&lt;b&gt;The spatial and temporal independence of Italian Zucchini production

Benz, Vilson; Lúcio, Alessandro Dal’Col; Lopes, Sidinei José

doi:10.4025/actasciagron.v37i2.19398

Cited by 4 publications

(6 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…These results indicate that the average of fresh biomass of beans is distributed randomly within the experimental area grown with snap beans, for any plot size and form of grouping. These results agree with those obtained by Benz, Lúcio and Lopes (2015), who found the random distribution of the zucchini production under different plot sizes and with the grouping of the three first harvests. However, in a greenhouse crop of tomatoes and in crops of melon in two commercial production areas with different soils, hybrid and cultural treatment (Miranda et al, 2005), the variability and spatial dependence seen was from moderate to strong in all the production components and crop systems.…”

Section: Resultssupporting

confidence: 83%

“…For the scenarios of plot sizes, neighboring plants were grouped inside the crop row, which generated greater uniformity in the production values by the combination of plants in a similar region. This methodology has been adopted by several authors (Lúcio et al, 2008;Carpes et al, 2010;Santos et al, 2014;Benz et al, 2015) due to the variability among the crop rows.…”

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Spatial dependence and experimental precision in snap bean ( Phaseolus vulgaris L.) trials related to the number of plants and harvests

et al. 2016

Self Cite

View full text Add to dashboard Cite

Spatial dependence and experimental precision in snap bean (Phaseolus vulgaris L.) trials related to the number of plants and harvestsDependência espacial e precisão experimental em ensaios com feijão- ABSTRACTThe productive variability in horticultural crops affects the planning and quality of the experiments, leading to wrong conclusions. The objectives of this study were to verify the spatial dependence of the fresh biomass of snap beans and to dimension the number of plants and harvests that are necessary to improve experimental accuracy in trials. The data of the fresh biomass of snap beans from uniformity trials carried out in a greenhouse and in the field with semivariograms were created with data transformed into indicators. Thus, they were combined on scenarios of plot size and harvest grouping, and they were adjusted to the spherical, exponential and Gaussian models. A response surface was also applied, with the variation coefficient as a dependent variable and the numbers of plants per plot and harvests as independent variables. The estimates of the semivariogram models parameters indicated a weak spatial dependence. The average of the fresh biomass of snap beans is distributed randomly in the trials, and it is not influenced by the number of plants per plot or by the number of grouped harvests. The best combinations between the number of plants per plot and harvest, for the smaller variation coefficients, are plots of 24 plants for plastic greenhouse and field, and 28 plants for plastic tunnel, in the autumn-winter, combined with the grouping of all harvests. In the spring-summer the number of plants per plot was 30 for plastic tunnel and field, also combined with the grouping of all harvests.Index terms: Geostatistic; spatial variability; multiple regression models; experiment planning; variation coefficient. RESUMOA variabilidade produtiva em cultivos olericolas afeta o planejamento e a qualidade de experimentos, levando a conclusões errôneas. Os objetivos foram verificar a dependência espacial da fitomassa fresca de vagens de feijão-de-vagem e dimensionar os números de plantas e de colheitas para melhor precisão experimental. Com os dados da fitomassa fresca de vagens de ensaios realizados em cultivo protegido e a campo com feijão-de-vagem foram ajustados semivariogramas com os dados transformados em indicadores. Foram combinados diferentes tamanhos de parcela e de agrupamentos de colheitas, sendo ajustados os modelos teóricos esférico, exponencial e gaussiano. Também foi ajustado um modelo de superfície de resposta tendo como variável dependente o coeficiente de variação e, como independentes, os números de plantas por parcela e de colheitas. As estimativas dos parâmetros dos modelos teóricos de semivariograma indicaram fraca dependência espacial. A média de fitomassa fresca de vagens possui distribuição aleatória nos ensaios, não sofrendo influência do número de plantas por parcela ou do número de colheitas agrupadas. As melhores combinações entre os números de plantas por parcela e de colheita...

show abstract

Section: Resultssupporting

confidence: 83%

Section: Resultsmentioning

confidence: 99%

Spatial dependence and experimental precision in snap bean ( Phaseolus vulgaris L.) trials related to the number of plants and harvests

et al. 2016

Self Cite

View full text Add to dashboard Cite

show abstract

“…During each harvest, the number and weight (in grams) of fruits harvested from each BU were observed, except for trials with P. vulgaris, where only 2006Benz et al, 2015), studying data transformations (Couto et al, 2009) and using the Papadakis method to minimize the effects of excess zeros and resultant data overdispersion (Lúcio et al, 2016). Lopes et al (1998), Lorentz et al (2005), Carpes et al (2008) and Lúcio et al (2008), have pointed out significant variability between crop rows and harvests, regardless of the species used, and that such variability significantly alters the estimates of sample sizes, types of sampling, size and form of the parcel, experimental outline, and number of harvests needed to adequately differentiate the study treatments.…”

Section: Methodsmentioning

confidence: 99%

Relations between zero-inflated variables in trials with horticultural crops

Lúcio

Nunes

Rego

et al. 2016

Span. j. agric. res.

View full text Add to dashboard Cite

Certain characteristics of some vegetable crops allow multiple harvests during the production cycle; however, to our knowledge, no study has described the behavior of fruit production with progression of the production cycle in vegetable crops with multiple harvests that present data overdispersion. We aimed to characterize the data overdispersion of zero-inflated variables and identify the behavior of these variables during the production cycle of several vegetable crops with multiple harvests. Data from 11 uniformity trials were used without applying treatments; these comprise the database from the Experimental Plants Group at the Federal University of Santa Maria, Brazil. The trials were conducted using four horticultural species grown during different cultivation seasons, cultivation environments, and experimental structures. Although at each harvest, a larger number of basic units with harvest fruit was observed than units without harvest fruit, the basic unit percentage without fruit was high, generating an overdispersion within each individual harvest. The variability within each harvest was high and increased with the evolution of the production cycle of Capsicum annuum, Solanum lycopersicum var. cerasiforme, Phaseolus vulgaris, and Cucurbita pepo species. However, the correlation coefficient between the mean weight and number of harvest fruits tended to remain constant during the crop production cycle. These behaviors show that harvest management should be done individually, at each harvest, such that data overdispersion is reduced.

show abstract

“…Studies in several vegetables have shown that harvest clustering reduces the variability between plants, decreasing data dispersion, and mitigating the negative effect of excess zeros in the database (Carpes et al, 2008(Carpes et al, , 2010Lúcio et al, 2011Lúcio et al, , 2016Santos et al, 2012Santos et al, a,b, 2014Benz et al, 2015;Lúcio & Benz, 2017). However, even with harvest clustering, variability may go on increasing, as the cumulative value of harvest "n" remains the same as that observed in harvest "n-1", when there are no products to be harvested in a plant, while in another, in which there are harvestable products, the value increases.…”

Section: Reducing the Variability In Vegetable Cropsmentioning

confidence: 99%

“…The most effective and also most used strategies to improve the quality of experiments with vegetables with multiple harvests are, namely, identification of crop-specific plot (Table 1) and sample sizes; determining the variability behavior between rows and between harvests, and; the study of data transformation and the use of Papadakis method to minimize the effects of excess zeros causing overdispersion in the database (Lúcio et al, 2011(Lúcio et al, , 2016Santos et al, 2012Santos et al, a,b, 2014Benz et al, 2015;Lúcio & Benz, 2017).…”

Section: Reducing the Variability In Vegetable Cropsmentioning

confidence: 99%

Planning and implementing experiments and analyzing experimental data in vegetable crops: problems and solutions

Lúcio

Sari

2017

Hortic. Bras.

Self Cite

View full text Add to dashboard Cite

The statistical interpretation of experimental results is inherent to the research process. Therefore, every researcher is expected to have basic understanding on the subject. In vegetable crops, the planning, implementing and data gathering is more complex due to specific aspects related to this group of plants, such as intensive management and high labor requirement to carry out the experiments, uneven fruit maturation and heterogeneity of the experimental area. Since all these factors are sources of variability within the experiment, circumventing them in the experiment planning and implementing phases is fundamental to reduce the experimental error. Furthermore, the knowledge of statistical tests and the assumptions for their use is equally critical to make the research statistically valid. The present work presents the problems of unwanted variability within an experiment with vegetables and the possibilities to reduce and manage it. We discuss alternatives to reduce the variability due to uncontrolled effects within an experiment; the most common experimental designs; recommendation of appropriate statistical tests for each type of treatment; and techniques for the diagnosis of residues. We expect to contribute with researchers dealing with vegetable crops, offering subsidies to aid researchers in the planning and implementation of experiments and in the analysis and interpretation of experimental results.

show abstract

<b>The spatial and temporal independence of Italian Zucchini production

Cited by 4 publications

References 11 publications

Spatial dependence and experimental precision in snap bean ( Phaseolus vulgaris L.) trials related to the number of plants and harvests

Spatial dependence and experimental precision in snap bean ( Phaseolus vulgaris L.) trials related to the number of plants and harvests

Relations between zero-inflated variables in trials with horticultural crops

Planning and implementing experiments and analyzing experimental data in vegetable crops: problems and solutions

Contact Info

Product

Resources

About