ABSTRACT

Chemical soil and plant analyses are time-consuming, expensive, and labor-intensive. There are some optical systems used for this purpose; however, they are expensive and require expertise for their operation. The aim of this study was to develop a low-cost prototype optical sensor and compare it with three commercial systems (GreenSeeker NDVI (Normalized Difference Vegetation Index) meter, chromameter, Fourier transform-near infrared reflectance spectroscopy (FT-NIRS)) to determine water and nutrient concentrations including nitrogen (N), phosphorus (P), potassium (K), calcium (Ca), magnesium (Mg), iron (Fe), copper (Cu), manganese (Mn), and zinc (Zn) of turfgrass (Lolium perenne L.). Study was conducted on an experimental field to which four different levels of nitrogen fertilizer were applied. Prediction models were developed using PLSR (Partial Least Square Regression) and their performances were evaluated using the criteria of SEP (Standard Error of Prediction) and R². With the prototype optical sensor, NDVI gave the best result among 10 different vegetation indices for the prediction of water (SEP = 1.43%) and N (SEP = 0.28%). The best results (lowest SEP) were obtained with the FT-NIRS. However, there are some disadvantages of this system along with the other two instruments (chromameter and NDVI meter) of being expensive and requiring expertise in their operation. Low-cost and easy-to-use prototype optical sensor gave similar results with the NDVI meter and chromameter to predict water and nutrient concentrations except K, Cu, and Zn. An optical sensor similar to the prototype sensor could be developed commercially with low cost and used to estimate the water and nutrient concentration of turfgrass.

摘要

化学土壤和植物分析非常耗时，昂贵且劳动强度大。有一些光学系统用于此目的。但是，它们价格昂贵，并且需要专门的操作知识。这项研究的目的是开发一种低成本的原型光学传感器，并将其与三种商用系统（GreenSeeker NDVI（归一化植被指数）仪，色度计，傅立叶变换近红外反射光谱仪（FT-NIRS））进行比较，以确定水和营养物的浓度，包括氮（N），磷（P），钾（K），钙（Ca），镁（Mg），铁（Fe），铜（Cu），锰（Mn）和锌（Zn）草坪草（黑麦草）L.）。在一个试验场上进行了研究，在该试验场上应用了四种不同水平的氮肥。使用PLSR（偏最小二乘回归）开发了预测模型，并使用SEP（预测的标准误差）和R ²的标准对它们的性能进行了评估。。使用原型光学传感器，NDVI在10种不同植被指数中的水（SEP = 1.43％）和N（SEP = 0.28％）的预测中表现最好。FT-NIRS获得了最好的结果（最低的SEP）。但是，该系统与其他两种仪器（色度计和NDVI计）一起存在一些缺点，即价格昂贵并且需要其操作方面的专业知识。低成本且易于使用的原型光学传感器与NDVI计和色度计可得出相似的结果，以预测除K，Cu和Zn以外的水和营养物浓度。类似于原型传感器的光学传感器可以低成本商业开发，并用于估算草皮草的水分和养分浓度。