scholarly journals Atmospheric CO 2 concentration impacts on the life cycle, yield and fruit quality of early‐maturing edible legumes cultivars

2021 ◽  
Author(s):  
Idoia Garmendia ◽  
Sakineh Rashidi ◽  
Marilyn RA Quezada‐Salirrosas ◽  
Nieves Goicoechea
Keyword(s):  
Life Cycle ◽  
Fruit Quality ◽  
Early Maturing

scholarly journals Effect of Formulated Fertilization on Fruit Quality of Early Ripe Peach

2019 ◽  
Vol 136 ◽  
pp. 07016
Author(s):  
Changbing Pu ◽  
Qiao Xiao ◽  
Jin Wang ◽  
Dong Liang ◽  
Xiulan Lv
Keyword(s):  
Fruit Quality ◽  
Orthogonal Experiment ◽  
Organic Fertilizer ◽  
Chemical Fertilizer ◽  
Test Material ◽  
Peach Fruit ◽  
Early Maturing ◽  
Set Up ◽  
Trace Element Fertilizers

Using the early maturing peach variety 'Japan Matsusen' as the test material, nine groups of formula fertilization schemes were set up by orthogonal experiment to study the effects of different fertilization treatments on the quality of peach fruit, in order to obtain the best fertilization formula to improve fruit quality. The results showed that the quality of peach fruit was significantly improved by adding organic fertilizer to the base fertilizer instead of chemical fertilizer. Therefore, by adding organic fertilizer as the base fertilizer, reducing the application amount of chemical fertilizer, and adding other trace element fertilizers can effectively improve the quality of peach fruit.

YIELD AND FRUIT QUALITY OF TWO EARLY MATURING ORANGE CULTIVARS, 'NAVELINA' AND 'FUKUMOTO', IN ANDALUSIA, SPAIN

2015 ◽  
pp. 255-259
Author(s):  
Carlos Merino ◽  
Aurea Hervalejo ◽  
Arturo Salguero ◽  
David González ◽  
Francisco J. Arenas-Arenas
Keyword(s):  
Fruit Quality ◽  
Early Maturing

Culture and fruit quality of rambutan (Nephelium lappaceumL.) in the Soconusco region, Chiapas, Mexico

Fruits ◽  
2004 ◽  
Vol 59 (5) ◽  
pp. 339-350 ◽  
Author(s):  
Eva Johanna Maria Vanderlinden ◽  
H. Alfred Juergen Pohlan ◽  
Marc J.J. Janssens
Keyword(s):  
Fruit Quality

Construction Control As A Strategy For Improving The Quality Of Buildings And Structures

2020 ◽  
Keyword(s):  
Quality Control ◽  
Life Cycle ◽  
Construction Control ◽  
Construction Sites ◽  
Actual Problem ◽  
Construction Market ◽  
Construction Products ◽  
Underlying Causes ◽  
Required Quality

In construction production, the safety of constructing buildings and structures is achieved by ensuring the required quality as a result of systematic construction control based on the implementation of a complex of technical, economic and organizational measures at all stages of the object's life cycle. The article deals with the actual problem of improving the quality of construction products-buildings and structures in conjunction with the activities of construction control bodies. The article presents the advanced foreign and domestic experience of ensuring the quality control at the construction sites, providing for the prevention of the underlying causes of defects and increasing the interest of the contractors directly. On the basis of the analysis of the current situation with quality control at the construction market, ways to improve its efficiency by developing a unified system of technological implementation of relevant requirements for the quality of construction products, determining the rational number and business load of construction control engineers, as well as the active activities of self-regulatory organizations in this area are offered.

Проблемы оценки качества при проектировании транспортных услуг

2020 ◽  
pp. 30-40
Author(s):  
S.U. Lyapina ◽  
◽  
V.N. Tarasova ◽  
V.B. Ruchkin ◽  
E.O. Koscheeva ◽  
...  
Keyword(s):  
Life Cycle ◽  
Business Processes ◽  
Service Industries ◽  
Service Organizations ◽  
Quality Of Services ◽  
Market Failures ◽  
Expert Opinions ◽  
Service Life Cycle ◽  
Quantitative Indicators

The quality issues of new services directly affect the competitiveness of service organizations. However, the introduction of new services to the market is often limited only to the construction of the logistics of business processes, and the design applies only to technological equipment and infrastructure, the quality of which ultimately does not always ensure the quality of the services provided. At the same time, quality management affects mainly operational aspects, that is, it covers the later stages of the service life cycle. In resource-intensive service industries (for example, transport, communications, etc.), the high cost of equipment and infrastructure reduces the possibility of changes in service delivery technologies to improve their quality, which leads to inefficiency and market failures due to the fact that the new service does not match the real needs of customers. Despite this, forecasting and planning the quality of a service at the stage «making a decision» to launch a new service on the market remains largely without sufficient attention. The authors prove the need to design the quality of services at the stage «making a decision» to bring new services to the market. The purpose of the article is to describe the approach developed by the authors to assessing the quality of projected services at the early stages of their life cycle, which makes it possible to integrate qualitative and quantitative indicators of the future service and take into account the forecast requests of customers. The proposed approach has two features: (1) forecasting customer requirements for the quality of services is based on the results of machine learning based on data on existing and potential customers, as well as on the basis of the accumulated knowledge base of customer experience and expert opinions; (2) multi-criteria optimization is used, while some of the optimized parameters are discrete and high-quality. In conclusion, the authors demonstrated the advantages of the developed model on the examples of transport and logistics business in the field of passenger and freight transportation in Russia.

Computable metrics of personal performance in software development teams

2019 ◽  
Author(s):  
Andriy Lishchytovych ◽  
Volodymyr Pavlenko
Keyword(s):  
Life Cycle ◽  
Software Development ◽  
Product Quality ◽  
Performance Indicators ◽  
Key Performance Indicators ◽  
Project Manager ◽  
Development Life Cycle ◽  
Software Product ◽  
Software Development Life Cycle

The present article describes setup, configuration and usage of the key performance indicators (KPIs) of members of project teams involved into the software development life cycle. Key performance indicators are described for the full software development life cycle and imply the deep integration with both task tracking systems and project code management systems, as well as a software product quality testing system. To illustrate, we used the extremely popular products - Atlassian Jira (tracking development tasks and bugs tracking system) and git (code management system). The calculation of key performance indicators is given for a team of three developers, two testing engineers responsible for product quality, one designer, one system administrator, one product manager (responsible for setting business requirements) and one project manager. For the key members of the team, it is suggested to use one integral key performance indicator per the role / team member, which reflects the quality of the fulfillment of the corresponding role of the tasks. The model of performance indicators is inverse positive - the initial value of each of the indicators is zero and increases in the case of certain deviations from the standard performance of official duties inherent in a particular role. The calculation of the proposed key performance indicators can be fully automated (in particular, using Atlassian Jira and Atlassian Bitbucket (git) or any other systems, like Redmine, GitLab or TestLink), which eliminates the human factor and, after the automation, does not require any additional effort to calculate. Using such a tool as the key performance indicators allows project managers to completely eliminate bias, reduce the emotional component and provide objective data for the project manager. The described key performance indicators can be used to reduce the time required to resolve conflicts in the team, increase productivity and improve the quality of the software product.

Sign in / Sign up

Export Citation Format

Share Document