Wild blueberry (V. angustifolium) is well adapted to orthic humo-ferric podzols. These soils are typically sandy, acidic (pH 3.9–5.5), highly leached, poorly buffered with well-developed organic horizons. Podzols are not naturally fertile. However, these soils can become quite productive with proper fertilizer applications. In Nova Scotia (Canada), commercial growers apply fertilizers in a form of diammonium phosphate or ammonium sulfate in combination with P and K at rate of 20 kg·ha−1 N, 10 kg·ha−1 P, and 15 kg·ha−1 K at the onset of shoot emergence from rhizomes in the sprout year of the production cycle (personal observations).
The extensive root and rhizome system in wild blueberry occurs within the top 10 cm of soil and accounts for 75% to 85% of the total plant dry weight (Jeliazkova and Percival, 2003). The rhizomes serve as a reservoir for nitrogenous compounds as well as carbohydrates and some inorganic constituents particularly N, P, and magnesium (Townsend et al., 1968). The numerous fine, hair roots are heavily colonized by indigenous ericoid mycorrhizal fungi that assist with nutrient uptake notably N and P and the acquisition of nutrients from organic sources that are normally unavailable to host plant roots (Read et al., 2004). The boreal forest species have been known to uptake organic N forms irrespective of different type of roots (Näsholm et al., 1998; Persson and Näsholm, 2001), and indirect evidence suggests that wild blueberry utilizes organic N (Maqbool, 2014).
Wild blueberry nutrient management varies considerably compared with typical tilled crop systems. Berries are removed from the fields every 2 years (cropping cycle) while extensive plant debris deposition to fields occurs in every production cycle in the form of leaf drop in fall and every 2 years in the form of pruning when the plants are mowed after harvest. As a result, wild blueberry soils contain as much as 10% organic matter (Kinsman, 1993). The wild blueberry fields have a fungal dominated soil system that promotes a slow cycling of nutrients and a low availability of nutrients. Nutrients tied in the organic matter are slowly available to plants through mineralization and nitrification is slow under low pH conditions typical of wild blueberry soils (Kinsman, 1993). Therefore, ammonium is the dominant form of N present in wild blueberry soils and P may not be readily available to plants due to the soils high acidity. Since irrigation is rarely used, blueberry plants are occasionally (1–3 years in a decade) exposed to drought which may significantly reduce berry yield by affecting floral bud development, berry weight, mineralization rates, and fertilizer response. The dynamic nature of interactions among plant and soil factors results in tremendous amount of uncertainty in wild blueberry nutrient management (Percival and Sanderson, 2004).
Plant growth and development (shoot number and fruit development) can almost double when ammonium is used instead of nitrate N (Cain, 1952; Townsend, 1969). Studies have also reported toxic effects of nitrate N on blueberries (Cain, 1952).
Fertilization generally promotes floral nodes, fruit set, and berry yield (Percival and Sanderson, 2004). For example, application of N (43 kg·ha−1) in the form of urea produced 22% more flower buds per stem and 25% more yield over unfertilized plants (Smagula and Hepler, 1978). However, an excess of N applied in the sprout year may reduce yield by promoting vegetative growth, increasing weed growth, causing micronutrient imbalances, increasing susceptibility to winter injury (excessively tall stems), or stimulating an overproduction of flower buds relative to the nutrient budget in the crop year (Benoit et al., 1984; Penney and McRae, 2000; Smagula, 1999; Yarborough et al., 1986). Yet, in Maine, high N application rates (20–98 kg·ha−1) increased stem length, flower buds, number of berries, and yield (Smagula and Dunham, 1995; Smagula and Hepler, 1978; unpublished data). The impact of N applications on berry yield has been inconsistent, with studies reporting yield gains (Ismail et al., 1981; Percival et al., 2003; Smagula and Hepler, 1978), yield reductions (Penney and McRae, 2000; Smagula and Ismail 1981), or no effect (Benoit et al., 1984; Blatt, 1993).
Variable responses in soil-applied P and K have also been reported. P can either significantly increase berry yield (Smagula and Dunham, 1995) or have no effect on yield potential as expressed in buds per stem) (Eaton et al., 1997). K was found to increase yield and berry size up to 40 kg·ha−1 K with no additional response occurring at higher rates (Eck, 1983). Percival and Sanderson (2004) found significant effects of soil-applied N and K for fruit set on Kemptown site, and soil-applied K on Mount Vernon site despite large levels of inherent phenotypic variability. They also reported that the harvestable yield of the unfertilized treatments was as much as 36% lower than the other soil-applied N–P–K treatments at Mount Vernon. One limitation from the previous studies was that fertilizer treatments were not varied across the entire range and mostly one or two nutrients were studied thus ignoring the full spectrum of interactions when applying nutrients from deficiency to over saturation levels.
The first objective of this research was to determine the main and interactive effects of soil-applied N–P–K fertilizers on wild blueberry growth, development, and berry yield while the second objective was to recommend fertilizer rates that optimize these same factors. We chose to use response surface methodology and canonical analysis as aids in modeling and examining the relationships between fertilizer rates and plant responses. The central composite design (CCD), the most efficient design for response surface analysis, considers several factors simultaneously, and allows the determination of the interactions among factors using a smaller number of experiments (Myers et al., 2009). This methodology has been used by others to describe the effects of fertilization on plant growth. For example, Lippke et al. (2006) evaluated soil-applied fertilizers (N and P) on annual ryegrass (Lolium multiflorum Lam.). The fitted response surface models provided optimum N and P levels for maximum dry matter yield. Sanchez (2000) used response surface methods with quadratic models to examine the effect of water and N on lettuce (Lactuca sativa L.). In this study, it was used to determine the optimum levels of soil-applied N–P–K fertilizers that could maximize yield and potential yield factors.
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