English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

This study aimed to design and develop a watermelon ripeness detector using Near-Infrared Spectroscopy (NIRS). The research problem being solved in this study is developing a prototype wherein the watermelon ripeness can be detected without the need to open it. This detector will save customers from buying unripe watermelon and the farmers from harvesting an unripe watermelon. The researchers attempted to use the NIRS technique in determining the ripeness level of watermelon as it is widely used in the agricultural sector with high-speed analysis. The project was composed of Raspberry Pi Zero W as the microprocessor unit connected to input and output devices, such as the NIR spectral sensor and the OLED display. It was programmed by Python 3 IDLE. The detector scanned a total of 200 watermelon samples. These samples were grouped as 60 % for the training dataset, 20 % for testing, and another 20 % for evaluation. The data sets were collected and are subjected to the Support Vector Machine (SVM) algorithm. Overall, experimental results showed that the detector could correctly classify both unripe and ripe watermelons with 92.5 % accuracy.

Watermelon ripeness detector using near infrared spectroscopy