光谱学与光谱分析 |
|
|
|
|
|
A New Approach to Rapid Determination of Compound Fertilizer Composition |
GUO Zheng, YUAN Hong-fu*, ZHANG Xian, SONG Chun-feng, LI Xiao-yu, XIE Jin-chun |
Beijing University of Chemical Technology, Beijing 100029, China |
|
|
Abstract In the present paper, a new approach to rapid determination of compound fertilizer composition was introduced, namely first preparing aqueous solution of solid fertilizer, then predicting the compound fertilizer composition using the near infrared transmission spectra of the solution. Using the new method, models were built by means of PLS regression, and the standard errors of prediction of total nitrogen content, P2O5 content, and K2O content are 0.5, 0.7, 0.8, and 2.0, respectively. This has solved the problem of large prediction error for K content of compound fertilizer using near infrared reflectance spectroscopy due to the fact that KCl dose not have near infrared absorption, and achieved rapid analysis of all compositions of compound fertilizer in 5 minutes.
|
Received: 2010-11-19
Accepted: 2011-03-30
|
|
Corresponding Authors:
YUAN Hong-fu
E-mail: hfyuan@mail.buct.edu.cn
|
|
[1] GB 15063—2009 Compound Fertilizer(复合肥料). Gtenaral Administation of Supervision, Inspection Quarantine of China(国家质量监督检验检疫总局), 2009. [2] GB/T 8572—2001 Determination of Total Nitrogen Content for Compound Fertilizer—Titrimetric Method after Distillation(复混肥料中总氮含量的测定—蒸馏后滴定法). Gtenaral Administation of Supervision, Inspection Quarantine of China(国家质量监督检验检疫总局), 2001. [3] GB/T 8573—1999 Determination of Available Phosphorus Content for Compound Fertilizers(复混肥料中有效磷含量的测定). Gtenaral Administation of Supervision, Inspection Quarantine of China(国家质量监督检验检疫总局), 1999. [4] GB/T 8574—2002 Determination of Potassium Content for Compound Fertilizers Potassium Tetraphenylborate Gravimetric Method(复混肥料中钾含量的测定—四苯硼酸钾重量法). Gtenaral Administation of Supervision, Inspection Quarantine of China(国家质量监督检验检疫总局), 2002. [5] LU Wan-zhen,YUAN Hong-fu,XU Guang-tong(陆婉珍,袁洪福,徐广通). The Modern Analysis Technique for Near-Infrared Spectra(现代近红外光谱分析技术). Beijing: Chinese Oil and Chemical Press(北京:中国石油化工出版社),2001. [6] Jerry W,Lois W. Practical Guide to Interpretive Near-Infrared Spectroscopy(近红外光谱解析实用指南). Translated by CHU Xiao-li,XU Yu-peng,TIAN Gao-you(褚小立,许育鹏,田高友,译). Beijing:Chemical Industry Press(北京:化学工业出版社),2009. 57.
|
[1] |
GAO Feng1, 2, XING Ya-ge3, 4, LUO Hua-ping1, 2, ZHANG Yuan-hua3, 4, GUO Ling3, 4*. Nondestructive Identification of Apricot Varieties Based on Visible/Near Infrared Spectroscopy and Chemometrics Methods[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 44-51. |
[2] |
LI Yu1, ZHANG Ke-can1, PENG Li-juan2*, ZHU Zheng-liang1, HE Liang1*. Simultaneous Detection of Glucose and Xylose in Tobacco by Using Partial Least Squares Assisted UV-Vis Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 103-110. |
[3] |
BAO Hao1, 2,ZHANG Yan1, 2*. Research on Spectral Feature Band Selection Model Based on Improved Harris Hawk Optimization Algorithm[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 148-157. |
[4] |
HU Cai-ping1, HE Cheng-yu2, KONG Li-wei3, ZHU You-you3*, WU Bin4, ZHOU Hao-xiang3, SUN Jun2. Identification of Tea Based on Near-Infrared Spectra and Fuzzy Linear Discriminant QR Analysis[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3802-3805. |
[5] |
LIU Xin-peng1, SUN Xiang-hong2, QIN Yu-hua1*, ZHANG Min1, GONG Hui-li3. Research on t-SNE Similarity Measurement Method Based on Wasserstein Divergence[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3806-3812. |
[6] |
BAI Xue-bing1, 2, SONG Chang-ze1, ZHANG Qian-wei1, DAI Bin-xiu1, JIN Guo-jie1, 2, LIU Wen-zheng1, TAO Yong-sheng1, 2*. Rapid and Nndestructive Dagnosis Mthod for Posphate Dficiency in “Cabernet Sauvignon” Gape Laves by Vis/NIR Sectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3719-3725. |
[7] |
WANG Qi-biao1, HE Yu-kai1, LUO Yu-shi1, WANG Shu-jun1, XIE Bo2, DENG Chao2*, LIU Yong3, TUO Xian-guo3. Study on Analysis Method of Distiller's Grains Acidity Based on
Convolutional Neural Network and Near Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3726-3731. |
[8] |
LUO Li, WANG Jing-yi, XU Zhao-jun, NA Bin*. Geographic Origin Discrimination of Wood Using NIR Spectroscopy
Combined With Machine Learning Techniques[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3372-3379. |
[9] |
ZHANG Shu-fang1, LEI Lei2, LEI Shun-xin2, TAN Xue-cai1, LIU Shao-gang1, YAN Jun1*. Traceability of Geographical Origin of Jasmine Based on Near
Infrared Diffuse Reflectance Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3389-3395. |
[10] |
YANG Qun1, 2, LING Qi-han1, WEI Yong1, NING Qiang1, 2, KONG Fa-ming1, ZHOU Yi-fan1, 2, ZHANG Hai-lin1, WANG Jie1, 2*. Non-Destructive Monitoring Model of Functional Nitrogen Content in
Citrus Leaves Based on Visible-Near Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3396-3403. |
[11] |
HUANG Meng-qiang1, KUANG Wen-jian2, 3*, LIU Xiang1, HE Liang4. Quantitative Analysis of Cotton/Polyester/Wool Blended Fiber Content by Near-Infrared Spectroscopy Based on 1D-CNN[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3565-3570. |
[12] |
HUANG Zhao-di1, CHEN Zai-liang2, WANG Chen3, TIAN Peng2, ZHANG Hai-liang2, XIE Chao-yong2*, LIU Xue-mei4*. Comparing Different Multivariate Calibration Methods Analyses for Measurement of Soil Properties Using Visible and Short Wave-Near
Infrared Spectroscopy Combined With Machine Learning Algorithms[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3535-3540. |
[13] |
KANG Ming-yue1, 3, WANG Cheng1, SUN Hong-yan3, LI Zuo-lin2, LUO Bin1*. Research on Internal Quality Detection Method of Cherry Tomatoes Based on Improved WOA-LSSVM[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3541-3550. |
[14] |
HUANG Hua1, LIU Ya2, KUERBANGULI·Dulikun1, ZENG Fan-lin1, MAYIRAN·Maimaiti1, AWAGULI·Maimaiti1, MAIDINUERHAN·Aizezi1, GUO Jun-xian3*. Ensemble Learning Model Incorporating Fractional Differential and
PIMP-RF Algorithm to Predict Soluble Solids Content of Apples
During Maturing Period[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 3059-3066. |
[15] |
CHEN Jia-wei1, 2, ZHOU De-qiang1, 2*, CUI Chen-hao3, REN Zhi-jun1, ZUO Wen-juan1. Prediction Model of Farinograph Characteristics of Wheat Flour Based on Near Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 3089-3097. |
|
|
|
|