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John A. Barden and Richard P. Marini

Productivity of perennial fruit plants depends to a sizeable degree on partitioning of assimilates between vegetative and reproductive structures. Cultivars and rootstocks modify the partitioning pattern, but there are very few data published on these relationships. The termination of a long-term evaluation of standard-growing and spur-type strains of `Delicious' and `Golden Delicious' on several dwarf and semi-dwarf rootstocks and interstocks provided an excellent opportunity to assess the relationships among cumulative yield, scion weight, and trunk cross-sectional area (TCA). Cultivars were `Goldspur' and `Smoothee' strains of `Golden Delicious' and `Redchief' and `Red Prince' strains of `Delicious'. Rootstocks and interstocks included Malling 9 (M.9), M.26, M.9/Malling Merton 106 (MM.106), M.9/MM.111, M.7, MM.106, and MM.111. Row spacing was standard at 6.1 m. Tree spacing varied with anticipated vigor and ranged from 1.8 to 5.5 m. Pruning times and weight of prunings were recorded in two years. After 18 years, trees were cut off just above the soil line and weighed. TCA and scion weight were highly correlated despite of considerable differences in degree of containment pruning required, and cumulative yields were well correlated with both TCA and scion weight. The ratio of cumulative crop weight to final scion weight decreased quadratically with increasing TCA. Pruning times and weight of prunings were somewhat better correlated with TCA in `Delicious' than in `Golden Delicious'.

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Charles G. Embree, Marina T.D. Myra, Douglas S. Nichols, and A. Harrison Wright

, 1954 ; Singh, 1948 ; Tromp, 2000 ), stimulate tree growth, and increase fruit size ( McArtney et al., 1996 ). For many cultivars, the optimal crop load is between 5 and 6 fruit/cm −2 trunk cross-sectional area (TSCA) ( Robinson and Watkins, 2003

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Carlos Miranda Jiménez and J. Bernardo Royo Díaz

Spring frosts are usual in many of Spain's fruit-growing areas, so it is common to insure crops against frost damage. After a frost, crop loss must be evaluated, by comparing what crop is left with the amount that would have been obtained under normal conditions. Potential crop must be evaluated quickly through the use of measurements obtainable at the beginning of the tree's growth cycle. During the years 1997 through 1999 and in 86 commercial plots of peach and nectarine [Prunus persica (L.) Batsch], the following measurements were obtained: trunk cross-sectional area (TCA, cm2), trunk cross sectional area per hectare (TCA/ha), estimated total shoot length per trunk cross-sectional area (SLT, shoot m/cm2 TCA), crop density (CD, amount of fruit/cm2 TCA), fruit weight (FW, g), yield efficiency (YE, kg of fruit/cm2 TCA), yield per tree (Y, kg fruit/tree) and days between full bloom and harvest (BHP, days). CD and average FW were related to the rest of the variables through the use of multiple regression models. The models which provided the best fit were CD = SLT - TCA/ha and FW = SLT + BHP - CD. These models were significant, consistent, and appropriate for all three years. The models' predictive ability was evaluated for 32 different plots in 2001 and 2002. Statistical analysis showed the models to be valid for the forecast of orchards' potential yield efficiency, so that they represent a useful tool for early crop prediction and evaluation of losses due to late frosts.

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Carlos Miranda Jiménez and J. Bernardo Royo Díaz

Spring frosts are usual in many of Spain's fruit-growing areas, so it is common to insure crops against frost damage. After a frost, crop loss must be evaluated, by comparing what crop is left with the amount that would have been obtained under normal conditions. Potential crop must be evaluated quickly through the use of measurements obtainable at the beginning of the tree's growth cycle. During the years 1998 and 1999 and in 62 commercial plots of `Golden Delicious' and `Royal Gala' apple (Malus ×domestica Borkh.), the following measurements were obtained: trunk cross-sectional area (TCA, cm2), space allocated per tree (ST, m2) trunk cross-sectional area per hectare (TCA/ha), flower density (FD, number of flower buds/cm2 TCA), flower density per land area (FA, number of flower buds/m2 land area), cluster set (CS, number of fruit clusters/number of flower clusters, percent), crop density (CD, number of fruit/cm2 TCA), fruit clusters per trunk cross-sectional area (FCT, number of fruit clusters/cm2 TCA), fruit clusters per land area (FCA, number of fruit clusters/m2 land area), fruit number per cluster (FNC), average fruit weight (FW, g), average yield per fruit cluster (CY, g), yield efficiency (YE, fruit g·cm-2 TCA), and tree yield (Y, fruit kg/tree). FCT and average CY were related to the rest of the variables through the use of multiple regression models. The models which provided the best fit were FCT = FD - TCA/ha - FD and CY= -FCA - FCT. These models were significant, consistent, and appropriate for both years. Predicted yield per land area was obtained by multiplying TCA/ha × FCT × CY. The models' predictive ability was evaluated for 64 different plots in 2001 and 2002. Statistical analysis showed the models to be valid for the forecast of potential yields in apple, so that they represent a useful tool for early crop prediction and evaluation of losses due to late frosts.

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Carlos Miranda Jiménez and J. Bernardo Royo Díaz

Spring frosts are usual in many of Spain's fruit-growing areas, so it is common to insure crops against frost damage. After a frost, crop loss must be evaluated, by comparing what crop is left with the amount that would have been obtained under normal conditions. Potential crop must be evaluated quickly through the use of measurements obtainable at the beginning of the tree's growth cycle. During 1996 and 1997 and in 95 commercial plots of `Blanquilla' and `Conference' pear (Pyrus communis L.), the following measurements were obtained: trunk cross-sectional area (TCA, cm2), space allocated per tree (ST, m2), trunk cross-sectional area per hectare (TCA/ha), flower density (FD, number of flower buds/cm2 TCA), flower density per land area (FA, number of flower buds/m2 land area), cluster set (CS, number of fruit clusters/number of flower clusters, %), crop density (CD, number of fruit/cm2 TCA), fruit clusters per trunk cross-sectional area (FCT, number of fruit clusters/cm2 TCA), fruit clusters per land area (FCA, number of fruit clusters/m2 land area), fruit number per cluster (FNC), average fruit weight (FW, g), average yield per fruit cluster (CY, g), yield efficiency (YE, fruit g·cm-2 TCA), and tree yield (Y, fruit kg/tree). CS and average CY were related to the rest of the variables through the use of multiple regression models. The models that provided the best fit were CS = TCA/ha - FA and CY = -FA - FCT. These models were significant, consistent, and appropriate for both years. Predicted yield per land area was obtained by multiplying FA × CS × CY. The models' predictive ability was evaluated for 46 different plots in 2001 and 2002. Statistical analysis showed the models to be valid for the forecast of orchards' potential yield efficiency, so that they represent a useful tool for early crop prediction and evaluation of losses due to late frosts.

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Chenggang Wang, Rolf Färe, and Clark F. Seavert

In this paper we analyze the sources of variation in revenue per unit of trunk cross-sectional area (TCA) across a 0.87-ha block of 272 pear (Pyrus communis L.) trees in 2003. Revenue capacity efficiency associated with TCA provides an overall measure of nutrient deficiency and revenue inefficiency caused by environmental constraints in the fruit production process. Data envelopment analysis (DEA) is adopted to estimate revenue capacity efficiency and its components. The deficiencies of macro- and micronutrients are measured and optimal nutrient levels computed for each individual tree. These measures are aggregated for comparing between grids and between rootstocks.

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Peter M. Hirst and David C. Ferree

Two-year-old branch sections of `Starkspur Supreme Delicious' apple (Malus domestics Borkh.) trees growing on 17 rootstock were studied over 6 years to determine the effects of rootstock on shoot morphology and spur quality and describe how these factors may be related to precocity and productivity. Shoot length was affected by rootstock and was positively related to trunk cross-sectional area within each year, but the slope of the regression line decreased as trees matured. The number of spurs on a shoot was largely a product of shoot length. Spur density was inversely related to shoot length, where rootstock with longer shoots had lower spur densities. Flower density was not related to spur density, and shoot length only accounted for a minor part of the variation in flower density. The proportion of spurs that produced flowers was closely related to flower density, indicating that rootstock influence flower density by affecting the development of individual buds rather than by the production of more buds. More vigorous rootstock generally had spurs with larger individual leaves and higher total leaf area per spur, but fewer spur leaves with lower specific leaf weights. More precocious rootstock were also more productive over a 10-year period when yields were standardized for tree size. Tree size was the best indicator of precocity and productivity, which could be predicted with a high degree of certainty as early as the 4th year.

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Frank Kappel, Michel Bouthillier, and Rob Brownlee

`Sweetheart' sweet cherry trees (Prunus avium L.) were summer-pruned for four summers (1991-94) either before or after harvest and at two levels, removing 1/3 or 2/3 of current-season growth by heading cuts. In an additional postharvest treatment, some current-season growth was removed by thinning cuts. The preharvest 1/3 treatment had the highest cumulative yield during the experiment. Higher yields were obtained following preharvest than postharvest treatments, and following less severe treatments (removing 1/3 of current-season growth) than more severe (removing 2/3) treatments. These increased yields were for the early stages of orchard production. Average fruit mass was not affected by any of the treatments. The summer-pruned trees had smaller trunk cross-sectional area (TCSA) increments over the trial and their final TCSA was smaller than that of the control trees.

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Richard C. Funt, Mark C. Schmittgen, and Glen O. Schwab

The performance of peach trees [Prunus persica (L.) Batsch cv. Redhaven/Siberian C.] on raised beds as compared to the conventional flat (unraised) orchard floor surface was evaluated from 1982 to 1991. The raised bed was similar to the flat bed in cation exchange capacity (CEC), Ca, P, K, Mg, B, and Zn soil levels in the 0-15 cm depth. Microirrigation, using two 3.7 L.h-1 emitters per tree vs. no irrigation, was applied to trees planted in a north-south orientation on a silt loam, noncalcareous soil. Raised beds increased trunk cross-sectional area (TCA) and yield-efficiency over 5 years. Irrigation increased fruit mass mostly in years of highest evaporation. Significant year to year variations occurred in yield, fruit mass, TCA and yield efficiency. There were significant bed × year interactions for yield and TCA. Irrigation increased leaf boron content regardless of bed type. Leaf potassium was higher in flat beds. Nonirrigated trees had the lowest tree survival on the flat bed, but the opposite was true on the raised bed.

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W.A. Retzlaff, L.E. Williams, and T.M. DeJong

Nursery stock of plum (Prunus salicina Lindel., `Casselman') was planted 1 Apr. 1988 in an experimental orchard at the Kearney Agricultural Center, Univ. of California, near Fresno. The trees were enclosed in open-top fumigation chambers on 1 May 1989 and exposed to three atmospheric ozone partial pressures (charcoal-filtered air, ambient air, and ambient air + ozone) from 8 May to 15 Nov. 1989 and from 9 Apr. to 9 Nov. 1990. Trees grown outside of chambers were used to assess chamber effects on tree performance. The mean 12-hour (0800-2000 hr Pacific Daylight Time) ozone partial pressures during the 2-year experimental period in the charcoal-filtered, ambient, ambient + ozone, and nonchamber treatments were 0.044, 0.059, 0.111, and 0.064 μPa·Pa-1 in 1989 and 0.038, 0.050, 0.090, and 0.050 pPa·Pa-1 in 1990, respectively. Leaf net CO2 assimilation rate of `Casselman' plum decreased with increasing atmospheric ozone partial pressure from the charcoal-filtered to ambient + ozone treatment. There was no difference in plum leaf net CO2 assimilation rate between the ambient chamber and nonchamber plots. Trees in the ambient + ozone treatment had greater leaf fall earlier in the growing season than those of the other treatments. Cross-sectional area growth of the trunk decreased with increasing atmospheric ozone partial pressures from the charcoal-filtered to ambient + ozone treatment. Yield of plum trees in 1990 was 8.8, 6.3, 5.5, and 5.5 kg/tree in the charcoal-filtered, ambient, ambient + ozone, and nonchamber treatments, respectively. Average fruit weight (grams/fruit) was not affected by atmospheric ozone partial pressure. Fruit count per tree decreased as atmospheric ozone partial pressure increased from the charcoal-filtered to ambient + ozone treatment. Decreases in leaf gas exchange and loss of leaf surface area were probable contributors to decreases in trunk cross-sectional area growth and yield of young `Casselman' plum trees during orchard establishment.