Redirigiendo al acceso original de articulo en 15 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

       
 
Antonios Chrysargyris and Nikolaos Tzortzakis    
Plant residues derived from the agro-industrial sector and their disposal are still unsolved issues despite the various research and applications. The current study assessed the possible peat substitution in growing media with solid residues derived from... 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

 
Antong Xia, Yanyou Wu, Zhanghui Qin, Yunfen Zhu, Lin Li, Juyue Xiao, Mohamed Aboueldahab, Haiying Wan, Jiajia Ming and Jiqian Xiang    
High cadmium (Cd) concentrations associated with geochemical anomalies are prevalent in carbonate-rich karstic areas, posing serious ecological risks, while the karstic soils are rich in bicarbonate (HCO3-). It is known that Selenium (Se) is a mineral el... ver más
Revista: Agronomy

 
Yaxin Wang, Qi Liu, Jie Yang, Guihong Ren, Wenqi Wang, Wuping Zhang and Fuzhong Li    
To address the current problem of the difficulty of extracting the phenotypic parameters of tomato plants in a non-destructive and accurate way, we proposed a method of stem and leaf segmentation and phenotypic extraction of tomato plants based on skelet... 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