NITROGEN CYCLING, OPTIMIZATION OF PLANT NUTRITION AND REMOTE SENSING OF LEAF NUTRIENTS IN WILD BLUEBERRIES (VACCINIUM ANGUSTIFOLIUM AIT.)

Abstract

This thesis consists of three sections that provide detailed knowledge of nutrient estimation and management in wild blueberry production. The first section investigated the main and interactive effects of long term fertilizer (NPK) enrichments on soil mineral nitrogen, organic nitrogen and carbon, microbial biomass nitrogen and carbon, net mineralization and net nitrification in wild blueberry soils. The second section studied the optimization of wild blueberry growth, development, foliar nutrients and harvestable yields by using response surface methodology. The third section examined nutrient estimation technologies using field spectroscopy. The remote sensing data was analysed with a combination partial least squares regression and variable selection algorithms (Chemometric analysis). The results indicated elevated nitrification activity under nitrogen enrichments, mainly performed by heterotrophs, report unusually high levels of dissolved organic carbon (> 150 C ha-1), a fungal dominated soil system and high concentration of soluble organic nitrogen in the crop year of production. Nitrification and high dissolved organic carbon levels were observed in connection with possible nitrogen saturation and potential environmental hazards. The results imply a need for nitrification inhibition measures. Results from field studies examining the main and interactive effects of soil applied N, P and K suggested that applications of nitrogen (35 kg ha-1), phosphorus (40 kg ha-1) and potassium (30 kg ha-1) were required to optimize growth, development and harvestable yields of wild blueberry. Under these fertilizer rates, the corresponding predicted harvestable yield was 4,126 kg ha-1 that is as much as 13% higher than would be produced by commonly used fertilizer rate in the industry. This study presented new leaf nutrient ranges for sprout and crop years for wild blueberry fields in Atlantic Canada. Hyperspectral remote sensing technologies were used for estimating macro and micro nutrients. This study provides critical information on wavelengths important for nutrient estimation in reflectance spectra (400-2500 nm). The results and inferences from this thesis may be employed to improve crop production, increase economic returns and health of soil and sustainability of wild blueberry production in Nova Scotia.