A regression analysis on factors affecting yield of highbush blueberries

Retamales, Jorge B.; Mena, Carlos; Lobos, Germán; Morales, Yohana

doi:10.1016/j.scienta.2015.02.003

Cited by 18 publications

(6 citation statements)

References 28 publications

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“…Between 1998 and 2011, world production increased from 143,704 tones to 467,048 tones. In South America, an increase of 478% in the area cultivated with blueberries in the period from 2003 to 2008 was observed (RETAMALES et al, 2015). Commercial production of blueberries occurs mainly in North America (United States and Canada), Europe (Poland, Germany) and also in countries of the Southern Hemisphere such as Argentina, Uruguay, Australia and Chile, which have the largest planted area and production in the European and North American off-season, becoming the largest world exporters (RETAMALES et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

Phenology, production and quality of blueberry produced in humid subtropical climate

et al. 2018

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Studies on adaptation to the cultivation site are necessary for the recommendation of new cultivars. The aim of this study was to evaluate the phenological development, productivity and fruit quality of eight blueberry cultivars from the rabbiteye group (Aliceblue, Bluebelle, Bluegem, Briteblue, Climax, Delite, Powderblue and Woodard) and two from the highbush group (Georgiagem and O'Neal) under humid subtropical conditions in the 2012/2013, 2013/2014 and 2014/2015 cycles. Beginning and end of flowering, beginning and end of harvesting, fruit set, production, mass, diameter, pH, content of soluble solids, titratable acidity, ratio and coloring were evaluated. The evaluated cultivars presented flowering in the period from July to September, concentrating harvest in the months of November and December. The highest fruit set was observed in Delite, Climax, Briteblue and Powderblue cultivars. There were differences among cultivars regarding fruit mass, size, pH, content of soluble solids and acidity. The results showed that the cultivars exhibited blue color with few variations over the evaluation years. Cultivars with the best productive performance under humid subtropical climate conditions are Bluegem, Delite, Climax and Powderblue. Index terms: Vaccinium sp., small fruits, fruit set. Fenologia, produção e qualidade de mirtilos produzidos em clima subtropical úmidoResumo -Para a recomendação de novas cultivares, são necessários estudos quanto à adaptação no local de cultivo. Logo, objetivou-se avaliar o desenvolvimento fenológico, a produtividade e a qualidade de frutos de oito cultivares de mirtileiro do grupo rabbiteye (Aliceblue, Bluebelle, Bluegem, Briteblue, Climax, Delite, Powderblue e Woodard) e duas do grupo highbush (Georgiagem e O'Neal) em condições de clima subtropical úmido, nos ciclos de . Foram avaliadas as datas do início e do final de floração, início e final de colheita, frutificação efetiva, produção, massa, diâmetro, pH, teor de sólidos solúveis, acidez titulável, ratio e coloração. As cultivares avaliadas apresentaram floração no período de julho a setembro, concentrando a colheita nos meses de novembro e dezembro. As maiores frutificações efetivas foram observadas nas cultivares Delite, Climax, Briteblue e Powderblue. Houve diferenças entre as cultivares quanto à massa do fruto, tamanho, pH, teor de sólidos solúveis e acidez. Os resultados demonstraram que as cultivares exibiram coloração azul, com poucas variações ao longo dos anos de avaliação. As cultivares com melhor desempenho produtivo, em condições de clima subtropical úmido, são Bluegem, Delite, Climax e Powderblue. Termos para indexação: Vaccinium sp., pequenas frutas, frutificação efetiva. 2 J. G. S. Medeiros et al. Rev. Bras. Frutic., Jaboticabal, 2018, v. 40, n. 3: (e-520)

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Section: Introductionmentioning

confidence: 99%

Phenology, production and quality of blueberry produced in humid subtropical climate

et al. 2018

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“…Juárez-Maldonado et al [23] used multiple regression models to calculate greenhouse tomato daily evapotranspiration and transpiration rates. Retamales et al [29] built a regression model to determine the variables that had the greatest influence on blueberry yield. Ulissi et al [28] compared the spectral reflectance values of leaf and N-NO 3 concentration chemical value by partial least squares chemometric multivariate methods to evaluate the possibility and the accuracy of the estimation of tomato leaf nitrogen concentration performed.…”

Section: Discussionmentioning

confidence: 99%

“…Multivariate regression analysis can provide scientific and quantitative information on the relationships among variable, which is widely used in fields involving agricultural production, such as greenhouse irrigation management [23][24][25] , plant nutrient element detection and analysis [26][27][28] , and crop yield analysis [29] . Similarly, this technique is also the best method for investigating soilless substrates to date, such as analyses of physical and chemical properties and the proportions prediction of different substrates in mixtures.…”

Section: Introduction mentioning

confidence: 99%

Establishment and verification of prediction models for evaluating the physical and chemical properties of soilless substrates

Gong

Wang

Zhang

et al. 2021

International Journal of Agricultural and Biological Engineering

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In soilless culture, a suitable mixed substrate that provides a balanced and stable rhizosphere environment is vital for promoting plant growth. The present study was undertaken to establish seven prediction models of physical and chemical properties, including bulk density (DB), total porosity (TP), water-holding porosity (WHP), air porosity (AP), WHP/AP, electrical conductivity (EC) and cation exchange capacity (CEC) of mixed substrate based on regression equations of measured values from 76 substrate combinations. These seven models were verified using the measured values of 12 mixed substrates, and the average relative prediction errors (REs) were all less than 10%. A comprehensive property prediction model was established by weighted summation of the seven models of physical and chemical properties. According to the set values of DB, TP, WHP, AP, WHP/AP, EC and CEC, the comprehensive property model predicted the six mixture proportions of mixed-substrate, as verified using the measured values. This study is the first to establish prediction models for the physical and chemical properties of mixed substrates. The comprehensive property model could be used to evaluate the physical and chemical properties of commercial mixed substrates, and to provide the optimal mixture substrate formulations according to the setting property value of production requirement.

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“…Horticultural factors such as field age, planting designs that include pollinizers, use of mulch, effective weed management, and conventional field management influence the probability of achieving higher yields (Retamales et al, 2015). Like most crops, soil conditions including plant nutrition and water availability directly affect blueberry productivity and need to be within an optimum range (Cameron et al, 1988;Bryla and Strik, 2015).…”

Section: Horticultural Factorsmentioning

confidence: 99%

Toward evidence-based decision support systems to optimize pollination and yields in highbush blueberry

DeVetter

Chabert

Milbrath

et al. 2022

Front. Sustain. Food Syst.

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Highbush blueberry (Vaccinium spp.) is a globally important fruit crop that depends on insect-mediated pollination to produce quality fruit and commercially viable yields. Pollination success in blueberry is complex and impacted by multiple interacting factors including flower density, bee diversity and abundance, and weather conditions. Other factors, including floral traits, bee traits, and economics also contribute to pollination success at the farm level but are less well understood. As blueberry production continues to expand globally, decision-aid technologies are needed to optimize and enhance the sustainability of pollination strategies. The objective of this review is to highlight our current knowledge about blueberry pollination, where current research efforts are focused, and where future research should be directed to successfully implement a comprehensive blueberry pollination decision-making framework for modern production systems. Important knowledge gaps remain, including how to integrate wild and managed pollinators to optimize pollination, and how to provide predictable and stable crop pollination across variable environmental conditions. In addition, continued advances in pesticide stewardship are required to optimize pollinator health and crop outcomes. Integration of on- and off-farm data, statistical models, and software tools could distill complex scientific information into decision-aid systems that support sustainable, evidence-based pollination decisions at the farm level. Utility of these tools will require multi-disciplinary research and strategic deployment through effective extension and information-sharing networks of growers, beekeepers, and extension/crop advisors.

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A regression analysis on factors affecting yield of highbush blueberries

Cited by 18 publications

References 28 publications

Phenology, production and quality of blueberry produced in humid subtropical climate

Phenology, production and quality of blueberry produced in humid subtropical climate

Establishment and verification of prediction models for evaluating the physical and chemical properties of soilless substrates

Toward evidence-based decision support systems to optimize pollination and yields in highbush blueberry

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