scholarly journals Optimizing Peach Tree Canopy Architecture for Efficient Light Use, Increased Productivity and Improved Fruit Quality

Agronomy ◽  
2021 ◽  
Vol 11 (10) ◽  
pp. 1961
Author(s):  
Brendon M. Anthony ◽  
Ioannis S. Minas
Keyword(s):  
Fruit Quality ◽  
Maximum Yield ◽  
Light Interception ◽  
High Density ◽  
Tree Canopy ◽  
Light Distribution ◽  
Yield Potential ◽  
Canopy Architecture ◽  
Training Systems ◽  
Cost Of Production

Peach production in the USA has been in decline in recent decades due to poor fruit quality, reduced consumption and increased cost of production. Productivity and fruit quality can only be enhanced in the orchard through optimizing preharvest factors such as orchard design and training systems. Transition from low-density plantings (LDP) to high-density plantings (HDP) in peach is associated with the availability of reliable size controlling rootstocks. Increased densities must be combined with modern training systems to diffuse vigor and further increase light interception and yields, while optimizing light distribution, fruit quality and cost of production. Several training systems have been tested in peach with various objectives and goals, such as increasing light, water use and labor efficiencies, along with designing canopy architectures to facilitate mechanization and robotics. In general, increased planting densities increase yields, but excessive densities can promote shade, while excessive crop load can deteriorate quality. An ideal peach cropping system should optimize light interception and light distribution to balance maximum yield potential with maximum fruit quality potential. Successful management of high-density peach fruiting wall systems can lead to enhanced and uniform fruit quality, and ensure a sustainable industry.

scholarly journals High efficiency sweet cherry orchard systems research

Italus Hortus ◽  
2019 ◽  
Vol 26 ◽  
pp. 25-34
Author(s):  
Gregory A. Lang
Keyword(s):  
Fruit Quality ◽  
Sweet Cherry ◽  
Three Dimensional ◽  
Light Interception ◽  
Training System ◽  
Crop Damage ◽  
Yield Potential ◽  
Training Systems ◽  
Systems Research ◽  
Sweet Cherries

The large tree size, and delicate nature and small size of the fruit, makes production of sweet cherries Fig. 6 - Planar UFO sweet cherry canopy architectural orchard designs: A) vertical-trellis UFO with 18,725 upright leaders per ha or B) Vtrellis UFO with 24,996 inclined leaders per ha, in theory with 33% higher yield potential, but slightly less training, harvest and pruning efficiency. Fig. 6 - Progettazione dell’architettura della chioma in piano “UFO” su ciliegio dolce: A) sostegni verticali per UFO con 18725 fusti verticali per ha o B) sostegno a V per UFO con 24996 fusti inclinati per ha, in teoria con il 33% in più di potenziale produttivo, ma leggermente meno per quanto riguarda efficienza di allevamento, raccolta e potatura. A B Lang 34 among the most traditionally labor-intensive tree fruits. Great improvements in orchard efficiencies have been achieved over the past two decades, prompted by the development of precocious, vigorcontrolling rootstocks such as the Gisela (Gi) series. Recent training systems research has focused on canopy architectural designs that improve various orchard efficiencies, including: 1) light interception and distribution whit minimization of shade; 2) bloom, fruit development and ripening for more uniform fruit harvest; 3) balanced, quantifiable crop load management for achieving high fruit quality; 4) simplified strategies for fruitwood development and maintenance to reduce hand-pruning labor; 5) partial mechanization to reduce pruning and harvest labor; 6) utilization of protective orchard covers to mitigate the risk of crop damage from rain, hail, frost, and wind; and 7) better spray coverage for protection from insect pests and diseases. Across several sites in North America, the NC140 regional research project has evaluated the performance of three sweet cherry cultivars on dwarfing (Gi3), semi-dwarfing (Gi5), and semi-vigorous (Gi6) rootstocks trained to “threedimensional” and “two-dimensional” (planar) canopy architectures over nine years to date. The planar Super Slender Axe (SSA) training system had the highest early yields on a per tree and per orchard basis, but the planar Upright Fruiting Offshoots (UFO) training system sustained higher cumulative yields upon reaching maturity. The three-dimensional Tall Spindle Axe (TSA) trees had higher early yields than those trained to the three-dimensional Kym Green Bush (KGB) canopy architecture, but the KGB trees achieved nearly comparable cumulative yields. Fruitwood renewal strategies are critical for maintenance of yields and fruit quality. Profitable yields of high quality fruit are achievable for each of the canopy architectures, but each also has specific advantages and challenges, including suitability for specific rootstocks and cultivars. These are discussed, including comparisons of the two- vs. three-dimensional canopy architectures developed as single leader (SSA vs. TSA) and multiple leader (UFO vs. KGB) training systems. The advantages of utilizing the natural light interception efficiencies and growth habit of sweet cherry in the simplified structure of UFO-style planar canopy architectures is expanding beyond sweet cherries to many other major trees fruits around the world as well.

scholarly journals Long-term Performance of ‘Delicious’ Apple Trees Grafted on Geneva® Rootstocks and Trained to Four High-density Systems under New York State Climatic Conditions

HortScience ◽  
2020 ◽  
Vol 55 (10) ◽  
pp. 1538-1550
Author(s):  
Gemma Reig ◽  
Jaume Lordan ◽  
Stephen Hoying ◽  
Michael Fargione ◽  
Daniel J. Donahue ◽  
...  
Keyword(s):  
Fruit Quality ◽  
New York State ◽  
Climatic Conditions ◽  
Training System ◽  
High Density ◽  
Cumulative Yield ◽  
Apple Trees ◽  
Cross Sectional ◽  
Training Systems ◽  
G 11

We conducted a large (0.8 ha) field experiment of system × rootstock, using Super Chief Delicious apple as cultivar at Yonder farm in Hudson, NY, between 2007 and 2017. In this study, we compared six Geneva® rootstocks (‘G.11’, ‘G.16’, ‘G.210’, ‘G.30’, ‘G.41’, and ‘G.935’) with one Budagovsky (‘B.118’) and three Malling rootstocks (‘M.7EMLA’, ‘M.9T337’ and ‘M.26EMLA’). Trees on each rootstock were trained to four high-density systems: Super Spindle (SS) (5382 apple trees/ha), Tall Spindle (TS) (3262 apple trees/ha), Triple Axis Spindle (TAS) (2243 apple trees/ha), and Vertical Axis (VA) (1656 apple trees/ha). Rootstock and training system interacted to influence growth, production, and fruit quality. When comparing systems, SS trees were the least vigorous but much more productive on a per hectare basis. Among the rootstocks we evaluated, ‘B.118’ had the largest trunk cross-sectional area (TCSA), followed by ‘G.30’ and ‘M.7EMLA’, which were similar in size but they did not differ statistically from ‘G.935’. ‘M.9T337’ was the smallest and was significantly smaller than most of the other rootstocks but it did not differ statistically from ‘G.11’, ‘G.16’, ‘G.210’, ‘G.41’, and ‘M.26EMLA’. Although ‘B.118’ trees were the largest, they had low productivity, whereas the second largest rootstock ‘G.30’ was the most productive on a per hectare basis. ‘M.9’ was the smallest rootstock and failed to adequately fill the space in all systems except the SS, and had low cumulative yield. The highest values for cumulative yield efficiency (CYE) were with ‘G.210’ for all training systems except for VA, where ‘M.9T337’ had the highest value. The lowest values were for all training systems with ‘B.118’ and ‘M.7EMLA’. Regardless of the training system, ‘M.7EMLA’ trees had the highest number of root suckers. Some fruit quality traits were affected by training system, rootstock or system × rootstock combination.

scholarly journals The Orchard Architecture Dedicated for Mechanical Harvesting of Dessert Plums and Prunes

2019 ◽  
Vol 27 (1) ◽  
pp. 1-10
Author(s):  
Augustyn Mika ◽  
Zbigniew Buler ◽  
Jacek Rabcewicz ◽  
Paweł Białkowski ◽  
Dorota Konopacka
Keyword(s):  
Tree Canopy ◽  
Light Distribution ◽  
Standard System ◽  
Training Systems ◽  
Canopy Volume ◽  
Grade Scale ◽  
The Cost

AbstractTwo plum cultivars ‘Record’ and ‘Empress’ and one prune cultivar ‘Common Prune’ were planted in spring 2014, spaced at 4.5 × 1.5 × 2.0 m, to be trained to the “Y”- and “V”-trellising systems for mechanical harvesting of dessert fruits with a canopy-contact harvester. The applied trellising systems were compared with the standard central leader system at the same spacing. Trellised trees showed a tendency to grow less well than leader-trained trees, but during the four years of training, they created a higher canopy volume than the control trees because of their spreading form. Trellised trees were able to give yields comparable to those of standard trees. Light distribution within the tree canopy was acceptable in all the training systems. After 4 years of training, the trees were suitable for mechanical harvesting. The effectiveness of mechanical harvesting varied from 85% to 90%. The quality of the fruits harvested with a canopy-contact harvester was comparable to that of manually picked fruits. The consumption of quality of fruits after mechanical harvesting rated on a 5-grade scale was 0.5 grade lower than that of manually harvested fruits. These fruits were acceptable in the local fruit market. Mechanical harvesting was 10–30 times faster compared to manual picking. The cost of the trellising system calculated per 1 ha was 2.0 times higher than that of the standard system.

Yield Determinants and Prediction for California’s Almond Orchards Based on Machine Learning Analytics

2020 ◽  
Author(s):  
Yufang Jin ◽  
Bin Chen ◽  
Bruce Lampinen ◽  
Patrick Brown
Keyword(s):  
Machine Learning ◽  
Meteorological Data ◽  
Maximum Yield ◽  
Light Interception ◽  
Tree Age ◽  
Yield Potential ◽  
Maximum Temperature ◽  
Potential Yield ◽  
Yield Variation ◽  
Almond Orchards

<p>Agricultural productivity is subject to various stressors, including abiotic and biotic threats, many of which are exacerbated by a changing climate. The productivity of tree crops, such as almond orchards, is particularly complex. Moreover, the State of California has implemented legislatively mandated nitrogen (N) management strategies of all growers statewide to minimize nitrogen losses to the environment, and almond growers must now apply N in accordance with the estimated yield in early spring. To understand and mitigate these threats requires a collection of multi-layer large data sets, and advanced analytics is also critical to integrate these highly heterogeneous datasets to generate insights about the key constraints on the yields at tree and field scales. Here we used machine learning approaches to predict orchard-level yield and examine the determinants of almond yield variation in California’s almond orchards, based on a unique 10-year dataset of field measurements of light interception, remote sensing metrics, and almond yield, along with meteorological data. We found that overall the maximum almond yield was highly dependent on light interception, e.g., with each one percent increase in light interception resulting in an increase of 57.9 lbs/acre in the potential yield. Light interception was highest for mature sites with higher long term mean spring incoming solar radiation, and lowest for younger orchards and when March maximum temperature was lower than 19 <sup>o</sup>C. However, at any given level of light interception, actual yield often falls significantly below full yield potential, driven mostly by tree age, temperature profiles in June and winter, and summer maximum vapor pressure deficit (VPDmax). The full random forest model was found to explain 82% (±1%) of yield variation, with a RMSE of 480±9 lbs/acre. When excluding light interception from the predictors, overall orchard characteristics (such as age, location and tree density) and key meteorological variables could still explain 78% of yield variation. The model analysis also showed that warmer winter conditions often limited mature orchards from reaching maximum yield potential and higher summer VPDmax  significantly limited the yield. Our findings through the machine learning approach improved our understanding of the complex interaction between climate, canopy light interception, and almond nut production. The demonstrated relatively robust predictability of almond yield, driven by “big data”, also provides quantitative information and guidance to make informed orchard nutrient management decisions, allocate resources, determine almond price targets, and improve market planning.</p>

scholarly journals Light Distribution in Three Apple Training Systems as Affected by Cultivar and Rootstock

HortScience ◽  
1998 ◽  
Vol 33 (4) ◽  
pp. 601a-601
Author(s):  
Ray A. Allen ◽  
Curt R. Rom
Keyword(s):  
Apple Tree ◽  
Vertical Axis ◽  
Threshold Value ◽  
Training System ◽  
High Density ◽  
Light Distribution ◽  
Light Penetration ◽  
Full Bloom ◽  
Training Systems ◽  
Slender Spindle

Light distribution in two cultivars on three dwarfing rootstocks in three high-density apple tree training systems was measured in the sixth leaf beginning at full bloom and continuing through the season. Training system had a significant effect on light penetration into the lowest point of the canopy (measured at 0.5 m), with the slender spindle being significantly darker than either the central leader or the vertical axis, although all three systems were below the threshold value of 30% full sun (FS) needed to maintain productivity for most of the season. Cultivar had no significant effect; however, trees of both `Jonagold' and `Empire' fell below 20% FS early in the season and remained there until late in the season. Rootstock had the greatest effect, with trees on M9 and M26 being significantly darker in the lower canopy than trees on Mark. Trees on M26 and M9 fell below 10% FS early in the season and remained there, while trees on Mark never fell below 20% FS.

scholarly journals Quantification of light interception within image-based 3-D reconstruction of sole and intercropped canopies over the entire growth season

2020 ◽  
Vol 126 (4) ◽  
pp. 701-712 ◽  
Author(s):  
Binglin Zhu ◽  
Fusang Liu ◽  
Ziwen Xie ◽  
Yan Guo ◽  
Baoguo Li ◽  
...  
Keyword(s):  
Plant Architecture ◽  
Near East ◽  
Light Interception ◽  
Light Distribution ◽  
Phenotypic Traits ◽  
Canopy Architecture ◽  
Radiation Model ◽  
Significant Difference ◽  
East West ◽  
Canopy Light Interception

Abstract Background and Aims Light interception is closely related to canopy architecture. Few studies based on multi-view photography have been conducted in a field environment, particularly studies that link 3-D plant architecture with a radiation model to quantify the dynamic canopy light interception. In this study, we combined realistic 3-D plant architecture with a radiation model to quantify and evaluate the effect of differences in planting patterns and row orientations on canopy light interception. Methods The 3-D architectures of maize and soybean plants were reconstructed for sole crops and intercrops based on multi-view images obtained at five growth dates in the field. We evaluated the accuracy of the calculated leaf length, maximum leaf width, plant height and leaf area according to the measured data. The light distribution within the 3-D plant canopy was calculated with a 3-D radiation model. Finally, we evaluated canopy light interception in different row orientations. Key Results There was good agreement between the measured and calculated phenotypic traits, with an R2 >0.97. The light distribution was more uniform for intercropped maize and more concentrated for sole maize. At the maize silking stage, 85 % of radiation was intercepted by approx. 55 % of the upper canopy region for maize and by approx. 33 % of the upper canopy region for soybean. There was no significant difference in daily light interception between the different row orientations for the entire intercropping and sole systems. However, for intercropped maize, near east–west orientations showed approx. 19 % higher daily light interception than near south–north orientations. For intercropped soybean, daily light interception showed the opposite trend. It was approx. 49 % higher for near south–north orientations than for near east–west orientations. Conclusions The accurate reconstruction of 3-D plants grown in the field based on multi-view images provides the possibility for high-throughput 3-D phenotyping in the field and allows a better understanding of the relationship between canopy architecture and the light environment.

scholarly journals EFFECT OF DORMANT PRUNING REGIMES ON CANOPY LIGHT DISTRIBUTION, FRUIT AND SPUR QUALITY, AND FRUIT PACKOUT OF `MCINTOSH' APPLES.

HortScience ◽  
1992 ◽  
Vol 27 (6) ◽  
pp. 637c-637
Author(s):  
Jon M. Clements ◽  
Joseph F. Costante
Keyword(s):  
Fruit Quality ◽  
Skin Color ◽  
Dry Weight ◽  
Quality Parameters ◽  
Tree Canopy ◽  
Light Distribution ◽  
Soluble Solids ◽  
Complete Analysis ◽  
Solids Concentration ◽  
Analysis Of Results

A randomized complete block study was initiated in 1991 in a fifteen year old `Rogers Red McIntosh'/9-106 interstem orchard to investigate the effect of three dormant pruning regimes- an unpruned control, selectively thinned, and heavily structured or “tiered”, on tree canopy light distribution and fruit and spur quality. Fruit quality parameters being measured for the 1991 and 1992 harvests include skin color (% red blush), weight (g.), flesh firmness (kg.), soluble solids concentration (% Brix), and packout (% fancy grade). Pruning treatment effect on fruit spur quality, in terms of spur bud diameter (mm.) and spur efficiency (leaf dry weight/spur), is also being evaluated at time of harvest. Light distribution is being measured (% PAR, umol/s/m2.) within the tree canopy from petal fall through harvest. Preliminary findings indicate there is a difference in tree canopy light distribution and some fruit quality measurements, including red skin color, between pruning regimes. Complete analysis of results from 1991 will be presented.

scholarly journals Bases of Yield and Production Efficiency in Apple Orchard Systems

1991 ◽  
Vol 116 (2) ◽  
pp. 188-194 ◽  
Author(s):  
Terence L. Robinson ◽  
Alan N. Lakso
Keyword(s):  
Conversion Efficiency ◽  
Production Efficiency ◽  
Light Interception ◽  
Apple Orchard ◽  
Tree Canopy ◽  
Canopy Architecture ◽  
Cross Sectional ◽  
Canopy Volume ◽  
Total Light ◽  
Slender Spindle

Bases of orchard productivity were evaluated in four 10-year-old apple orchard systems (`Empire' and `Redchief Delicious' Malus domestics Borkh. on slender spindle/M.9, Y-trellis/M.26, central leader/M.9/MM.111, and central leader/M.7a). Trunk cross-sectional areas (TCA), canopy dimension and volume, and light interception were measured. Canopy dimension and canopy volume were found to be relatively poor estimators of orchard light interception or yield, especially for the restricted canopy of the Y-trellis. TCA was correlated to both percentage of photosynthetically active radiation (PAR) intercepted and yields. Total light interception during the 7th to the 10th years showed the best correlation with yields of the different systems and explained most of the yield variations among systems. Average light interception was highest with the Y-trellis/M.26 system of both cultivars and approached 70% of available PAR with `Empire'. The higher light interception of this system was the result of canopy architecture that allowed the tree canopy to grow over the tractor alleys. The central leader/M.7a had the lowest light interception with both cultivars. The efficiency of converting light energy into fruit (conversion efficiency = fruit yield/light intercepted) was significantly higher for the Y-trellis/M.26 system than for the slender spindle/M.9 or central leader/M.9/MM.111 systems. The central leader/M.7a system bad the lowest conversion efficiency. An index of partitioning was calculated as the kilograms of fruit per square centimeter increase in TCA. The slender spindle/M.9 system had significantly higher partitioning index than the Y-trellis/M.26 or central leader/M.9/MM.111. The central leader/M.7a system had the lowest partitioning index. The higher conversion efficiency of the Y/M.26 system was not due to increased partitioning to the fruit; however, the basis for the greater efficiency is unknown. The poor conversion efficiency of the central leader/M.7a was mostly due to low partitioning to the fruit. The Y-trellis/M.26 system was found to be the most efficient in both intercepting PAR and converting that energy into fruit.

scholarly journals Light Relations in a Plum Orchard Trellised Horizontally in Comparison with Standard, Central Leader Training

2016 ◽  
Vol 24 (2) ◽  
pp. 31-36
Author(s):  
Augustyn Mika ◽  
Zbigniew Buler
Keyword(s):  
Light Transmission ◽  
Light Interception ◽  
Light Distribution ◽  
Cumulative Yield ◽  
Training Systems ◽  
Canopy Volume ◽  
Leader Training ◽  
Index Weight ◽  
Fruit Load

Abstract Plum trees of ‘Elena’, designed for mechanical harvesting with a straddle self-propelled harvester, were planted in 2008 in the experimental orchard at Dąbrowice at a distance of 4 × 1.5 and 2.0 m. The trees were trained to a central leader to a height of 2.7 m and 1.5 or 2.0 m spread. Plum trees designed for mechanical harvesting with a small tractor-driven harvester were spaced at 4 × 1.0 or 1.5 m and were trellised horizontally on wires stretched along rows 0.8 m above the ground. Fruits were harvested in 2012–2015. The cumulative yield from the trellised trees was only half of that from the trees trained to a central leader, whereas the fruit load index (weight of fruits per m3 canopy) was the highest at 4 × 1.0 m). To explain this phenomenon, studies were conducted in 2015 on light relations in the two training systems. The studies revealed that light transmission has different patterns in the two training systems, but the level of light interception was nearly similar. Light distribution was more beneficial for photosynthesis in the central leader trees. The trees trained to a horizontal canopy had poor illumination at the canopy base. The main reason of low productivity of the horizontal canopy was low canopy volume.

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