11:02

Fruit Volatile Analysis Using an Electronic Nose

Published on: March 30, 2012

22.3K
PTR-ToF-MS Coupled with an Automated Sampling System and Tailored Data Analysis for Food Studies: Bioprocess Monitoring, Screening and Nose-space Analysis
08:43

PTR-ToF-MS Coupled with an Automated Sampling System and Tailored Data Analysis for Food Studies: Bioprocess Monitoring, Screening and Nose-space Analysis

Published on: May 11, 2017

12.9K

Area of Science:

  • Agricultural Science
  • Spectroscopy
  • Machine Learning

Background:

  • Near-infrared (NIR) spectroscopy and hyperspectral imaging (HSI) are powerful tools for fruit quality assessment.
  • Existing software often lacks support for advanced deep learning models and 2D image data analysis.
  • There is a need for user-friendly software that integrates data preprocessing and complex model training for HSI data.

Purpose of the Study:

  • To develop SpectralFlow, a comprehensive software solution for spectral data analysis in fruit quality evaluation.
  • To address limitations in current software regarding deep learning and hyperspectral image feature extraction.
  • To simplify the process of spectral data preprocessing and model training for researchers.

Main Methods:

  • Developed SpectralFlow software with integrated spectral data extraction, preprocessing, and visualization.
  • Included a model library with support for custom deep learning architectures and hyperparameter tuning.
  • Validated SpectralFlow using two case studies: mango anthracnose prediction and dry matter content (DMC) prediction in multiple fruits.

Main Results:

  • SpectralFlow demonstrated effective spectral data preprocessing and model training capabilities.
  • Mango anthracnose prediction achieved over 92% accuracy.
  • Dry matter content (DMC) prediction models for apples, mangoes, kiwifruit, and pears achieved R-squared values exceeding 0.80.

Conclusions:

  • SpectralFlow significantly lowers the technical barrier for advanced spectral data analysis.
  • The software is highly effective for both spectral data preprocessing and complex model training.
  • SpectralFlow shows great potential for advancing fruit quality evaluation using NIR spectroscopy and HSI.