Sistem Pengukuran Nitrogen, Fosfor, Kalium Dengan Local Binary Pattern Dan Analisis Regresi

Muhammad Miftahul Amri, R. Sumiharto
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引用次数: 3

Abstract

Nitrogen, Phosphorus and Potassium (NPK) are macro elements that important for the paddy development. NPK is a parameter that used for calculating fertilizer dosage. Current NPK measurement through laboratory requires a relatively long time, so we design a new system that can speed up the process and provide correct fertilizer dosage recommendations.This paper proposes an android based system using Local Binary Pattern (LBP) and Regression Analysis to measure soil nutrients and provide fertilizer dosage recommendations based on the LPT Bogor's formula. Samples of soil image taken from rice fields in Special Region of Yogyakarta. The measurement is processed by extracting LBP features from the soil image that has through the pre-processing stage. The extraction results were then analyzed using Multiple Linear Regression (MLR). The equation results from MLR is used to calculate NPK.The results show that the proposed system can detect NPK levels in paddy fields in Yogyakarta and provide fertilization dosage with an average detection accuracy of 70.65% (N 94.98%, P 50.84 %, and K 66.14%). The accuracy was obtained from the image taking at an optimal height of 70 cm and optimal angle of 0o to the ground surface. The average processing time is 0.61 seconds.
局部二元模式氮磷钾测定系统及其回归分析
氮、磷、钾(NPK)是水稻生长发育的重要宏观元素。氮磷钾是计算肥料用量的参数。目前通过实验室测量氮磷钾需要较长的时间,因此我们设计了一个新的系统,可以加快这一过程,并提供正确的肥料用量建议。本文提出了一种基于机器人的基于局部二值模式(LBP)和回归分析的土壤养分测量系统,并根据LPT茂物公式提供肥料用量建议。从日惹特区稻田中拍摄的土壤图像样本。通过提取预处理后的土壤图像中的LBP特征对测量结果进行处理。提取结果采用多元线性回归(MLR)进行分析。利用MLR计算得到的方程计算NPK。结果表明,该系统能有效检测日惹地区稻田氮磷钾水平,提供的施肥剂量平均检测准确率为70.65% (N为94.98%,P为50.84%,K为66.14%)。该精度是在最佳高度为70 cm,最佳角度为0°时拍摄的图像获得的。平均处理时间为0.61秒。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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