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     Advance Journal of Food Science and Technology

    Abstract
2015(Vol.7, Issue:4)
Article Information:

Nutritional Diagnosis for Apple by DRIS, CND and DOP

Min Xu, Jianing Zhang, Faqi Wu and Xudong Wang
Corresponding Author:  Xudong Wang 
Submitted: July ‎18, ‎2014
Accepted: September ‎20, ‎2014
Published: February 10, 2015
Abstract:
This study derived and compared norms for apple, using the Diagnosis and Recommendation Integrated System (DRIS), Compositional Nutrient Diagnosis (CND) and deviation form optimum percentage (DOP) diagnose methods in the Weibei Loess Plateau, Shaanxi Province, China. A total of 68 leaf samples were collected from apple trees grown in Huangshan soils. The nutritional status was diagnosed by the DRIS, CND and DOP methods. The CND norms expressed as row-centered log ratios (mean±standard deviation) for d = 5 nutrients for the high-yield subpopulation (producing more than 46.67 t/ha) were: VN*= 0.998±0.066, VP* = -1.499±0.124, VK* = -0.189±0.283, Vca* = 0.217±0.213, VMg* = -1.035±0.267, VR5 * = 1.508±0.144. The optimum ranges for leaf nutrient concentrations were: N = 27.23±1.79 g/kg, P = 2.26±0.32 g/kg, K = 8.63±2.50 g/kg, Ca = 12.73±2.66 g/kg, Mg = 3.71±1.12 g/kg, R5 = 45.44±3.95 g/kg. The regression relating CND to DRIS and DOP indices were significant linear. There was a multinomial regression equation between CND r2 and DRIS NBI, also between CND r2 and ∑DOP. This study showed that the differences in CND, DRIS and DOP approaches did not lead to large differences in identified deficiencies. So, CND may in practice still be the preferred approach since multivariate methods could be further explored to assess nutrient status in plants, but people can choose any approach they want use since they had the similar evaluation result.

Key words:  Apple, CND, DOP, DRIS, leaf diagnosis, weibei loess plateau,
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Cite this Reference:
Min Xu, Jianing Zhang, Faqi Wu and Xudong Wang, . Nutritional Diagnosis for Apple by DRIS, CND and DOP. Advance Journal of Food Science and Technology, (4): 266-273.
ISSN (Online):  2042-4876
ISSN (Print):   2042-4868
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