• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Computers and Electronics in Agriculture >Classification of oil palm fresh fruit bunches based on their maturity using portable four-band sensor system.
【24h】

Classification of oil palm fresh fruit bunches based on their maturity using portable four-band sensor system.

机译：使用便携式四波段传感器系统基于成熟度对油棕新鲜水果串进行分类。

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Classification of oil palm fresh fruit bunch (FFB) maturity is a critical factor that dictates the quality of produced palm oil. This study evaluates a multi-band portable, active optical sensor system; comprising of four spectral bands, 570, 670, 750, and 870nm, to detect oil palm FFB maturity. The in-field spectral reflectance data were collected using the sensor system from a total of 120 fresh fruit bunches. These fruit bunches were categories into unripe, ripe, and overripe classes. Different classifiers were applied to assess the applicability of using the sensor system. Based on the classification accuracies, data analysis on the spectral features (reflectance data and other features extracted from vegetation indices) indicated that the spectral reflectance data could be valuable in predicting the maturity of the fruit bunches. The quadratic discriminant analysis and discriminant analysis with Mahalanobis distance classifiers yielded highest average overall accuracies of greater than 85% in classifying oil palm FFB maturity. Additionally, the average individual class (unripe, ripe, and overripe) classification accuracies were also higher than 80%. Thus, optical sensing using four-band sensor system could be useful for oil palm FFB maturity classification under field condition. All rights reserved, Elsevier.
机译：油棕新鲜水果束（FFB）成熟度的分类是决定所生产的棕榈油质量的关键因素。这项研究评估了多波段便携式有源光学传感器系统;由四个光谱带570、670、750和870nm组成，以检测油棕FFB的成熟度。使用传感器系统从总共120个新鲜水果束中收集了现场光谱反射率数据。这些水果串分为未成熟，成熟和过度成熟类。应用了不同的分类器来评估使用传感器系统的适用性。基于分类的准确性，对光谱特征（反射率数据和从植被指数中提取的其他特征）的数据分析表明，光谱反射率数据对于预测水果串的成熟度可能是有价值的。在对油棕FFB成熟度进行分类时，二次判别分析和使用Mahalanobis距离分类器进行的判别分析产生的最高平均总准确度大于85％。此外，平均个人分类（未成熟，成熟和过度成熟）的分类准确性也高于80％。因此，在田间条件下，使用四波段传感器系统进行光学传感可能对油棕FFB成熟度分类很有用。保留所有权利，Elsevier。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号