Calibration and Algorithm Development for Estimation of Nitrogen in Wheat Crop Using Tractor Mounted N-Sensor
The experiment was planned to investigate the tractor mounted N-sensor (Make Yara International) to predict nitrogen (N) for wheat crop under different nitrogen levels. It was observed that, for tractor mounted N-sensor, spectrometers can scan about 32% of total area of crop under consideration. An...
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          | Published in | TheScientificWorld Vol. 2015; no. 2015; pp. 1 - 12 | 
|---|---|
| Main Authors | , , , , | 
| Format | Journal Article | 
| Language | English | 
| Published | 
        Cairo, Egypt
          Hindawi Publishing Corporation
    
        01.01.2015
     John Wiley & Sons, Inc Wiley  | 
| Subjects | |
| Online Access | Get full text | 
| ISSN | 2356-6140 1537-744X 1537-744X  | 
| DOI | 10.1155/2015/163968 | 
Cover
| Abstract | The experiment was planned to investigate the tractor mounted N-sensor (Make Yara International) to predict nitrogen (N) for wheat crop under different nitrogen levels. It was observed that, for tractor mounted N-sensor, spectrometers can scan about 32% of total area of crop under consideration. An algorithm was developed using a linear relationship between sensor sufficiency index (SIsensor) and SISPAD to calculate the Napp as a function of SISPAD. There was a strong correlation among sensor attributes (sensor value, sensor biomass, and sensor NDVI) and different N-levels. It was concluded that tillering stage is most prominent stage to predict crop yield as compared to the other stages by using sensor attributes. The algorithms developed for tillering and booting stages are useful for the prediction of N-application rates for wheat crop. N-application rates predicted by algorithm developed and sensor value were almost the same for plots with different levels of N applied. | 
    
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| AbstractList | The experiment was planned to investigate the tractor mounted N-sensor (Make Yara International) to predict nitrogen (N) for wheat crop under different nitrogen levels. It was observed that, for tractor mounted N-sensor, spectrometers can scan about 32% of total area of crop under consideration. An algorithm was developed using a linear relationship between sensor sufficiency index (SIsensor) and SISPAD to calculate the N app as a function of SISPAD. There was a strong correlation among sensor attributes (sensor value, sensor biomass, and sensor NDVI) and different N-levels. It was concluded that tillering stage is most prominent stage to predict crop yield as compared to the other stages by using sensor attributes. The algorithms developed for tillering and booting stages are useful for the prediction of N-application rates for wheat crop. N-application rates predicted by algorithm developed and sensor value were almost the same for plots with different levels of N applied. The experiment was planned to investigate the tractor mounted N-sensor (Make Yara International) to predict nitrogen (N) for wheat crop under different nitrogen levels. It was observed that, for tractor mounted N-sensor, spectrometers can scan about 32% of total area of crop under consideration. An algorithm was developed using a linear relationship between sensor sufficiency index (SIsensor) and SISPAD to calculate the Napp as a function of SISPAD. There was a strong correlation among sensor attributes (sensor value, sensor biomass, and sensor NDVI) and different N-levels. It was concluded that tillering stage is most prominent stage to predict crop yield as compared to the other stages by using sensor attributes. The algorithms developed for tillering and booting stages are useful for the prediction of N-application rates for wheat crop. N-application rates predicted by algorithm developed and sensor value were almost the same for plots with different levels of N applied. The experiment was planned to investigate the tractor mounted N‐sensor (Make Yara International) to predict nitrogen (N) for wheat crop under different nitrogen levels. It was observed that, for tractor mounted N‐sensor, spectrometers can scan about 32% of total area of crop under consideration. An algorithm was developed using a linear relationship between sensor sufficiency index (SI sensor ) and SI SPAD to calculate the N app as a function of SI SPAD . There was a strong correlation among sensor attributes (sensor value, sensor biomass, and sensor NDVI) and different N‐levels. It was concluded that tillering stage is most prominent stage to predict crop yield as compared to the other stages by using sensor attributes. The algorithms developed for tillering and booting stages are useful for the prediction of N‐application rates for wheat crop. N‐application rates predicted by algorithm developed and sensor value were almost the same for plots with different levels of N applied. The experiment was planned to investigate the tractor mounted N-sensor (Make Yara International) to predict nitrogen (N) for wheat crop under different nitrogen levels. It was observed that, for tractor mounted N-sensor, spectrometers can scan about 32% of total area of crop under consideration. An algorithm was developed using a linear relationship between sensor sufficiency index ([SI.sub.sensor]) and [SI.sub.SPAD] to calculate the [N.sub.app] as a function of [SI.sub.SPAD]. There was a strong correlation among sensor attributes (sensor value, sensor biomass, and sensor NDVI) and different N-levels. It was concluded that tillering stage is most prominent stage to predict crop yield as compared to the other stages by using sensor attributes. The algorithms developed for tillering and booting stages are useful for the prediction of N-application rates for wheat crop. N-application rates predicted by algorithm developed and sensor value were almost the same for plots with different levels of N applied. The experiment was planned to investigate the tractor mounted N-sensor (Make Yara International) to predict nitrogen (N) for wheat crop under different nitrogen levels. It was observed that, for tractor mounted N-sensor, spectrometers can scan about 32% of total area of crop under consideration. An algorithm was developed using a linear relationship between sensor sufficiency index ([subscript]SIsensor[/subscript] ) and [subscript]SISPAD[/subscript] to calculate the [subscript]Napp[/subscript] as a function of [subscript]SISPAD[/subscript] . There was a strong correlation among sensor attributes (sensor value, sensor biomass, and sensor NDVI) and different N-levels. It was concluded that tillering stage is most prominent stage to predict crop yield as compared to the other stages by using sensor attributes. The algorithms developed for tillering and booting stages are useful for the prediction of N-application rates for wheat crop. N-application rates predicted by algorithm developed and sensor value were almost the same for plots with different levels of N applied.  | 
    
| Audience | Academic | 
    
| Author | Singh, Bhupinder Thind, S. K. Singh, Manjeet Sharma, Ankit Kumar, Rajneesh  | 
    
| AuthorAffiliation | 1 Department of Farm Machinery and Power Engineering, Punjab Agricultural University, Ludhiana 141001, India 2 Krishi Vigyan Kendra, Samrala, Punjab 141114, India 4 Department of Botany, Punjab Agricultural University, Ludhiana 141001, India 3 Krishi Vigyan Kendra, Mansa, Punjab 151505, India  | 
    
| AuthorAffiliation_xml | – name: 4 Department of Botany, Punjab Agricultural University, Ludhiana 141001, India – name: 2 Krishi Vigyan Kendra, Samrala, Punjab 141114, India – name: 1 Department of Farm Machinery and Power Engineering, Punjab Agricultural University, Ludhiana 141001, India – name: 3 Krishi Vigyan Kendra, Mansa, Punjab 151505, India  | 
    
| Author_xml | – sequence: 1 fullname: Singh, Bhupinder – sequence: 2 fullname: Sharma, Ankit – sequence: 3 fullname: Kumar, Rajneesh – sequence: 4 fullname: Singh, Manjeet – sequence: 5 fullname: Thind, S. K.  | 
    
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/25811039$$D View this record in MEDLINE/PubMed | 
    
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| CitedBy_id | crossref_primary_10_1016_j_compag_2025_110110 crossref_primary_10_1007_s40030_024_00864_8 crossref_primary_10_1080_01904167_2023_2241873 crossref_primary_10_3390_s18093129 crossref_primary_10_1080_01904167_2024_2342353 crossref_primary_10_1590_0103_8478cr20170743  | 
    
| Cites_doi | 10.1300/j144v09n01_02 10.2134/agronj2003.0913 10.2134/agronj2001.931131x 10.1007/s11119-011-9229-2 10.1139/b79-163 10.1080/01904169209364335 10.2134/agronj2002.8150 10.2134/agronj1996.00021962008800010001x 10.2134/agronj2007.0244 10.2134/agronj2006.0190 10.2136/sssaj2003.0937 10.1016/S0378-4290(99)00063-5 10.13031/2013.27678 10.1016/0034-4257(94)90125-2 10.1016/s0167-1987(01)00176-3 10.2134/agronj1992.00021962008400010013x 10.2134/agronj2005.0268 10.1080/00103629209368733 10.13031/2013.27665  | 
    
| ContentType | Journal Article | 
    
| Copyright | Copyright © 2015 Manjeet Singh et al. COPYRIGHT 2015 John Wiley & Sons, Inc. Copyright © 2015 Manjeet Singh et al. Manjeet Singh et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Copyright © 2015 Manjeet Singh et al. 2015  | 
    
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| References | Anonymous YARA (Hydro Agri), tec5Hellma) 2010 (6) 1992; 23 (8) 1994; 47 (7) 1992; 15 (21) 2008; 100 (10) 1996; 88 (11) 1996; 39 (13) 2001; 93 (9) 1996; 39 (14) 2002; 94 (5) 1992; 84 (3) 1999; 64 (12) 2001; 60 (1) 2003; 9 (16) 2011; 12 (17) 2007; 99 (15) 2007; 99 (4) 2003; 95 Singh M. Sharma A. Jasper J. Investigations on tractor mounted n-sensor for wheat crop in India Proceedings of the AIPA 2012 (20) 1979; 57 (2) 2003; 67 e_1_2_8_16_2 e_1_2_8_17_2 e_1_2_8_18_2 e_1_2_8_19_2 e_1_2_8_12_2 e_1_2_8_13_2 e_1_2_8_14_2 e_1_2_8_15_2 e_1_2_8_9_2 e_1_2_8_2_2 e_1_2_8_1_2 e_1_2_8_4_2 e_1_2_8_3_2 e_1_2_8_6_2 e_1_2_8_5_2 e_1_2_8_8_2 e_1_2_8_7_2 e_1_2_8_20_2 e_1_2_8_10_2 e_1_2_8_21_2 e_1_2_8_11_2  | 
    
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| Snippet | The experiment was planned to investigate the tractor mounted N-sensor (Make Yara International) to predict nitrogen (N) for wheat crop under different... The experiment was planned to investigate the tractor mounted N‐sensor (Make Yara International) to predict nitrogen (N) for wheat crop under different...  | 
    
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| SubjectTerms | Agricultural equipment Agricultural production Agriculture - instrumentation Algorithms Biomass Calibration Cereal crops Chlorophyll - analysis Crop Production - methods Crop yield Fertilizers Fertilizers - analysis Measurement Nitrogen Nitrogen - analysis Nitrogen in the body Nutritional aspects Optical Devices Sensors Spectrometers Studies Triticum - chemistry Triticum - growth & development Wheat  | 
    
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| Title | Calibration and Algorithm Development for Estimation of Nitrogen in Wheat Crop Using Tractor Mounted N-Sensor | 
    
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