Development of an integrated sugarcane quality management system using combined use of optical sensors

结合使用光学传感器开发集成甘蔗质量管理系统

• 批准号: 21J14214
• 负责人: Aparatana Kittipon
• 金额: $ 0.96万
• 依托单位: Kagoshima University
• 依托单位国家: 日本
• 项目类别: Grant-in-Aid for JSPS Fellows
• 财政年份: 2021
• 资助国家: 日本
• 起止时间: 2021-04-28 至 2023-03-31
• 项目状态: 已结题
• 来源: https://kaken.nii.ac.jp/en/grant/KAKENHI-PROJECT-21J14214/
• 关键词: Sugarcane; Sugar; Near-infrared; Spectroscopy; Remote sensing; Multivariate analysis; Near infrared

In 2022, we conducted experiments on Minamidaito Island in Okinawa, Japan during the growth or ripening stage of sugarcane (October-December 2022). We measured sugar quality and absorbance spectra of sugarcane stalks in the sugarcane field using a portable Vis-NIR spectrometer. Additionally, we collected multispectral images of sugarcane leaves using an unmanned aerial vehicle equipped with a multispectral camera. We evaluated the effectiveness of the multispectral images in estimating sugar quality by checking the correlation between sugar quality measured by the portable Vis-NIR spectrometer and vegetation indices.Furthermore, we investigated the effect of sugarcane skin on Minamidaito (Jan-Mar 2023). We scanned normal sugarcane stalks and peeled sugarcane stalks from different fields and varieties, then harvested the sugarcane and brought it back to the laboratory to measure sugar quality and develop a new calibration model. After developing models using the multiple linear regression method, we found that the peeled sugarcane spectra showed lower noise than the non-peeled spectra, which had higher noise caused by sugarcane wax. The results reveal that the peeled spectra model provides more accurate results than the non-peeled sugarcane spectra model, as the top two wavelengths with the highest correlation coefficient of the peeled sugarcane spectra model contain the sugar content absorption band (900-910 nanometers), whereas the normal sugarcane stalk spectra model had to select at least four wavelengths to find the sugar content absorption band.

2022年，我们在甘蔗的生长或成熟阶段（2022年10月至12月）在日本冲绳的Minamidaito岛进行了实验。我们使用便携式Vis-NIR光谱仪测量了甘蔗场中甘蔗茎的糖质量和吸光度光谱。此外，我们使用配备了多光谱摄像头的无人机收集了甘蔗叶的多光谱图像。我们通过检查通过便携式Vis-Nir光谱仪和植被指数测得的糖质量之间的相关性来评估了多光谱图像在估计糖质量方面的有效性。Furthermore，我们研究了甘蔗皮肤对Minamidaito的影响（Jan-Mar 2023）。我们扫描了来自不同田间和品种的正常甘蔗茎和剥落的甘蔗茎，然后收集了甘蔗，并将其带回实验室以测量糖品质并开发新的校准模型。在使用多个线性回归方法开发模型之后，我们发现剥落的甘蔗光谱显示出比非毛线光谱低的噪声，该光谱具有由甘蔗蜡引起的噪声更高的噪声。结果表明，剥离的光谱模型比非甲基甘蔗光谱模型提供了更准确的结果，因为剥皮的甘蔗光谱模型具有最高相关系数的前两个波长包含糖含量吸收带（900-910纳米），而糖含量的含量为糖cantal STALK STALK SPECTRA模型至少可以找到四个糖效率，可以找到糖的含量。

项目成果

Non-destructive Laboratory Analysis of the Detection of Unhealthy Sugarcane Stalks Using a Portable Vis-NIR Spectrometer

使用便携式可见-近红外光谱仪对不健康甘蔗茎进行无损实验室分析

• DOI: 10.37221/eaef.15.2_72
• 发表时间: 2022
• 期刊: Engineering in Agriculture, Environment and Food
• 作者: APARATANA Kittipon;ISHIKAWA Daitaro;MARAPHUM Kanvisit;SAENGPRACHATANARUG Khwantri;AGARIE Hitoshi;SHIKANAI Takeshi;TANAKA Munehiro;TAIRA Eizo
• 通讯作者: TAIRA Eizo

Development of the cane quality model using portable near-infrared and benchtop near-infrared spectrometer

使用便携式近红外和台式近红外光谱仪开发甘蔗质量模型

• 发表时间: 2021
• 作者: Kittipon Aparatana;Yumika Naomasa;Muneshi Mitsuoka;Eizo Taira
• 通讯作者: Eizo Taira

Predicting sugarcane quality using a portable visible near infrared spectrometer and a benchtop near infrared spectrometer

使用便携式可见近红外光谱仪和台式近红外光谱仪预测甘蔗质量

• DOI: 10.1177/09670335221136545
• 发表时间: 2022
• 期刊: Journal of Near Infrared Spectroscopy
• 影响因子: 1.8
• 作者: Aparatana Kittipon;Naomasa Yumika;Sano Morito;Watanabe Kenta;Mitsuoka Muneshi;Ueno Masami;Kawamitsu Yoshinobu;Taira Eizo
• 通讯作者: Taira Eizo

Possibility of Correlation between Sugar Parameter and Sugarcane Canopy Using a Multispectral Imaging and Portable Visible Near-infrared Spectrometer

使用多光谱成像和便携式可见近红外光谱仪建立糖参数与甘蔗冠层相关性的可能性

• 发表时间: 2022
• 作者: Kittipon Aparatana;Yumika Naomasa;Muneshi Mitsuoka;Eizo Taira
• 通讯作者: Eizo Taira

Possibility of sugarcane diagnosis using a UAV equipped with a multispectral camera

使用配备多光谱相机的无人机进行甘蔗诊断的可能性

• 发表时间: 2021
• 作者: Kittipon Aparatana;Yumika Naomasa;Muneshi Mitsuoka;Eizo Taira
• 通讯作者: Eizo Taira