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Articles by Iosif GERGEN
Total Records ( 3 ) for Iosif GERGEN
  Monica HARMANESCU , Despina Maria BORDEAN and Iosif GERGEN
  Not available
  Monica HARMANESCU , Alexandru MOISUC , Veronica SARATEANU , Aurica BOROZAN and Iosif GERGEN
  The aim of this study was to perform a NIR calibration model for crude protein prediction of forages harvested in June 2009 from hill permanent grassland (Gradinari, Caras-Severin District) organized in ten experimental trials fertilized organic, mineral, and organo-mineral. The soil was Calcic Luvisol and the annual average temperature around 10.4°C. The floristic composition was determined gravimetrically. From Poaceae were present Festuca rupicola and Calamagrostis epigejos. Fabaceae family was represented by Trifolium repens and Lathyrus pratensis. From other botanical family: Rosa canina, Filipendula vulgaris, Galium verum and Inula britanica. Like input data was used the results for this parameter by Kjeldahl chemical method and the reflectance values from NIR spectra for analysed samples. Partial last square (PLS) regression was selected to perform the multivariate analysis to obtain the “NIR-CP” model, implemented in Panorama program (version 3, LabCognition, 2009). The statistical parameters (R2=0.8630; RMSEC=1.2844) and the differences between references and predicted values situated in range 0.03 - 1.73 % shows that it is promising to use this calibration model to evaluate the quality of forages from grassland in this period of year.
  Monica HARMANESCU , Alexandru MOISUC , Veronica SARATEANU , Marinel HORABLAGA , Aurica BOROZAN , Florina RADU and Iosif GERGEN
  In a permanent grassland agro-ecosystem the floristic composition varied depending on substances flow, soil nutrients availability and climatic conditions (Rotar, 1997; Moisuc et al., 2001). On the floristic composition of forages will depended its quality and the satisfaction of nutritive necessities of animal’s, in relationship with the final quality of row matter (Ammerman et al., 1995; Church&Pond, 1988). The aim of this study was to discuss how the fertilisation influences the floristic composition of hill permanent grassland in spring. Principal Components and Classification Analysis (PC&CA) technique implemented in Statistica 6 software was used to perform the statistical interpretation.
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