Influential Components Research Articles

Routine Outcome Monitoring and Clinical Feedback in Psychotherapy: Recent Advances and Future Directions

In the past decade, there has been an increase in research related to the routine collection and active use of standardized patient data in psychotherapy. Research has increasingly focused on personalization of care to patients, clinical skills and interventions that modulate treatment outcomes, and implementation strategies, all of which appear to enhance the beneficial effects of ROM and feedback. In this article, we summarize trends and recent advances in the research on this topic and identify several essential directions for the field in the short to medium term. We anticipate a broadening of research from the focus on average effects to greater specificity around what kinds of feedback, provided at what time, to which individuals, in what settings, are most beneficial. We also propose that the field needs to focus on issues of health equity, ensuring that ROM can be a vehicle for increased wellbeing for those who need it most. The complexity of mental healthcare systems means that there may be multiple viable measurement solutions with varying costs and benefits to diverse stakeholders in different treatment contexts, and research is needed to identify the most influential components in each of these contexts.

Hydrologic connectivity assessment among natural hydrosystem components using emerging entropy and evolutionary computing methods

Abstract Understanding the interactions among the natural components of hydrological systems is essential for managing water resources, addressing environmental concerns, and mitigating the impacts of natural events such as floods and droughts. In this study, long-term (1993–2019) hydrologic connectivity among precipitation, humidity, evaporation, surface runoff, minimum/maximum temperature, and their interactions with groundwater level (GWL) in the southeastern Caspian Sea region was assessed using mutual information theory and the state-of-the-art jittered genetic programming approach. While the former was used to find dominant components, their effective time delay, and the power of potential nonlinear interactions, the latter was utilized to extract an explicit relation between the GWL and the most influential components. The data were gathered from several piezometers, meteorological stations, and a stream gauge available in the study area. The results showed an overall positive trend in the GWL with an increasing rate since 2007 that reflects the influence of artificial recharge infrastructures built in the study area. Statistical connectivity analyses demonstrated that historical precipitation and streamflow series have the least impact on the temporal variation of the average GWL.

Comparisons of rainfall partitioning and canopy interception modelling in pure and mixed forests on the Chinese Loess Plateau

AbstractRainfall partitioning is a key process in forest ecosystems that affects the forest hydrological cycle and ecological services. However, little is known about the rainfall partitioning in Pinus tabuliformis (PT), Robinia pseudoacacia (RP), and Pinus tabuliformis×Robinia pseudoacacia (PT × RP) forests, which are widely distributed on the Chinese Loess Plateau (CLP) for controlling soil and water losses. The objectives of this study were to compare the rainfall partitioning and conduct interception modelling in PT, RP, and PT × RP forests, using data from the Ansai and Changwu sites on the CLP. The sites feature similar weather conductions and both pure and mixed forests of the same age. The tree density of PT × RP was moderate at the Ansai site but higher at the Changwu site compared to PT and RP. We quantitatively measured the throughfall (Tf), stemflow (Sf), and interception loss (Ic) for the forests at the two sites during the growing season (May–October, 2022), and simulated Ic using the Revised Gash Analytical Model (RGAM) and Liu model. The results showed that measured Ic for PT × RP (26.0% of the total gross rainfall, Pg) was larger than for RP (22.0% of Pg) but smaller than for PT (27.8% of Pg) at the Ansai site, and vice versa for the Tf and Sf (RP > PT × RP > PT), while the measured Ic for PT × RP (33.7% of Pg) at the Changwu site was larger than both for PT (31.1% of Pg) and RP (19.5% of Pg). The Tf and Sf for PT × RP was smaller than for PT and RP. Given the similar weather conditions, differences in Ic for the pure and mixed forests at each site were attributed to canopy storage capacity, wet canopy evaporation rate, and tree density. Additionally, the RGAM and the Liu model effectively simulated and captured the differences in Ic for PT, RP, and PT × RP. However, the RGAM performed better with a relative error less than −7.3%, Nash‐Sutcliffe model efficiency ranging from 0.82 to 0.95, and root mean square error less than 0.5 mm. According to the RGAM, evaporation from the wet canopy during rainfall events and after rainfall cessation were the two most influential components. The results of this study suggest that mixed forest can optimize rainfall partitioning compared to pure forests, but a reasonable density should be adopted to increase rainwater replenishment to the forest floor.

Pre-service elementary teachers’ science and engineering teaching self-efficacy and outcome expectancy: exploring the impacts of efficacy source experiences through varying course modalities

BackgroundTeacher efficacy is one of the most influential components for effective instruction, highlighting the importance of providing preservice teachers (PSTs) with opportunities to learn how to teach engineering during their college preparatory coursework. Making space for engineering instruction within science methods coursework could provide opportunities for PSTs to enhance their engineering teaching efficacy but also requires course instructors to give up some time previously devoted to science-focused instruction. The purpose of the current study was to explore how infusing engineering learning opportunities into a science methods course impacts PSTs’ engineering and science teaching efficacy and outcome expectancy.ResultsPre/post-surveys were completed by PSTs enrolled in a Kindergarten-8th grade science methods course offered in four modalities (i.e., face-to-face, hybrid, online, rapid shift online). The course offered multiple engineering-focused learning activities and vicarious experiences. PSTs’ science teaching efficacy beliefs, engineering teaching efficacy beliefs, science teaching outcome expectancy, and engineering teaching outcome expectancy all significantly increased from pre- to post-test. There was no significant difference between efficacy gains based on course modality. The purposeful inclusion of multiple engineering activities and vicarious experiences allows for significant gains in science and engineering teaching efficacy and outcome expectancy regardless of the modality in which the course is taken.ConclusionsThis study shows that having varied efficacy source experiences while learning engineering design can result in increased efficacy, even in the absence of field experience and face-to-face coursework, and that the inclusion of these engineering experiences with science methods coursework does not detract from enhancing science teaching efficacy beliefs and outcome expectancy. Further research is needed to more closely examine individual components of science methods courses and the impacts each component has when implemented using different course modalities.

Unveiling the relationship between social anxiety, loneliness, motivations, and problematic smartphone use: A network approach

BackgroundPrevious studies suggested social anxiety as an essential risk factor for problematic smartphone use, but the complex interactions and the most influential components affecting this relationship remain unclear. This study capitalizes on network analysis to identify the central factors and possible mediating paths among social anxiety, loneliness, five types of motivation, and problematic smartphone use. Material and methodsEmploying 549 emerging adults, we obtained a stable network of the above variables. The central components and the stability of this network were also identified. ResultsWithin this network, the edge linking withdrawal behavior and use of application (APP) exhibits the most robust edge intensity. The central components include social comfort, use of APP, withdrawal behavior, and companionship while the bridge central nodes include social anxiety and escapism motivation. The direct link between social anxiety and PSU revealed only fragile edges with both withdrawal behavior and use of APP. Considering the possible mediating pathways, three pathways were observed in our network. Loneliness and escapism mediated the relationship between social anxiety and social comfort. Moreover, another mediating way was from social anxiety, loneliness, social interaction motivation, and escapism motivation to social comfort. DiscussionBased on the above identification of related components and pathways, future researchers could intervene against problematic smartphone usage in this socially anxious population.

Development of a polarimetric thermal imager calibration method

Measurement of thermal imager characteristics is important for the reliable and efficient operation of the device in various fields, including science, medicine, and industry. Incorrect measurements can lead to errors, which can be critical, especially for military-grade thermal imagers.
 This article is dedicated to developing a method for monitoring the output parameters of polarimetric thermal imagers based on calibration. During calibration, the following operations are proposed: visual inspection, functionality check, measurement of polarimetric thermal imager parameters, and evaluation of measurement uncertainties. In this article, the controlled parameters of the polarimetric thermal imager are the measured for device temperature and NETD, Noise Equivalent Temperature Difference. For these parameters, a measurement model, a measurement function, and an uncertainty budget have been developed. The uncertainty budget includes only the main and most influential uncertainty components. This methodology can only be used for one type of polarimetric thermal imager, where the determination of the radiation polarization state is achieved by rotating a phase plate.

Identification and Ranking of Financial, Non-Financial, and Behavioral Components Influencing Earnings Response Coefficient in the Iranian Capital Market (Data Mining Approach)

Objective: The relationship between accounting profit and investor reactions, as well as stock price changes, is measured using the Earnings Response Coefficient (ERC). Previous research indicates a variation in ERC between companies and over time, which is attributed to specific company factors and characteristics. The aim of this study is to identify and rank the financial, non-financial, and behavioral components affecting companies' ERC. Methodology: Using data from 153 companies listed on the Tehran Stock Exchange over the period 2013 to 2022, and employing data mining techniques and two methods: stepwise forward regression and regression decision tree, the influential components on ERC were identified and ranked. Findings: The results of the stepwise forward regression method indicated that the components of auditor's opinion type, earnings per share (EPS), stock liquidity, growth opportunities, earnings stability, inflation rate, sales growth, operating profit ratio, relative strength index per share, and market index return respectively influence ERC. The regression decision tree method results also showed that the components of earnings stability, stock liquidity, EPS, stock price synchronicity, stock trading imbalance, adjusted trading volume, psychological line index, relative strength index per share, earnings conservatism, and financial statement restatements respectively influence ERC. The Wilcoxon test results also showed that the ranking of components influencing ERC is not the same in the two methods. Additionally, comparing the mean absolute error of the two methods indicated that the regression decision tree method identifies and ranks the influential components on ERC more accurately. Conclusion: The results of both methods confirm the high impact of EPS, stock liquidity, earnings stability, and relative strength index per share on the ERC of companies.

Identification of Effective Factors on Public Oversight of Public Policies with a Crowdsourcing Approach Using Thematic Analysis and DEMATEL Techniques

Objective: The primary goal of this article is to identify the factors influencing public oversight of public policies using a crowdsourcing approach with thematic analysis and DEMATEL techniques. Methodology: The research methodology is mixed (qualitative-quantitative). In addition to documentary studies, thematic analysis technique has been utilized. The statistical population in this study comprised all experts in the field of public policy-making, managers, and public health professionals, with theoretical saturation achieved after 16 interviews. Eventually, basic, organizing, and global themes were extracted, and in the quantitative part, the DEMATEL technique was used to determine the impact and influence of factors on public oversight of public policies with a crowdsourcing approach. Findings: This study identified 15 dimensions (health service capacities, motivational factors, environmental factors, internal policies, domestic infrastructure, executive factors, development and education of public services in health, development of domestic services, globalization of public services, development of knowledge sharing policies and services, structural issues, laws and regulations, cultural factors, financial management) and 32 components and 159 indicators were extracted. Through the DEMATEL method in the quantitative section, 8 influential components and 7 influenced components were identified. Conclusion: The studies indicated that among the identified dimensions, the dimension of health service capacities has the highest importance in terms of impact and requires special attention, while the dimension of cultural factors is the most influenced dimension that is affected by other dimensions.

Explaining the Structural Model of Factors Influencing the Retention and Maintenance of Human Capital Based on Organizational Productivity

Objective: An organization demands its employees to possess the maximum potential benefits and expects them to meet organizational needs. Therefore, in a new perspective, the creation of an appropriate environment for the retention and maintenance of human capital and its connection to increased organizational productivity has been introduced as an important step towards the realization and achievement of objectives, including organizational productivity. The aim of this paper is to explain the structural model of factors effective in retaining and maintaining human capital based on organizational productivity in the National Iranian Oil Company. Methodology: The research method was descriptive-survey, and the statistical population consisted of senior managers and deputies in the human resources domain from the National Iranian Oil Company in headquarters and field staff (582 individuals), of whom 235 were selected as the sample using Cochran's formula. Interviews and questionnaires were used as data collection tools, validated through content and construct validity, and reliability was established using Cronbach's alpha coefficient. For data analysis, statistical methods and tests such as Pearson correlation coefficient, single variable t-test, Kolmogorov-Smirnov test, exploratory and confirmatory factor analysis were used, employing SPSS and LISREL software. Findings: The results indicate that the investigation into creating an appropriate environment for retaining and maintaining human capital and increasing organizational productivity involves individual factors, organizational factors, and group factors, each including components that significantly impact the productivity of the organization at the National Iranian Oil Company. The research also showed that retaining and maintaining human capital is key to improving and increasing organizational productivity, with the most influential components on productivity in the National Iranian Oil Company being organizational factors—performance management (efficiency and effectiveness) with an impact of 0.85, merit selection with an impact of 0.83, intellectual capital smartization with an impact of 0.80, talent management with an impact of 0.80, and individual factors—ability and knowledge with an impact of 0.79. Conclusion: A comprehensive human resource retention program can play a vital role both in attracting and retaining key employees and in financial turnover and other human resource costs. These factors significantly aid organizational productivity and overall business performance. It is far more efficient to retain a competent employee than to hire, train, and guide a replacement with similar capabilities.

Optimizing Bank Profitability Model Considering the Role of Modern Banking Technologies

The aim of this study is to present an optimized model for bank profitability by considering the role of modern banking technologies. This research, being exploratory in nature due to its model development, is also considered applied because its results are utilized by beneficiaries. A quantitative method is used in this study to optimize bank profitability while considering the role of modern banking technologies. In the first step, influential components are identified through library techniques and document review, followed by mathematical programming for modeling. The proposed model is optimized using the epsilon-constraint algorithm in the MAPLE software and further optimized using MATLAB software. The research population, as a case study, includes documents and articles related to the banking industry. Initially, a single-component bank, considered as part of the system, was examined. Assume the bank operates in a seven-hour shift, six days a week. The maintenance activity time and fintech interventions were set to 7 time units, and the service delivery and corrective actions were set to 12 time units. With a 10% and 20% increase in the δ_E and δ_(M/C) data, significant changes in the objective function and decision variables were observed. However, changes in other data did not result in noticeable alterations in the model, indicating the importance of preventing the process from shifting to an out-of-control state and the significance of changes in the mean and standard deviation of the targeted quality characteristic. The proposed model determines the optimal value of each of the four decision variables: sample size (n), sampling interval (h), control limit coefficient (k), and intervals for preventive fintech actions (t_PM), which minimizes the total expected cost from integration per time unit. A numerical example demonstrated the economic impact of cost parameters on the integrated policy of profit control and preventive fintech actions. Additionally, in this study, the integrated model was compared with the independent model through a numerical example, and the significant difference in total cost highlighted the superiority of the integrated model over the independent model.

Screening of Wild and Cultivated Vigna Accessions for Resistance to Bruchid (Callosobruchus maculatus F.)

The bruchid beetles (Callosobruchus maculatus) is one of the primary causes for the loss in pulses due to the seed damages during storage. The wild relatives of crop species are essential sources of new genes for crop improvement. A set of 40 wild Vigna accessions and cultivated Vigna species were screened for C. maculatus resistance. Based on the results, the accessions viz., V. radiata var. sublobata, V. trilobata and V. umbellata were found resistant as it recorded less adult emergence, lesser seed damage, low index of susceptibility and less seed weight loss among bruchid resistance traits. These traits are more influential principal components and have a high correlation. The identified accessions can be involved in the resistance breeding program as a donor to introgress resistance against bruchid beetles towards developing superior cultivars. One of the identified key traits, viz.,seed weight loss or seed damage or index of susceptibility, should be given more importance while framing the breeding program for reliable and stable bruchid resistance among the cultivar.

Both/And: Mixed methods analysis of network composition, communication patterns, and socio-economic support within social networks of transgender women involved in sex work in Lima, Peru

IntroductionSocial networks contribute to normative reinforcement of HIV prevention strategies, knowledge sharing, and social capital, but little research has characterized the social networks of transgender women (TW) in Latin America. We conducted a mixed methods analysis of three network clusters of TW in Lima, Peru, to evaluate network composition, types of support exchanged, and patterns of communication.MethodsWe recruited TW residing in or affiliated with three “casas trans” (houses shared among TW) in Lima between April-May 2018. Eligible participants were 18 or older, self-reported HIV-negative, and reported recent intercourse with a cis-male partner. Participants completed demographic questionnaires, social network interviews, and semi-structured interviews to assess egocentric network structures, support exchanged, and communication patterns. Quantitative and qualitative data were analyzed using Stata v14.1 and Atlas.ti, respectively.ResultsOf 20 TW, median age was 26 years and 100% reported involvement in commercial sex work. Respondents identified 161 individuals they interacted with in the past month (alters), of whom 33% were TW and 52% family members. 70% of respondents reported receiving emotional support from family, while 30% received financial support and instrumental support from family. Of the 13 (65%) respondents who nominated someone as a source of HIV prevention support (HPS), the majority (69%) nominated other TW. In a GEE regression analysis adjusted for respondent education and region of birth, being a family member was associated with lower likelihood of providing financial support (aOR 0.21, CI 0.08–0.54), instrumental support (aOR 0.16, CI 0.06–0.39), and HPS (aOR 0.18, CI 0.05–0.64). In qualitative interviews, most respondents identified a cis-female family member as their most trusted and closest network member, but other TW were more often considered sources of day-to-day support, including HPS.ConclusionTW have diverse social networks where other TW are key sources of knowledge sharing and support, and family members may also represent important and influential components. Within these complex networks, TW may selectively solicit and provide support from different network alters according to specific contexts and needs. HIV prevention messaging could consider incorporating network-based interventions with TW community input and outreach efforts for supportive family members.

Traditional commercial banking and systemic risk: Evidence from Hungary

Systemic risk reduction in banking is a key component in maintaining financial stability. Even after extensive explorations, the role of nontraditional activites in systemic risk still offers several questions to study. The paper aims to contribute to the literature on the topic by empirically examining whether traditional and nontraditional banking activities differ in terms of systemic risk. To answer this question, traditional commercial banking is assumed to be represented by the loan-deposit interest margin income component. Hungarian banking sector data between 2003 and 2020 are analyzed with principal component analysis and multidimensional scaling. The primary measure in systemic risk quantification is the return covariance-based absorption ratio. Empirical findings suggest that, when compared to a more diverse range of banking activities, traditional commercial banking may be characterized by lower systemic risk. Although in these two cases the most influential components of systemic risk may be considered as similar, the other components exhibit significant differences.

Attitudes of Managers towards Ethical Programs in Slovakia

In the modern world, ethical programs have high importance regarding the ethical behavior of companies. Developing and maintaining the corporate ethical culture and reputation is the responsibility of top managers. The current paper aims to reveal the main characteristics of employees influencing their attitude towards selected elements of the ethical program that are considered the most suitable for supporting the ethical behavior of managers, as well as to identify the components of the ethical program with less impact on ethical behavior of managers. The study applied the questionnaire survey method for quantitative data collection in the selected Slovak company. The results show that a code of ethics is an essential part of an ethical program and is crucial for companies. Moreover, although employees’ attitudes towards selected elements regarding ethical behavior are positive, only the attitude to employee care is dependent on the position of respondents in the company. We concluded about employees considering training, employee care, conflict of interest monitoring and transparency in stakeholder relations as the most influential components of the ethical program.

Metabolomics approach to growth-age discrimination in mountain-cultivated ginseng (Panax ginseng C. A. Meyer) using ultra-high-performance liquid chromatography coupled with quadrupole-time-of-flight mass spectrometry.

Mountain-cultivated ginseng is typically harvested after 10 years, while ginseng aged over 15 years is considered wild ginseng. This study aims to differentiate mountain-cultivated ginseng by age, as the fraudulent practice of selling low-aged cultivated ginseng disguised as high-aged one is damaging the market. In this study, LC-MS analyzed 98 ginseng samples, and multivariate statistical analysis identified patterns between samples to select influential components. Machine learning models were developed to identify ginseng samples of different ages. The untargeted metabolomic analysis clearly divided samples aged 4-20 years into three age groups. Twenty-two potential age-dependent biomarkers were discovered to differentiate the three sample groups. Three machine learning models were used to predict new samples, and the optimal model was selected. Some biomarkers could determine age phases according to the differentiation of mountain-cultivated ginseng samples. These biomarkers were thoroughly analyzed for variation trends. The machine learning models established using the screened biomarkers successfully predicted the age group of new samples.

Utilizing the R.E.N.A.L Nephrometry Score to predict the Surgical Technique and Peri-operative Outcomes of Renal Masses

Background: despite the rise in the incidence of renal cell carcinoma attributed to availability of medical imaging, a considerable decline in mortality is an association. Morbidity-wise, the shift from radical nephrectomy to partial nephrectomy is the trend for now. Multiple scoring systems have been introduced over the past decades to help surgeons choose between radical and partial nephrectomy. One commonly used system is the RENAL nephrometry score that was first introduced by Kutikov and Uzzo in 2009. Objective: to evaluate the role of RENAL nephrometry scoring system in predicting the surgical technique to use to resect renal masses and associated perioperative outcomes. Subjects and methods: between December 2018 and December 2020, we prospectively recruited 88 patients with renal masses. Nephrometry scores of all patients were calculated by an experienced radiologist and a decision then was made by blinded treating surgeons to proceed to radical or partial nephrectomy. Patients then sub-grouped into low, moderate, and high nephrometry scores, and into radical and partial nephrectomy. Pre-, intra-, and post-operative data were collected and analyzed. Results: Eighty-three patients completed the study. Thirty-three had undergone radical nephrectomy and 50 had partial nephrectomy. Total nephrometry score differed significantly between the two groups. Mass radius and nearness to the renal hilum were the only influential components. The only complication that differed significantly among the three nephrometry groups was the estimated blood loss, being highest in the low complexity group. No significant difference was found in the total operation time, ischemia time, renal function and hospital stay. Major complications were seen only in the high complexity group. Conclusion: Total nephrometry score, mass radius and nearness to renal hilum can be regarded as good and reproducible predictors of type of surgery required to treat renal masses. They also can predict the perioperative complication to a good extent.

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Purpose: There has been a recent uptick in interest in studying the impact of user ratings and comments posted on social networking sites. The growth of the Internet and e-commerce sites have made it more simpler to locate and assess data, lessened the possibility of identity theft, and increased confidence in the data's accuracy. The study's goal is to determine whether or not customers' exposure to reviews and comments influences their propensity to make a purchase on e-commerce site. Theoretical framework: In contrast to previous research that has examined the impact of user reviews and comments on e-commerce sites, the team behind this investigation looked solely at the impact of such data on media consumers Design/methodology/approach: In a poll, participants were asked about their recent internet shopping experiences and whether or not they were impacted by word-of-mouth advertising. Then, give impartial evaluation data on how views, reactions, and eWOM affected online shopping intent Findings: Based on a structural equation modeling study of 384 observations, we learn that the most influential components in shaping purpose are knowledge, attitude, perceived value, familiarity, and reference group Research, Practical & Social implications: The study help business use social media to sell product or service effectively through understanding consumer behavior in referencing feedback and view on product Originality/value: The value of the study provide researcher theoretical framework in studying consumer behavior through product purchase intention impacted by feedback and view of consumer on social media

Glass flame-work of Firozabad: Unfolding the potential clusters and design intervention

This paper explores the craft of Glass Flame-work and its significance. It narrates the history, location, pattern and structure of the craft, and explains the craft practice in detail. The paper also discusses the methodology for the research, which involves identifying the influential components of the craft. The main part of the paper analyzes the socio-economic data related to the craft. The paper then focuses on the design development process, aiming to create products that can sustain the art in the current market. The paper chooses jewellery as the area of product development and incorporates Glass Flame-work into it. The research was based on primary, secondary and additional data collected from market surveys, closet studies of potential buyers, client studies from various perspectives, and trend research. The data was then filtered and selected according to the research objectives. This paper offers an opportunity for the artisan to meet the aesthetic demands of the market.

How Does the Residential Complex Regulate Residents’ Behaviour? An Empirical Study to Identify Influential Components of Human Territoriality on Social Interaction

Although urbanisation and urban land limitations are prevalent, residential complexes are seldom discussed as a means of compartmentalising social interactions and contributing to residents’ social interactions. Due to the spatial orientation of social interactions, semi-public spaces in these buildings are unable to host residents’ interactions due to a lack of appropriate arrangements/establishment of tangible and visible objects. The influential components, however, have rarely been identified in residential complexes. To fill this gap, using the theory of human territoriality, the current study explores the influential physical components of human territorialities in semi-public spaces in four residential complexes and investigates whether a significant relationship exists between human territorialities’ physical components and social interactions. This study collected data from 264 residents of four residential complexes with different spatial configuration layouts. Pearson correlation and Spearman’s rank correlation are used to evaluate linear and monotonic relationships between study variables. The correlation between spatial configurations of physical components and residents’ interactions confirms that spatial configurations influence residents’ use of semi-public spaces. Social interaction can, therefore, be improved through green space, brightness, accessibility, and furniture in common areas. The findings prove that residential complexes with clustered arrangements have not performed well in creating social interaction due to the lack of defined spaces and territories for people, but multi-core, mixed, and linear complexes that define several open and semi-open spaces have been more successful in the amount of social interaction of residents. This study is one of the first to identify the influential components using the integration of residents’ perceptions and spatial configuration.

65 years of cotton lint yield progress in the USA: Uncovering key influential yield components

Context or problemCotton is an essential cash crop with significant importance in industries related to fiber, feed, and oil. However, achieving further improvements in cotton lint yield requires a more comprehensive understanding of different biomass components and the development of targeted management strategies. Objective or research questionThe objective of this study was to assess the biomass partitioning of 20 cotton cultivars released between 1953 and 2018, determine the rate of gain for lint yield, and identify the contribution of biomass components to yield performance. MethodsA two-year field experiment was conducted to evaluate the biomass partitioning of the 20 cotton cultivars released between 1953 and 2018. Correlation, linear, and path analyses were performed to estimate the effects of various biomass components (such as leaf, stem, bolls, burs, seed, and lint harvest index) on lint yield. ResultsThe study found that lint percentage, lint harvest index, seed biomass, and total aboveground biomass and its components exhibited a linear increase with the year of release. However, improving total aboveground biomass alone without enhancing reproductive partitioning could lead to a decrease in lint yield. Furthermore it was observed that the efficiency of modern cultivars in partitioning aboveground biomass into different plant parts, except for lint, has remained unchanged over the past 65 years of breeding. ConclusionsThe results suggest that future research should prioritize improving the lint harvest index to further enhance the potential lint yield of cotton. Merely increasing total aboveground biomass may not yield the desired improvements in lint yield. Optimizing reproductive partitioning is crucial for achieving enhanced lint yield. Implications or significanceThis study provides valuable insights into the biomass partitioning and yield performance of cotton cultivars spanning several decades. The findings emphasize the importance of focusing on improving the lint harvest index as a key factor in increasing lint yield. The results have implications for the development of targeted management strategies in cotton production and breeding programs, contributing to the overall sustainability and productivity of the cotton industry. Data AvailabilityThe datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.