Redirigiendo al acceso original de articulo en 24 segundos...
Inicio  /  Agronomy  /  Vol: 9 Núm: 1 Par: January (2019)  /  Artículo
ARTÍCULO
TITULO

The Prognostic Breeding Application JMP Add-In Program

Vasilia A. Fasoula    
Kevin C. Thompson and Andy Mauromoustakos    

Resumen

Prognostic breeding is a crop improvement methodology that utilizes prognostic equations to enable concurrent selection for plant yield potential and stability of performance. There is a necessity for plant breeders to accurately phenotype plants in the field and select effectively for high and stable crop yield in the absence of the confounding effects of competition. Prognostic breeding accomplishes this goal by evaluating plants for (i) plant yield potential and (ii) plant stability, in the same generation. The plant yield index, stability index and the plant prognostic equation are the main criteria used for the selection of the best plants and the best entries grown in honeycomb designs. The construction of honeycomb designs and analysis of experimental data in prognostic breeding necessitate the development of a computer program to ensure accurate measurement of the prognostic equations. The objective of this paper is to introduce the Prognostic Breeding Application JMP Add-In, a program for constructing honeycomb designs and analyzing data for the efficient selection of superior plants and lines. The program displays powerful controls, allowing the user to create maps of any honeycomb design and visualize the selected plants in the field. Multi-year soybean data are used to demonstrate key features and graphic views of the most important steps.

 Artículos similares

       
 
Zuguo Xi, Huiyan Jia, Yifan Li, Jinqing Ma, Mengqian Lu, Zhihui Wang, Dexu Kong and Wei-Wei Deng    
Tea is a healthy beverage made from the leaves of the tea plant [Camellia sinensis (L.) O. Kuntze]. The tea plant is a perennial evergreen plant that is widely distributed in tropical and subtropical regions. PR proteins (pathogenesis-related proteins, P... ver más
Revista: Agronomy

 
Chao Yan, Fuxin Shan, Chang Wang, Xiaochen Lyu, Yuanyi Wu, Shuangshuang Yan and Chunmei Ma    
Increasing planting density is one of the most effective ways to increase soybean yield, but supra-optimum density leads to an increase in the risk of lodged soybean. In this study, two varieties were selected. Heinong84 (lodging-susceptible variety, HN8... ver más
Revista: Agronomy

 
Bin Li, Li Zhang, Lincao Wei, Yujie Yang, Zhexuan Wang, Bo Qiao and Lingjuan Han    
(1) Background: Low-calcium stress can have adverse effects on the rhizosphere environment of cucumber, subsequently impacting cucumber growth. However, plant-growth-promoting rhizobacteria can directly or indirectly enhance plant growth and induce plant... ver más
Revista: Agronomy

 
Shuangshuang Lai, Hailin Ming, Qiuyan Huang, Zhihao Qin, Lian Duan, Fei Cheng and Guangping Han    
The efficient management of commercial orchards strongly requires accurate information on plant growing status for the implementation of necessary farming activities such as irrigation, fertilization, and pest control. Crown planar area and plant number ... ver más
Revista: Agronomy

 
Niharika Sharma, Lakshay Sharma, Dhanyakumar Onkarappa, Kalenahalli Yogendra, Jayakumar Bose and Rita A. Sharma    
Heat stress (HS) is a major threat to crop productivity and is expected to be more frequent and severe due to climate change challenges. The predicted increase in global temperature requires us to understand the dimensions of HS experienced by plants, pa... ver más
Revista: Agronomy