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Calibration and algorithm development for estimation of nitrogen in wheat crop using tractor mounted N-sensor.
Singh, Manjeet; Kumar, Rajneesh; Sharma, Ankit; Singh, Bhupinder; Thind, S K.
Afiliação
  • Singh M; Department of Farm Machinery and Power Engineering, Punjab Agricultural University, Ludhiana 141001, India.
  • Kumar R; Krishi Vigyan Kendra, Samrala, Punjab 141114, India.
  • Sharma A; Krishi Vigyan Kendra, Mansa, Punjab 151505, India.
  • Singh B; Department of Farm Machinery and Power Engineering, Punjab Agricultural University, Ludhiana 141001, India.
  • Thind SK; Department of Botany, Punjab Agricultural University, Ludhiana 141001, India.
ScientificWorldJournal ; 2015: 163968, 2015.
Article em En | MEDLINE | ID: mdl-25811039
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.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Triticum / Algoritmos / Nitrogênio Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2015 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Triticum / Algoritmos / Nitrogênio Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2015 Tipo de documento: Article