scholarly journals Varying Density with Constant Rectangularity: I. Effects on Apple Tree Growth and Light Interception in Three Training Systems over Ten Years

HortScience ◽  
2004 ◽  
Vol 39 (3) ◽  
pp. 501-506 ◽  
Author(s):  
Cheryl R. Hampson ◽  
Harvey A. Quamme ◽  
Frank Kappel ◽  
Robert T. Brownlee
Keyword(s):  
Leaf Area ◽  
Tree Height ◽  
Light Interception ◽  
Training System ◽  
Influential Factor ◽  
Planting Density ◽  
Area Index ◽  
Training Systems ◽  
Slender Spindle ◽  
Plot Design

The effect of increasing planting density at constant rectangularity on the vegetative growth and light interception of apple [Malus ×sylvestris (L) var. domestica (Borkh.) Mansf.] trees in three training systems (slender spindle, tall spindle, and Geneva Y trellis) was assessed for 10 years. Five tree densities (from 1125 to 3226 trees/ha) and two cultivars (Royal Gala and Summerland McIntosh) were tested in a fully guarded split-split plot design. Planting density was the most influential factor. As tree density increased, tree size decreased, and leaf area index and light interception increased. A planting density between 1800 and 2200 trees/ha (depending on training system) was needed to achieve at least 50% light interception under the conditions of this trial. Training system altered tree height and canopy diameter, but not total scion weight. Training system began to influence light interception in the sixth leaf, when the Y trellis system intercepted more light than either spindle form. Trees trained to the Y trellis tended to have more spurs and a lower proportion of total leaf area in shoot leaves than the other two systems. The slender and tall spindles were similar in most aspects of performance. Tall spindles did not intercept more light than slender spindles. `Royal Gala' and `Summerland McIntosh' trees intercepted about the same amount of light. `Royal Gala' had greater spur leaf area per tree than `Summerland McIntosh', but the cultivars were similar in shoot leaf area per tree and spur density.

scholarly journals Effect of Spatial-Temporal Light Competition on Cotton Yield and Yield Distribution

Agronomy ◽  
2021 ◽  
Vol 11 (11) ◽  
pp. 2346
Author(s):  
Qingru Wang ◽  
Huanxuan Chen ◽  
Yingchun Han ◽  
Fangfang Xing ◽  
Zhanbiao Wang ◽  
...  
Keyword(s):  
Leaf Area ◽  
Plant Height ◽  
Retention Rate ◽  
Block Design ◽  
Light Interception ◽  
Planting Density ◽  
Cotton Yield ◽  
Light Competition ◽  
Area Index ◽  
Yield Distribution

The photosynthetically active radiation (PAR) of crop canopy is highly related to yield formation, but how it relates to yield and yield distribution is not well understood. The focus of this study was to explore the relationship between light competition under different densities and yield distributions of cotton. The experiment was conducted in 2019 and 2020 at the Cotton Research Institute of the Chinese Academy of Agricultural Sciences in Anyang city, Henan Province, China. A randomized block design was employed, with a total of three repeats. Each repeat had six density treatments: D1: 15,000; D2: 33,000; D3: 51,000; D4: 69,000; D5: 87,000; and D6: 105,000 plants·ha−1. As predicted, the results showed that the canopy light interception, leaf area index, plant height, and biomass of high-density cotton were higher than those of low-density cotton. The aboveground biomass produced by D6 was the highest, and was 12.9, 19.5, 25.4, 46.3, and 69.2% higher in 2019 and 14.3, 19.9, 32.5, 53.7, and 109.9% higher in 2020 than D5, D4, D3, D2, and D1, respectively. Leaf area, plant height, biomass, boll number, and boll weight were significantly correlated with the light interception rate. D5 (87,000 plants·ha−1) had a higher light interception rate and the highest yield. The highest lint yields produced by D5 were 1673.5 and 1375.4 kg·ha−1 in two years, and was 3.2, 4.3, 5.6, 9.7, and 24.7% higher in 2019, and 6.8, 10.6, 13.5, 21.5, and 34.4% higher in 2020 than D6, D4, D3, D2, and D1, respectively. The boll retention of the lower fruit branch under D5 reached 0.51 and 0.57 in two years, respectively. The shedding rate of the upper fruit branch decreased with the increase in cotton density in two years. The boll retention rate and shedding rate in the lower part of cotton plants were most closely related to light interception, with R2 values of 0.91 and 0.96, respectively. Our study shows cotton yield could be improved through higher light interception by optimizing planting density and canopy structure.

scholarly journals Climate change and vine training systems: the influence different spatial distribution of shoots may have on sugar accumulation in Sangiovese grapevines.

2019 ◽  
Vol 13 ◽  
pp. 04006 ◽  
Author(s):  
Gabriele Valentini ◽  
Gianluca Allegro ◽  
Chiara Pastore ◽  
Emilia Colucci ◽  
Eugenio Magnanini ◽  
...  
Keyword(s):  
Climate Change ◽  
Leaf Area ◽  
Light Interception ◽  
Training System ◽  
Soluble Solids ◽  
Sugar Accumulation ◽  
Stem Water Potential ◽  
Negative Consequences ◽  
Training Systems ◽  
Open Canopy

The choice of training system may influence vineyard efficiency in terms of light interception and water consumption, particularly in the current context of climate change. On this basis, during the 2017 season, Sangiovese potted vines were grown outdoors using two different training systems: guyot vertical shoot positioned system (C) and V-shaped open canopy (A). From the end of June until September, vine transpiration was continuously monitored by the gravimetric approach and at different times in the season, the leaf area, light interception, photosynthetic activity and stem water potential were measured. Grape yield and fruit composition were recorded at harvest. C plants did not differ from A in terms of leaf area during the entire season. Light interception was higher in C vines during the early hours of the morning and lower in the central part of the day and the transpiration loss was higher, as was the net photosynthesis detected on some days in August. No differences were detected in terms of yield but a significant increase in soluble solids was found in C compared to A. The open canopy compared to a closed one, in a particularly hot year like 2017, resulted in negative consequences on the accumulation of soluble solids, probably as a result of the radiative stress suffered by the A vines in the middle hours of the day.

scholarly journals Optimization of Light Interception, Leaf Area and Yield in “WA38”: Comparisons among Training Systems, Rootstocks and Pruning Techniques

Agronomy ◽  
2020 ◽  
Vol 10 (5) ◽  
pp. 689 ◽  
Author(s):  
Brendon Anthony ◽  
Sara Serra ◽  
Stefano Musacchi
Keyword(s):  
Leaf Area ◽  
Management Strategy ◽  
New Technologies ◽  
Light Interception ◽  
Alternate Bearing ◽  
Area Index ◽  
Training Systems ◽  
Optimal Thresholds ◽  
Proper Training ◽  
Pruning Techniques

As apple orchards have transitioned to high-density plantings, proper training systems are required to manage increased leaf area. Leaf area index (LAI) is defined as the ratio between leaf area to ground area (m2/m2) and can infer orchard health, light relationships and productivity. New technologies enable rapid assessments of LAI and light interception (LI) in the orchard. In this study, LAI, LI, and productivity were assessed across two training systems (Spindle and V), two rootstocks (Geneva 41® (G41) and Malling 9—Nic29 (Nic29)) and two pruning techniques (“click” and bending) in 2016 and 2017. The objective of this study was to determine a management strategy for “WA38” to meet optimal levels for LAI (1.2–2.0) and light interception (65–75%). Higher light interception was measured in V compared to Spindle and in G41 compared to Nic29 in both years. Minimal differences in LAI and light interception were detected across pruning techniques. In “WA38” the “click” technique maintained more consistent yields than bending. In both years, the Spindle-Nic29-“click” combination maintained optimal thresholds for LAI (1.93 and 1.48), light interception (66% and 68%) and consistent yields. This sequence helps mitigate “blind wood” and alternate bearing, while optimizing leaf area and light in “WA38”.

scholarly journals The Relationship Between Leaf Area and Light Interception by Spur and Extension Shoot Leaves and Apple Orchard Productivity

HortScience ◽  
2000 ◽  
Vol 35 (7) ◽  
pp. 1202-1206 ◽  
Author(s):  
Jens N. Wünsche ◽  
Alan N. Lakso
Keyword(s):  
Leaf Area ◽  
Production Systems ◽  
Light Interception ◽  
Apple Orchard ◽  
Fruit Yield ◽  
Area Index ◽  
Canopy Development ◽  
Slender Spindle ◽  
The Relationship ◽  
Canopy Light Interception

The study evaluated the relationship of spur vs. extension shoot leaf area and light interception to apple (Malus {XtimesX}domesticaBorkh.) orchard productivity. Fifteen-year-old `Marshall McIntosh'/M.9 trees had significantly greater leaf area and percentage of light interception at 3-5 and 10-12 weeks after full bloom (AFB) than did 4-year-old `Jonagold'/Mark trees. Despite significant increases in leaf area and light interception with canopy development, linear relationships between total, spur, and extension shoot canopy leaf area index (LAI) and 1) light interception and 2) fruit yield were similar at both times. Mean total and spur canopy LAI and light interception were significantly and positively correlated with fruit yield; however, extension shoot LAI and light interception were poorly correlated with yield. In another study total, spur and extension shoot canopy light interception varied widely in five apple production systems: 15-year-old central leader `Redchief Delicious' MM.111, 15-year-old central leader `Redchief Delicious' MM.111/M.9, 16-year-old slender spindle `Marshall McIntosh' M.9, 14-year-old `Jerseymac' M.9 on 4-wire trellis, and 17-year-old slender spindle `MacSpur' M.9. Yields in these orchards were curvilinearly related to total and extension shoot canopy light interception and decreased when total light interception exceeded 60% and extension shoot interception exceeded 25%. Fruit yields were linearly and highly correlated (r2 = 0.78) with spur light interception. The findings support the hypothesis that fruit yields of healthy apple orchards are better correlated with LAI and light interception by spurs than by extension shoots. The results emphasize the importance of open, well-illuminated, spur-rich tree canopies for high productivity.

Orchard training systems influence early canopy development and light microclimate within apple tree canopies

1993 ◽  
Vol 73 (1) ◽  
pp. 237-248 ◽  
Author(s):  
Frank Kappel ◽  
Harvey A. Quamme
Keyword(s):  
Leaf Area ◽  
Low Light ◽  
Area Index ◽  
Canopy Development ◽  
Training Systems ◽  
Light Levels ◽  
Tree Canopies ◽  
Slender Spindle ◽  
And Training ◽  
Radiation Measurements

Delicious and McIntosh apple trees were trained to five orchard systems: central leader (two spacings), slender spindle, van Roechoudt trellis, and vertical axe. Radiation measurements were taken at the bottom of the canopy throughout the season or at various heights within the canopy after the growth of the canopy was completed. Early in the life of the plantings slender spindle and vertical axe trees of each cultivar had the highest yields expressed on a per hectare basis. By the fifth year of the planting, McIntosh trees trained to the slender spindle and the narrow central leader spacing were producing similar amounts of fruit. Light levels at the bottom of the canopy for some orchard systems were at or below 30% of full sun as early as 25 d after petal fall. Orchard system affected total leaf area and the number of spurs per tree in both 1989 and 1990. The low light levels at the bottom of the canopy reported in this study suggest that attention to pruning and training in the early stages of the orchard development is critical. Key words: Malus domestica, central leader, slender spindle, van Roechoudt trellis, vertical axe, light distribution, leaf area index

scholarly journals Varying Density with Constant Rectangularity: II. Effects on Apple Tree Yield, Fruit Size, and Fruit Color Development in Three Training Systems over Ten Years

HortScience ◽  
2004 ◽  
Vol 39 (3) ◽  
pp. 507-511 ◽  
Author(s):  
Cheryl R. Hampson ◽  
Harvey A. Quamme ◽  
Frank Kappel ◽  
Robert T. Brownlee
Keyword(s):  
Fruit Size ◽  
Fruit Color ◽  
Training System ◽  
Tree Density ◽  
Fruit Yield ◽  
Influential Factor ◽  
Planting Density ◽  
Cumulative Yield ◽  
Yield Efficiency ◽  
Training Systems

The effect of increasing planting density at constant rectangularity on the fruit yield, fruit size, and fruit color of apple [Malus ×sylvestris (L) var. domestica (Borkh.) Mansf.] in three training systems (slender spindle, tall spindle, and Geneva Y trellis) was assessed for 10 years. Five tree densities (from 1125 to 3226 trees/ha) and two cultivars (Royal Gala and Summerland McIntosh) were tested in a fully guarded split-split plot design. Density was the most influential factor. As tree density increased, per-tree yield decreased, but yield per unit area increased. The relation between cumulative yield per ha and tree density was linear at the outset of the trial, but soon became curvilinear, as incremental yield diminished with increasing tree density. The chief advantage of high density planting was a large increase in early fruit yield. In later years, reductions in cumulative yield efficiency, and in fruit color for `Summerland McIntosh', began to appear at the highest density. Training system had no influence on productivity for the first 5 years. During the second half of the trial, fruit yield per tree was greater for the Y trellis than for either spindle form at lower densities but not at higher densities. The slender and tall spindles were similar in nearly all aspects of performance, including yield. `Summerland McIntosh' yielded almost 40% less than `Royal Gala' and seemed more sensitive to the adverse effects of high tree density on fruit color.

scholarly journals Modeling light interception and distribution in mixed canopy of common cocklebur (Xanthium stramarium) in competition with corn

2010 ◽  
Vol 28 (3) ◽  
pp. 455-462 ◽  
Author(s):  
F. Vazin ◽  
M. Hassanzadeh ◽  
A. Madani ◽  
M. Nassiri-Mahallati ◽  
M. Nasri
Keyword(s):  
Leaf Area ◽  
Extinction Coefficient ◽  
Distribution Density ◽  
Yield Loss ◽  
Light Interception ◽  
Area Index ◽  
Corn Seed ◽  
Parabolic Function ◽  
Triangular Function ◽  
Height Model

The aim of this study was to model light interception and distribution in the mixed canopy of Common cocklebur (Xanthium stramarium) with corn. An experiment was conducted in factorial arrangement on the basis of randomized complete blocks design with three replications in Gonabad in 2006-2007 and 2007-2008 seasons. The factors used in this experiment include corn density of 7.5, 8.5 and 9.5 plants per meter of row and density of Common cocklebur of zero, 2, 4, 6 and 8 plants per meter of row. INTERCOM model was used through replacing parabolic function with triangular function of leaf area density. Vertical distribution of the species' leaf area showed that corn has concentrated the most leaf area in layer of 80 to 100 cm while Common cocklebur has concentrated in 35-50 cm of canopy height. Model sensitivity analysis showed that leaf area index, species' height, height where maximum leaf area is seen (hm), and extinction coefficient have influence on light interception rate of any species. In both species, the distribution density of leaf area at the canopy length fit a triangular function, and the height in which maximum leaf area was observed was changed by change in density. There was a correlation between percentage of the radiation absorbed by the weed and percentage of corn seed yield loss (r² = 0.89). Ideal type of corn was determined until the stage of tasseling in competition with weed. This determination indicates that the corn needs more height and leaf area, as well as less extinction coefficient to successfully fight against the weed.

Effects of Planting Density on Leaf Area and Productivity of Two Maize Cultivars in Nigeria

1982 ◽  
Vol 18 (1) ◽  
pp. 93-100 ◽  
Author(s):  
S. U. Remison ◽  
E. O. Lucas
Keyword(s):  
Grain Yield ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Dry Matter ◽  
Plant Population ◽  
Planting Density ◽  
Dry Matter Yield ◽  
Area Index ◽  
Positive Correlation ◽  
Maize Cultivars

SUMMARYTwo maize cvs, FARZ 23 and FARZ 25, were grown at three densities (37,000, 53,000 and 80,000 plants/ha) in 1979 and 1980. Leaf area index (LAI) increased with increase in plant population and was at a maximum at mid-silk. Grain yield was highest at 53,000 plants/ha. There was no relation between LAI and grain yield but there was a positive correlation between LAI and total dry matter yield.

scholarly journals Leaf Removal Affects Maize Morphology and Grain Yield

Agronomy ◽  
2020 ◽  
Vol 10 (2) ◽  
pp. 269 ◽  
Author(s):  
Guangzhou Liu ◽  
Yunshan Yang ◽  
Wanmao Liu ◽  
Xiaoxia Guo ◽  
Jun Xue ◽  
...  
Keyword(s):  
Grain Yield ◽  
Leaf Area ◽  
Field Experiments ◽  
Photosynthetic Capacity ◽  
Maize Yield ◽  
Light Distribution ◽  
Planting Density ◽  
Leaf Removal ◽  
Area Index ◽  
Source Sink

Increasing planting density is an important practice associated with increases in maize yield, but densely planted maize can suffer from poor light conditions. In our two-year field experiments, two morphologically different cultivars, ZD958 (less compact) and DH618 (more compact), were planted at 120,000 plants ha−1 and 135,000 plants ha−1, respectively. We established different leaf area index (LAI) treatments by removing leaves three days after silking: (1) control, no leaves removed (D0); (2) the two uppermost leaves removed (D1); (3) the four uppermost leaves removed (D2); (4) the leaves below the third leaf below the ear removed (D3); (5) the leaves of D1 and D3 removed (D4); (6) the leaves of D2 and D3 removed (D5). Optimal leaf removal improved light distribution, increased photosynthetic capacity and the post-silking source-sink ratio, and thus the grain yield, with an average LAI of 5.9 (5.6 and 6.2 for ZD958 and DH618, respectively) for the highest yields in each year. Therefore, less-compact cultivars should have smaller or fewer topmost leaves or leaves below the ear that quickly senesce post-silking, so as to decrease leaf area and thus improve light distribution and photosynthetic capacity in the canopy under dense planting conditions. However, for more compact cultivars, leaves below the ear should senesce quickly after silking to reduce leaf respiration and improve the photosynthetic capacity of the remaining top residual leaves. In future maize cultivation, compact cultivars with optimal post-silking LAI should be adopted when planting densely.

scholarly journals Estimation of Peanut Leaf Area Index from Unmanned Aerial Vehicle Multispectral Images

Sensors ◽  
2020 ◽  
Vol 20 (23) ◽  
pp. 6732
Author(s):  
Haixia Qi ◽  
Bingyu Zhu ◽  
Zeyu Wu ◽  
Yu Liang ◽  
Jianwen Li ◽  
...  
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Vegetation Index ◽  
Field Experiments ◽  
Predictive Accuracy ◽  
Vegetation Indices ◽  
Planting Density ◽  
Coefficient Of Determination ◽  
Multispectral Images ◽  
Area Index

Leaf area index (LAI) is used to predict crop yield, and unmanned aerial vehicles (UAVs) provide new ways to monitor LAI. In this study, we used a fixed-wing UAV with multispectral cameras for remote sensing monitoring. We conducted field experiments with two peanut varieties at different planting densities to estimate LAI from multispectral images and establish a high-precision LAI prediction model. We used eight vegetation indices (VIs) and developed simple regression and artificial neural network (BPN) models for LAI and spectral VIs. The empirical model was calibrated to estimate peanut LAI, and the best model was selected from the coefficient of determination and root mean square error. The red (660 nm) and near-infrared (790 nm) bands effectively predicted peanut LAI, and LAI increased with planting density. The predictive accuracy of the multiple regression model was higher than that of the single linear regression models, and the correlations between Modified Red-Edge Simple Ratio Index (MSR), Ratio Vegetation Index (RVI), Normalized Difference Vegetation Index (NDVI), and LAI were higher than the other indices. The combined VI BPN model was more accurate than the single VI BPN model, and the BPN model accuracy was higher. Planting density affects peanut LAI, and reflectance-based vegetation indices can help predict LAI.

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