Background and Aims Pollen limitation is most prevalent among bee-pollinated plants, self-incompatible plants, and tropical plants. However, we have very little understanding of the extent to which pollen limitation affects fruit set in mass-flowering trees despite tree crops accounting for at least 600 million tons of the 9,200 million tons of annual global food production. Methods We determined the extent of pollen limitation in a bee-pollinated, partially self-incompatible, subtropical tree by hand cross-pollinating the majority of flowers on mass-flowering macadamia (Macadamia integrifolia) trees that produce about 200,000–400,000 flowers. We measured tree yield and kernel quality and estimated final fruit set. We genotyped individual kernels by MassARRAY to determine levels of outcrossing in orchards and assess paternity effects on nut quality. Key Results Macadamia trees were pollen limited. Supplementary cross-pollination increased nut-in-shell yield, kernel yield and fruit set by as much as 97%, 109% and 92%, respectively. The extent of pollen limitation depended upon the proximity of experimental trees to trees of another cultivar because macadamia trees were highly outcrossing. Between 84% and 100% of fruit arose from cross-pollination, even at 200 m (25 rows) from orchard blocks of another cultivar. Large variations in nut-in-shell mass, kernel mass, kernel recovery and kernel oil concentration were related to differences in fruit paternity, including between self-pollinated and cross-pollinated fruit, thus demonstrating pollen-parent effects on fruit quality, i.e. xenia. Conclusions This study is the first to demonstrate pollen limitation in a mass-flowering tree. Improved pollination led to increased kernel yield of 0.31–0.59 tons per hectare, which equates currently to higher farm-gate income of approximately US3,720–US7,080 per hectare. The heavy reliance of macadamia flowers on cross-pollination and the strong xenia effects on kernel mass demonstrate the high value that pollination services can provide to food production.

Tree nuts play an important role in healthy diets, but their economic value and nutritional quality may be affected by their size and paternity. We assessed relationships between nut size and kernel recovery, the incidence of whole kernels, fatty acid composition and mineral nutrient concentrations in three macadamia cultivars, "Daddow", "816" and "A4". We determined to what extent differences in nut size and quality were the result of different levels of cross-or self-paternity. Small nuts of all cultivars had lower kernel recovery than large nuts, and small nuts provided lower incidence of whole kernels in "Daddow" and "A4". Small kernels had a lower relative abundance of the saturated fatty acid, palmitic acid, in all cultivars and higher relative abundance of the unsaturated fatty acid, oleic acid, in "Daddow" and "A4". Small kernels had higher concentrations of many essential nutrients such as nitrogen and calcium, although potassium concentrations were lower in small kernels. Most nuts arose from cross-pollination. Therefore, nut size and kernel quality were not related to different levels of cross-and self-paternity. Identified cross-paternity was 88%, 78% and 90%, and identified self-paternity was 3%, 2% and 0%, for "Daddow", "816" and "A4", respectively. Small macadamia kernels are at least as nutritious as large macadamia kernels. High levels of cross-paternity confirmed that many macadamia cultivars are predominantly outcrossing. Macadamia growers may need to closely inter-plant cultivars and manage beehives to maximise cross-pollination.Plants 2020, 9, 228 2 of 14 also a valuable source of calcium, iron and zinc, which can be absorbed insufficiently during phases of high dietary demand such as infancy, childhood, adolescence, pregnancy and breastfeeding [16][17][18][19][20][21].The fatty acid composition and nutrient concentrations of tree-nut kernels can vary greatly among cultivars [9,[22][23][24][25][26][27][28]. Fatty acid composition and nutrient concentrations can also vary within almond or pistachio cultivars because of differences in the pollen parentage of individual kernels [22][23][24][25]29,30]. For example, self-pollinated kernels of some almond cultivars have lower oleic:linoleic acid ratios than cross-pollinated kernels [25,29]. In addition, self-pollinated kernels of some almond, chestnut and hazelnut cultivars are smaller than cross-pollinated kernels [22,[31][32][33]. Such effects of the paternal genetic background on the size or quality of the embryo are termed "xenia", and xenic effects are common in fruit and nut crops [34]. Therefore, maximising both yield and human-health benefits may depend upon ensuring high levels of cross-pollination in tree-nut orchards.Relationships between kernel size, nutritional composition, and cross-or self-paternity are poorly understood for some nuts, including the subtropical tree nut, macadamia (Macadamia integrifolia, M. tetraphylla and hybrids). Macadamia flowers are bee-pollinated and partially self-incompatible [35][36][37][38][39][40][41][42]...

Many tree crops experience sub-optimal yields and low fruit quality due to inadequate pollination, low fruit set, and poor crop nutrition. Boron (B) is a critical crop nutrient for fruit set because B levels affect pollen germination and pollen tube growth. However, the relationship between floral B concentration and fruit set is not well understood. The aim of this study was to determine the effect of B applications on the initial fruit set, yield, quality, and paternity of macadamia (Macadamia integrifolia). Cultivar ‘816’ trees received one of three treatments: (a) 0 g, (b) 15 g, or (c) 30 g B per tree prior to flowering. Boron application increased the B concentration of macadamia flowers. Application of 15 g B increased fruit set at 3 weeks after peak anthesis, but this higher initial fruit set was not translated into higher fruit set at 6 or 10 weeks after peak anthesis or higher yield. Boron application increased B concentrations in kernels but did not affect nut-in-shell (NIS) mass, kernel mass, kernel recovery, kernel oil concentration or incidence of whole kernels. Cultivar ‘816’ was highly outcrossing, with 97–98% cross-paternity among kernels from all treatments. Our results indicate that higher B concentration in macadamia flowers can be associated with an increased initial fruit set. However, high B levels did not affect yield, nut quality, or the proportion of self-pollinated fruit at maturity. The heavy dependence on outcrossing highlights the importance of inter-planting different cultivars and managing bee hives to sustain the productivity of macadamia orchards.

Tree crop yield is highly dependent on fertiliser inputs, which are often guided by the assessment of foliar nutrient levels. Traditional methods for nutrient analysis are time-consuming but hyperspectral imaging has potential for rapid nutrient assessment. Hyperspectral imaging has generally been performed using the adaxial surface of leaves although the predictive performance of spectral data has rarely been compared between adaxial and abaxial surfaces of tree leaves. We aimed to evaluate the capacity of laboratory-based hyperspectral imaging (400–1000 nm wavelengths) to predict the nutrient concentrations in macadamia leaves. We also aimed to compare the prediction accuracy from adaxial and abaxial leaf surfaces. We sampled leaves from 30 macadamia trees at 0, 6, 10 and 26 weeks after flowering and captured hyperspectral images of their adaxial and abaxial surfaces. Partial least squares regression (PLSR) models were developed to predict foliar nutrient concentrations. Coefficients of determination (R2P) and ratios of prediction to deviation (RPDs) were used to evaluate prediction accuracy. The models reliably predicted foliar nitrogen (N), phosphorus (P), potassium (K), calcium (Ca), copper (Cu), manganese (Mn), sulphur (S) and zinc (Zn) concentrations. The best-fit models generally predicted nutrient concentrations from spectral data of the adaxial surface (e.g., N: R2P = 0.55, RPD = 1.52; P: R2P = 0.77, RPD = 2.11; K: R2P = 0.77, RPD = 2.12; Ca: R2P = 0.75, RPD = 2.04). Hyperspectral imaging showed great potential for predicting nutrient status. Rapid nutrient assessment through hyperspectral imaging could aid growers to increase orchard productivity by managing fertiliser inputs in a more-timely fashion.