Fast And Simultaneous Prediction Of Agricultural Soil Nutrients Content Using Infrared Spectroscopy
Abstract. The functions soil depends on the balances of its structure, nutrients composition as well as other chemical and physical properties. Conventional methods, used to determine nutrients content on agricultural soil were time consuming, complicated sample processing and destructive in nature....
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Syiah Kuala University
2019-04-01
|
| Series: | Rona Teknik Pertanian |
| Subjects: | |
| Online Access: | https://jurnal.usk.ac.id/RTP/article/view/11656 |
| _version_ | 1797277472786481152 |
|---|---|
| author | Devianti Devianti Zulfahrizal Zulfahrizal Sufardi Sufardi Agus Arip Munawar |
| author_facet | Devianti Devianti Zulfahrizal Zulfahrizal Sufardi Sufardi Agus Arip Munawar |
| author_sort | Devianti Devianti |
| collection | DOAJ |
| description | Abstract. The functions soil depends on the balances of its structure, nutrients composition as well as other chemical and physical properties. Conventional methods, used to determine nutrients content on agricultural soil were time consuming, complicated sample processing and destructive in nature. Near infrared reflectance spectroscopy (NIRS) has become one of the most promising and used non-destructive methods of analysis in many field areas including in soil science. The main aim of this present study is to apply NIRS in predicting nutrients content of soils in form of total nitrogen (N). Transmittance spectra data were obtained from a total of 18 soil samples from 8 different sites followed by N measurement using standard laboratory method. Principal component regression (PCR) with full cross validation were used to develop and validate N prediction models. The results showed that N content can be predicted very well even with raw spectra data with coefficient correlation (r) and residual predictive deviation index (RPD) were 0.95 and 3.35 respectively. Furthermore, spectra correction clearly enhances and improve prediction accuracy with r = 0.96 and RPD = 3.51. It may conclude that NIRS can be used as fast and simultaneous method in determining nutrient content of agricultural soils. |
| first_indexed | 2024-03-07T15:48:55Z |
| format | Article |
| id | doaj.art-ee116275c7e8410f85bae377aeceefe9 |
| institution | Directory Open Access Journal |
| issn | 2085-2614 2528-2654 |
| language | English |
| last_indexed | 2024-03-07T15:48:55Z |
| publishDate | 2019-04-01 |
| publisher | Syiah Kuala University |
| record_format | Article |
| series | Rona Teknik Pertanian |
| spelling | doaj.art-ee116275c7e8410f85bae377aeceefe92024-03-05T03:45:56ZengSyiah Kuala UniversityRona Teknik Pertanian2085-26142528-26542019-04-01121616610.17969/rtp.v12i1.1165610089Fast And Simultaneous Prediction Of Agricultural Soil Nutrients Content Using Infrared SpectroscopyDevianti Devianti0Zulfahrizal Zulfahrizal1Sufardi Sufardi2Agus Arip Munawar3Department of Agricultural Engineering, Universitas Syiah KualaDepartment of Agricultural Engineering, Universitas Syiah KualaDepartment of Soil Science, Universitas Syiah KualaDepartment of Agricultural Engineering, Universitas Syiah KualaAbstract. The functions soil depends on the balances of its structure, nutrients composition as well as other chemical and physical properties. Conventional methods, used to determine nutrients content on agricultural soil were time consuming, complicated sample processing and destructive in nature. Near infrared reflectance spectroscopy (NIRS) has become one of the most promising and used non-destructive methods of analysis in many field areas including in soil science. The main aim of this present study is to apply NIRS in predicting nutrients content of soils in form of total nitrogen (N). Transmittance spectra data were obtained from a total of 18 soil samples from 8 different sites followed by N measurement using standard laboratory method. Principal component regression (PCR) with full cross validation were used to develop and validate N prediction models. The results showed that N content can be predicted very well even with raw spectra data with coefficient correlation (r) and residual predictive deviation index (RPD) were 0.95 and 3.35 respectively. Furthermore, spectra correction clearly enhances and improve prediction accuracy with r = 0.96 and RPD = 3.51. It may conclude that NIRS can be used as fast and simultaneous method in determining nutrient content of agricultural soils.https://jurnal.usk.ac.id/RTP/article/view/11656infraredsoilnitrogenpredictionspectroscopy |
| spellingShingle | Devianti Devianti Zulfahrizal Zulfahrizal Sufardi Sufardi Agus Arip Munawar Fast And Simultaneous Prediction Of Agricultural Soil Nutrients Content Using Infrared Spectroscopy Rona Teknik Pertanian infrared soil nitrogen prediction spectroscopy |
| title | Fast And Simultaneous Prediction Of Agricultural Soil Nutrients Content Using Infrared Spectroscopy |
| title_full | Fast And Simultaneous Prediction Of Agricultural Soil Nutrients Content Using Infrared Spectroscopy |
| title_fullStr | Fast And Simultaneous Prediction Of Agricultural Soil Nutrients Content Using Infrared Spectroscopy |
| title_full_unstemmed | Fast And Simultaneous Prediction Of Agricultural Soil Nutrients Content Using Infrared Spectroscopy |
| title_short | Fast And Simultaneous Prediction Of Agricultural Soil Nutrients Content Using Infrared Spectroscopy |
| title_sort | fast and simultaneous prediction of agricultural soil nutrients content using infrared spectroscopy |
| topic | infrared soil nitrogen prediction spectroscopy |
| url | https://jurnal.usk.ac.id/RTP/article/view/11656 |
| work_keys_str_mv | AT deviantidevianti fastandsimultaneouspredictionofagriculturalsoilnutrientscontentusinginfraredspectroscopy AT zulfahrizalzulfahrizal fastandsimultaneouspredictionofagriculturalsoilnutrientscontentusinginfraredspectroscopy AT sufardisufardi fastandsimultaneouspredictionofagriculturalsoilnutrientscontentusinginfraredspectroscopy AT agusaripmunawar fastandsimultaneouspredictionofagriculturalsoilnutrientscontentusinginfraredspectroscopy |