# Energy-Efficient and Economy-Sustainable Technology for Online Seed Viability Detection Using Hyper Spectrum

**Authors:** Xiantao He, Yichen Li, Jinting Zhu, Ceang Wen, Dawei Sun, Li Yang, Dongxing Zhang, Tao Cui, Kailiang Zhang, Ying Deng

PMC · DOI: 10.3390/s26041333 · Sensors (Basel, Switzerland) · 2026-02-19

## TL;DR

This paper introduces a non-destructive, energy-efficient method using hyperspectral technology to detect viable mung bean seeds before sowing, improving agricultural efficiency and reducing costs.

## Contribution

A novel hyperspectral-based online seed viability detection method is proposed, offering high accuracy and sustainability.

## Key findings

- The PLS algorithm achieved 98.8% accuracy in identifying non-viable mung bean seeds.
- The proposed method costs $0.25 per test and consumes 0.05 kWh−1, significantly lower than traditional germination tests.
- Sorting non-viable seeds increased revenue by $286.9 per hectare.

## Abstract

The seed viability detection before sowing is indispensable in the agricultural production of mung beans. The conventional detection methods for seed viability are destructive, carry a risk of contamination, and fail to identify individual non-viable seeds. In this study, an efficient and sustainable method for online viability detection of mung bean seeds was developed, which utilized hyperspectral techniques and had characteristics of rapid speed, non-destructive analysis, and the ability to detect the viability status without pollution to the environment. A sample holder for mung bean seeds was designed to stably collect spectral data. The effects of different optimal spectral bands and modeling algorithms on the detection accuracy of seed viability were analyzed. Compared to the support vector machine (SVM) and the extreme learning machine (ELM) algorithms, the partial least squares (PLS) algorithm based on the visible and near-infrared spectra (380~980 nm) had better performance. The accuracy for the identification of non-viable seeds was 98.8%, and the error of viability prediction was 20.71%. The cost of a one-time viability test is $0.25 with energy consumption of 0.05 kWh−1, which is much lower than the germination test with a cost of $80.2 and energy consumption of 50.4 kWh−1. Furthermore, individual non-viable seeds can be identified and removed, and the revenue increases by $286.9 per hectare after sorting the non-viable seeds from the seeds with an 85% germination rate. This will promote the cleaner production of mung beans without additional chemical solutions added in the process.

## Linked entities

- **Species:** Vigna radiata (taxon 157791)

## Full-text entities

- **Diseases:** injury to (MESH:D014947), insect pests (MESH:C000719201)
- **Chemicals:** starch (MESH:D013213), oil (MESH:D009821), carbohydrate (MESH:D002241), tetrazolium (MESH:D013778), lipid (MESH:D008055), bromothymol blue (MESH:D001979)
- **Species:** Solanum lycopersicum (tomato, species) [taxon 4081], watermelon [taxon 260674], Homo sapiens (human, species) [taxon 9606], Vigna radiata (mung bean, species) [taxon 157791]

## Full text

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## Figures

6 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12944581/full.md

## References

58 references — full list in the complete paper: https://tomesphere.com/paper/PMC12944581/full.md

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Source: https://tomesphere.com/paper/PMC12944581