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  • Author or Editor: R. Marini x
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The objectives of this experiment were to test the efficacy of a mechanical string thinner (Darwin PT-250; Fruit-Tec, Deggenhauserertal, Germany) on apple and to identify an optimal range of thinning severity as influenced by spindle rotation speed. Trials were conducted in 2010 and 2011 at the Pennsylvania State University Fruit Research and Extension Center in Biglerville, PA, on five-year-old ‘Buckeye Gala’/M.9 apple trees that were trained to tall spindle. A preliminary trail on five-year-old ‘Cripps Pink’/M.9 was conducted to determine the relationship between string number and thinning severity. As the number of strings increased, the level of thinning severity increased. A range of spindle speeds (0 to 300 rpm) was applied to the same trees for two consecutive years. As spindle speed increased, blossom density (blossom clusters per limb cross-sectional area) was reduced as was the number of blossoms per spur. In 2010, leaf area per spur was reduced 9% to 45%. In 2011, the fastest spindle speed reduced leaf area per spur 20%. Although increased spindle speed reduced cropload, injury to spur leaves may have inhibited increases in fruit size. The largest gain in fruit weight was 28 g (300 rpm) compared with the control. In both years, the most severe thinning treatments reduced yield by more than 50%. There was no relationship between spindle speed and return bloom. Severe thinning treatments (240 to 300 rpm) caused significant reductions in spur leaf area, yield, and fruit calcium and did not improve fruit size or return bloom. Spindle speeds of 180 and 210 rpm provided the best overall thinning response and minimized injury to spur leaves, but cropload reduction was insufficient in years of heavy fruit set. Therefore, mechanical blossom thinning treatments should be supplemented with other thinning methods. Mechanical string thinning may be a viable treatment in organic apple production, where use of chemical thinners is limited.

Free access

Abstract

During a 6-week fruiting cycle of a day-neutral strawberry, (Fragaria × ananassa Duch. cv. Hecker), net photosynthesis (Pn) was significantly greater on fruiting plants than deblossomed plants on 5 of 6 measurement dates. The presence of fruit did not affect dark respiration (Rd). Pn tended to decline during the fruiting cycle while Rd tended to increase. Removal of inflorescences from fruiting plants resulted in a significant decline in Pn while Rd was unaffected.

Open Access

The effect of nighttime ozone (O3) exposure, alone and in combination with daytime O3 treatment, was tested on yield of an O3-resistant (R123) and an O3-sensitive (S156) snap bean (Phaseolus vulgaris L.) genotype. Three trials, with exposure durations ranging in length from 14 to 21 days, were conducted in continuous stirred tank reactors located within a greenhouse. The effects of day-only (0800–1900 hr = 11 hours·day−1) and day + night (0800–1900 hr + 2000–0700 hr = 22 hours·day−1) exposure timings were compared. The Fall 2014 trial also tested the effect of nighttime-only (2000–0700 hr = 11 hours·day−1) O3 exposure. Nighttime O3 exposure alone, at 62 ppb, did not cause foliar injury and had no effect on the yield of either genotype. In combination with daytime O3 exposure, nighttime O3 concentrations up to 78 ppb did not impact yields or show a consistent effect on nocturnal stomatal conductance (g sn). When data were pooled across the day and day + night exposures times, mean daytime O3 levels ≥62 ppb caused foliar injury and significant yield decreases in all three trials. Under control conditions, R123 and S156 produced similar pod masses in two of the three trials. In all three trials, R123 produced significantly greater yields by mass than S156 with elevated O3. Nighttime conductance measurements suggested that S156 and R123 have inherently different g sn rates and that cumulative O3 exposure can increase g sn in both genotypes.

Free access

During a 3-year study of bitter pit in commercial ‘Honeycrisp’ apple (Malus ×domestica) orchards, incidence was associated with low calcium (Ca) levels in fruit peel; high ratios of nitrogen (N), potassium (K), and/or magnesium (Mg) to Ca in fruit peel; excessive terminal shoot length; and low crop load. Peel N and Mg concentrations were negatively correlated and peel Ca concentration positively correlated with crop density (CD). Shoot length (SL) was not consistently correlated with peel N, Mg, or phosphorus (P) and was negatively correlated with only Ca. A two-variable model that included SL and the ratio of N to Ca explained more than 65% of bitter pit incidence. The model has implications for best management of the cultivar in the field and during storage.

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In three experiments, diameters of apples representing 7% to 30% of the fruit on a tree were measured at ≈60 days after full bloom. Using previously published regression equations, the early-season fruit diameter values were used to estimate apple fruit weight at harvest (FWH). At harvest, all fruit on sample trees were weighed and the distributions of estimated FWH for fruit measured early in the season were compared with distributions of the actual FWH for whole trees. Actual FWH was normally distributed for only one of the three experiments. Although the estimated mean FWH averaged for the 10 trees was within 9% of the actual mean FWH for all three experiments, the distribution of estimated FWH differed significantly from the actual distribution for all three experiments. All fruit were then assigned to appropriate commercial fruit sizes or box counts (number of fruit/19.05 kg). Fruit size tended to peak on the same four box counts for the estimated and actual populations, but the estimated populations had too few fruits in the small- and large-size box counts. Using early-season estimates of FWH, commercial apple growers and packers can predict fairly accurately the percentage of the crop that will fall into the peak box counts, but a more accurate early-season estimate of the fruit size distribution will likely require measuring 50% of the fruit on a tree.

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‘Honeycrisp’ (Malus ×domestica) apples were harvested from a total of 17 mid-Atlantic orchards during 2018 and 2019 to verify a previously published bitter pit prediction model. As in the previous study, bitter pit incidence was associated with low calcium (Ca) levels and high ratios of nitrogen (N), potassium (K), and/or magnesium (Mg) to Ca in the fruit peel and excessive terminal shoot growth. The best two-variable model for predicting bitter pit developed with the 2018–19 data set contained boron (B) and the ratio of Mg to Ca (R 2 = 0.83), which is different from previous models developed with data from three individual years (2015–17). When used to predict the bitter pit incidence of the 2018–19 data, our previous best model containing the average shoot length (SL) and the ratio of N to Ca underestimated the incidence of bitter pit. The model is probably biased because one or more important variables related to bitter pit have not yet been identified. However, the model is accurate enough to identify orchards with a low incidence of bitter pit.

Open Access

Canopies of ‘Gala’ and ‘Fuji’ trees, trained to the vertical axis, were divided into eight vertical sections, each representing 12.5% of the tree canopy. The diameter of all ‘Gala’ fruit and fruit weight for all ‘Fuji’ fruit were recorded for each canopy section. Fruit size from most canopy sections was normally distributed and distributions were similar for most sections. Therefore, fruit size distribution for a tree can be estimated by harvesting fruit from two sections of a tree, representing 25% of the canopy. For small trees in intensive plantings, with canopy diameters less than 2.0 m, average fruit diameter or fruit weight estimated from all fruit collected from 25% of the canopy may provide estimates within 7% of the true value.

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Effects of nighttime (2000 to 0700 hr) O3 on the pod mass of sensitive (S156) and resistant (R123) snap bean (Phaseolus vulgaris) genotypes were assessed using continuous stirred tank reactors located within a greenhouse. Two concentration-response relationship trials were designed to evaluate yield response to nighttime O3 exposure (10 to 265 ppb) in combination with daytime exposure at background levels (44 and 62 ppb). Three replicated trials tested the impact of nighttime O3 treatment at means of 145, 144, and 145 ppb on yields. In addition, stomatal conductance (g S) measurements documented diurnal variations and assessed the effects of genotype and leaf age. During the concentration-response experiments, pod mass had a significant linear relationship with the nighttime O3 concentration across genotypes. Yield losses of 15% and 50% occurred at nighttime exposure levels of ≈45 and 145 ppb, respectively, for S156, whereas R123 yields decreased by 15% at ≈150 ppb. At low nighttime O3 levels of ≈100 ppb, R123 yields initially increased up to 116% of the treatment that received no added nighttime O3, suggesting a potential hormesis effect for R123, but not for S156. Results from replicated trials revealed significant yield losses in both genotypes following combined day and night exposure, whereas night-only exposure caused significant decreases only for S156. The g S rates ranged from less than 100 mmol·m−2·s−1 in the evening to midday levels more than 1000 mmol·m−2·s−1. At sunrise and sunset, S156 had significantly higher g S rates than R123, suggesting a greater potential O3 flux into leaves. Across genotypes, younger rapidly growing leaves had higher g S rates than mature fully expanded leaves when evaluated at four different times during the day. Although these were long-term trials, g S measurements and observations of foliar injury development suggest that acute injury, occurring at approximately the time of sunrise, also may have contributed to yield losses. To our knowledge, these are the first results to confirm that the relative O3 sensitivity of the S156/R123 genotypes is valid for nighttime exposure.

Open Access

Early-season fruit diameter measurements for ‘Gala’, ‘Fuji’, and ‘Honeycrisp’ apples in three orchards for 3 years were used to develop regression models to estimate fruit weight at harvest. Fruit weight at harvest was linearly related to fruit diameter 60 days after bloom, but intercepts and slopes were not homogeneous for all nine combinations of orchards and years for any of the cultivars. When the entire data set for a cultivar was used to develop a single predictive model, the model was biased and underpredicted fruit weight for small fruit and overpredicted fruit weight for large fruit. Adding the ratio of (fruit weight/fruit diameter) at 60 days after bloom to the model with fruit diameter at 60 days after bloom produced a less-biased model with improved coefficients of determination, and predicted values were more similar to the observed values. The (fruit weight/fruit diameter) ratio was positively related to cumulative growing degree days for the 60 days before the fruit were measured and tended to be lower in years when fruits were exposed to frosts. These multiple regression models can be used to develop tables with predicted fruit weights at harvest for varying combinations of fruit diameter and (fruit weight/fruit diameter) ratio 60 days after bloom.

Free access

‘Honeycrisp’ is a popular apple cultivar, but it is prone to several disorders, especially bitter pit. Previously reported models for predicting bitter pit are biased, indicating that the models are missing one or more important predictor variables. To identify additional variables that may improve bitter pit prediction, a study was undertaken to investigate the influence of canopy position, spur characteristics, and individual fruit characteristics on bitter pit development. ‘Honeycrisp’ trees from two orchards over 2 years provided four combinations of orchards and years. Fruits were sampled from spurs at different canopy positions and with varying bourse shoot lengths and numbers of fruits and leaves. Following cold storage, bitter pit was assessed in three ways: 1) bitter pit severity was recorded as the number of pits per fruit, 2) bitter pit was recorded as a binomial response (yes, no) for each fruit, and 3) the incidence of bitter pit was recorded as the proportion of fruit developing bitter pit. As a result of the high fruit-to-fruit variation, bitter pit severity was associated with canopy position or spur characteristics to a lesser extent than bitter pit incidence. Bitter pit incidence was generally greater for fruits developing on spurs with only one fruit and spurs from the lower canopy. Binomial data were analyzed with a generalized linear mixed model. Fruit harvested from trees with heavy crop loads, and those developing on spurs with multiple fruit and spurs with long bourse shoots had the lowest probability of developing bitter pit. Regardless of how bitter pit was assessed, bitter pit related positively to fruit weight (FW), but the relationship usually depended on other variables such as canopy position, fruit per spur, and leaves per spur. The advantages of fitting binomial data with logistic regression models are discussed.

Open Access