Most popular articles
Everything About Peaches. Clemson University Cooperative Extension Service Everything About Peaches Website: whether you are a professional or backyard peach...
Mission Statement. For the sake of mankind and the world as a whole a further increase of the sustainability...
Newsletter 9: July 2013 - Temperate Fruits in the Tropics and Subtropics. Download your copy of the Working Group Temperate...
USA Walnut varieties. The Walnut Germplasm Collection of the University of California, Davis (USA). A description of the Collection and a History...
China Walnut varieties.

Articles

Precision crop load management tools to ensure consistent cropping of high-density pear and apple orchards

Article number
1401_13
Pages
87 – 96
Language
English
Abstract
The recent trend of establishing apple and pear orchards at increasingly higher tree densities is generally justified by these systems’ inherent potential to produce early yields.
The positive, linear relationship between early orchard productivity and tree density is requisite for rapidly returning high investment costs.
Maximum yield potential of an orchard, on the other hand, requires carefully balanced crop loads.
Central to this precept is the regulation of excess vigor and its subsequent deleterious effect on precocity and early productivity; a task comparatively more difficult to achieve in pear systems than apple in most regions of the world.
The need for dwarfing rootstocks, especially in cold climates, has significantly limited the evolution of pear systems.
The manipulation of plant architecture via rootstocks, training systems, spacing, and pruning (both above and belowground) to develop balanced canopies is required for the application of precision crop load management tools.
Precision management of modern apple systems has expanded considerably due to wide use of dwarfing rootstocks that control vegetative growth and facilitate planting systems comprised of uniform canopies with repeatable fruiting units.
These systems, in turn, are compatible with rapidly emerging technologies.
Several tools are now available to inform and optimize thinning efficacy: These begin with precision dormant pruning to reduce flower load; a pollen tube growth model to facilitate bloom thinning; several new, efficacious post-bloom thinning chemistries; a carbohydrate balance model to inform the application timing, dose and selection of chemical thinners; and, growth rate models that predict abscission rates and aid with reapplication decisions.
The transfer of this knowledge and potential application to pear systems requires a consideration of the pomological (both horticultural and physiological) differences between the two species that ultimately regulates their response to horticultural interventions.
Ongoing development of automation, imaging and geo-referencing technologies to generate variability maps will likely increase the level of precision necessary to consistently manage crop load and improve production consistency, labor-use-efficiency and profitability.

Publication
Authors
T.C. Einhorn
Keywords
crop load management, pruning, prediction models, dwarfing rootstocks, training systems, thinning, fruit set
Full text
Online Articles (40)
Caihong Zhong | Dawei Li | Qiong Zhang | Li Li | Wenjun Huang | Fei Han
Shangyun Li | Rui Gui | Bing Zhao | Jiayu Lu | Haoru Tang | Yong Zhang
C.H. Wu | Q. Wang | M.Y. Lu | Y. Zhao | X.K. Yan | S.Y. Li | M.J. Zhang
Yongjie Qi | Na Ma | LiQing Lu | Fanjun Ke | Liping Kan | Zixian Zha | Yiliu Xu | Zhenghui Gao
H.J. Zhao | W.S. Liu | N. Liu | Y.P. Zhang | Y.J. Zhang | M. Xu | Q.P. Zhang | X.X. Ma | J.C. Liu | B.J. Wang | S. Liu
P. Ollitrault | M. de Saint Roman | E. Bloquel | M. Miranda | N. Athiyannan | P. Mournet | S. Krattinger | B. Bachès | M. Bachès | A. Oihabi | A. Al Hameid | H. Beheiry | L. Julhia | Y. Froelicher
T. Wang | Z.H. Han | T. Wu
R. Li | J.R. Shi | D. Yan | C. Li | Q.Q. Zhao | C.Y. Tan | Y.S. Tao | F.W. Ma | Z.D. Liu | X.L. Ren | C.H. Liu
Y. Gao | Z. Wang | W. Yu | J.B. Ni | S.L. Bai | Y.W. Teng
Chen Pan | Yi Zhou | Yifei Liao | Manman Zhang | Jiahao Wu | Junbei Ni | Songling Bai | Yuanwen Teng
Lu Zhang | Lu Wang | Yuhao Gao | Shulin Yang | Junbei Ni | Yuanwen Teng | Songling Bai
M. Zhang | Y. Liao | S.L. Bai | J.B. Ni | Y.W. Teng
Songling Bai | Qinsong Yang | Yuhao Gao | Yuanwen Teng
Jia Wei | Qinsong Yang | Junbei Ni | Yuhao Gao | Yinxin Tang | Songling Bai | Yuanwen Teng
M. Yang | G.Y. Hou | Y.T. Peng | Y.Y. Jiang | C.X. He | M.S. She | Y. Luo
Xuxu Wang | Peihui Wang | Baojing Shi | Duanni Wang | Junbei Ni | Songling Bai | Yuanwen Teng
X.Y. Ma | J.H. Bao | J.W. Li | X. Cheng | M.M. Tahir | M.Z. Liu | X. Lu | M.R. Wang | Z.B. Hamborg | D. Zhang