scholarly journals Spatiotemporal Analyses of Tomato Brown Rugose Fruit Virus in Commercial Tomato Greenhouses

Agronomy ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 1268
Author(s):  
Luis Felipe González-Concha ◽  
Joaquín Guillermo Ramírez-Gil ◽  
Raymundo Saúl García-Estrada ◽  
Ángel Rebollar-Alviter ◽  
Juan Manuel Tovar-Pedraza

Tomato brown rugose fruit virus (ToBRFV) is an emerging pathogen affecting tomato-production systems in several countries, including Mexico. This situation involves challenges due to the negative impact on yield and the lack of disease-management measures. This work analyzes the spatiotemporal distribution of ToBRFV in commercial tomato greenhouses. The presence or absence of diseased plants was evaluated weekly, assigning a location in space (x, y). Temporal analysis consisted of fitting the incidence to the monomolecular, logistic, log-logistic, Gompertz, exponential, Weibull, and Richard models, evaluated using the Akaike information criterion, significance, correlation, coefficient of determination, and root mean square error. Spatial analysis consisted of determining spatial aggregation using the Moran, Fisher, and Lloyd indices. In addition, spatial distribution was assessed by sequence observations, point patterns using the inverse distance index, and analysis by SADIE distance indicators. Results indicated that the logistic models (log-logistic and logistic) best described the temporal progress of ToBRFV. This disease also had slightly aggregated patterns in the initial phase, highly aggregated in the exponential phase, and uniform in the deceleration and stationary phases. This study demonstrates that the spatial and temporal dynamics of ToBRFV have important implications for the monitoring, diagnosis, management, and risk prediction of this disease.

2017 ◽  
Vol 48 (1) ◽  
Author(s):  
Thais Destefani Ribeiro ◽  
Taciana Villela Savian ◽  
Tales Jesus Fernandes ◽  
Joel Augusto Muniz

ABSTRACT: The goal of this study was to elucidate the growth and development of the Asian pear fruit, on the grounds of length, diameter and fresh weight determined over time, using the non-linear Gompertz and Logistic models. The specifications of the models were assessed utilizing the R statistical software, via the least squares method and iterative Gauss-Newton process (DRAPER & SMITH, 2014). The residual standard deviation, adjusted coefficient of determination and the Akaike information criterion were used to compare the models. The residual correlations, observed in the data for length and diameter, were modeled using the second-order regression process to render the residuals independent. The logistic model was highly suitable in demonstrating the data, revealing the Asian pear fruit growth to be sigmoid in shape, showing remarkable development for three variables. It showed an average of up to 125 days for length and diameter and 140 days for fresh fruit weight, with values of 72mm length, 80mm diameter and 224g heavy fat.


2018 ◽  
Vol 39 (3) ◽  
pp. 1327
Author(s):  
Cleber Franklin Santos de Oliveira ◽  
João Marcos Novais Tavares ◽  
Gerusa Da Silva Salles Corrêa ◽  
Bruno Serpa Vieira ◽  
Silvana Alves Pedrozo Vitalino Barbosa ◽  
...  

The aim of this study was to compare mathematical models describing growth curves of white-egg layers at different population densities. To fit the models, 4,000 growing white-egg layers were utilized. The experimental design was completely randomized, with population densities of 71, 68, 65, 62, and 59 birds per cage in the starter phase and 19, 17, 15, 13, and 11 birds per cage in the grower phase, with 10 replicates each. Birds were weighed weekly to determine the average body weight and the weight gain. Gompertz and Logistic models were utilized to estimate their growth. The data analysis was carried out using the PROC NLMIXED procedure of the SAS® statistical computer software to estimate the parameters of the equation because mixed models were employed. The mean squared error, the coefficient of determination, and Akaike’s information criterion were used to evaluate the quality of fit of the models. The studied models converged for the description of the growth of the birds at the different densities studied, showing that they were appropriate for estimating the growth of white-egg layers housed at different population densities. The Gompertz model showed a better fit than the Logistic model.


2017 ◽  
Vol 38 (5) ◽  
pp. 2933
Author(s):  
Cláudia Marques de Bem ◽  
Alberto Cargnelutti Filho ◽  
Giovani Facco ◽  
Denison Esequiel Schabarum ◽  
Daniela Lixinski Silveira ◽  
...  

The objective of the present study was to fit Gompertz and Logistic nonlinear to descriptions of morphological traits of sunn hemp. Two uniformity trials were conducted and the crops received identical treatment in all experimental area. Sunn hemp seeds were sown in rows 0.5 m apart with a plant density of 20 plants per row meter in a usable area of 52 m × 50 m. The following morphological traits were evaluated: plant height (PH), number of leaves (NL), stem diameter (SD), and root length (RL). These traits were assessed daily during two sowing periods—seeds were sown on October 22, 2014 (first period) and December 3, 2014 (second period). Four plants were randomly collected daily, beginning 7 days after first period and 13 days after for second period, totaling 94 and 76 evaluation days, respectively. For Gompertz models the equation was used y=a*e^((?-e?^((b-c*xi))and Logistic models the equation was used yi= a/(1+e^((-b-c*xi)). The inflection points of the Gompertz and Logistic models were calculated and the goodness of fit was quantified using the adjusted coefficient of determination, Akaike information criterion, standard deviation of residuals, mean absolute deviation, mean absolute percentage error, and mean prediction error. Differences were observed between the Gompertz and Logistic models and between the experimental periods in the parameter estimate for all morphological traits measured. Satisfactory growth curve fittings were achieved for plant height, number of leaves, and stem diameter in both models using the evaluation criteria: coefficient of determination (R²), Akaike information criterion (AIC), standard deviation of residuals (SDR), mean absolute deviation (MAD), mean absolute percentage error (MAPE), and mean prediction error (MPE).


2021 ◽  
Vol 43 ◽  
pp. e22
Author(s):  
André Luiz Pinto dos Santos ◽  
Frank Sinatra Gomes da Silva ◽  
Guilherme Rocha Moreira ◽  
Cícero Carlos Ramos de Brito ◽  
Maria Lindomárcia Leonardo da Costa ◽  
...  

The present study aimed to propose new two-compartment models from the combination of the Gompertz, Logistic and Von Bertalanffy models and to identify between Gompertz and Logistic models, in their uni and two-compartiment versions, the one that presents the highest quality of fit to cumulative gas production curves of five cassava genotypes: Brasília, Engana Ladrão, Dourada, Gema de Ovo e Amansa Burro. The gas production readings were 2, 4, 6, 8, 10, 12, 14, 17, 20, 24, 28, 32, 48, 72, and 96 hours after the start of the in vitro fermentation process. The estimation of the parameters for the models was made by the least squares method through the Gauss-Newton iterative process. The selection of the best model to describe the gas accumulation was based on the adjusted coefficient of determination, residual mean squares, mean absolute deviation, Akaike information criterion and Bayesian information criterion. Among the adjusted models, the proposed models were the best to describe the accumulation of gases over time according to the methodology and conditions under which this study was developed.


2018 ◽  
Vol 10 (12) ◽  
pp. 157 ◽  
Author(s):  
Jéssica Andiara Kleinpaul ◽  
Alberto Cargnelutti Filho ◽  
Daniela Lixinski Silveira ◽  
Ismael Mario Marcio Neu ◽  
Cirineu Tolfo Bandeira ◽  
...  

Adjusting nonlinear Gompertz and Logistic models will help in the understanding of the growth pattern of the rye crop and also in the height response of the plant, when planted in different environmental conditions. The the aims of this study were to adjust the nonlinear Gompertz and Logistic models for plant height and indicate the one that best describes growth of two rye cultivars in five sowing times. Ten uniformity trials were conducted with the rye crop in the 2016 harvest. In each trial, ten randomly selected plants were evaluated from the first expanded leaf weekly. In each plant height was measured. The adjustment of the Gompertz and Logistic models as a function of the accumulated thermal sum was performed with the average plant height at each evaluation. The parameters a, b, and c were estimated for each model. The confidence interval for each parameter and the inflection points, maximum acceleration, maximum deceleration and asymptotic deceleration were calculated. The quality of fit of the models was verified by the coefficient of determination, Akaike's information criterion and residual standard deviation. Intrinsic non-linearity and non-linearity of the parameter effect were quantified. Both models describe satisfactorily the plant height. The model that best describes the growth of rye cultivars is Logistic.


Author(s):  
Jéssica A. Kleinpaul ◽  
Alberto Cargnelutti Filho ◽  
Fernanda Carini ◽  
Rafael V. Pezzini ◽  
Gabriela G. Chaves ◽  
...  

ABSTRACT This study aimed to adjust the Gompertz and Logistic nonlinear models for the fresh and dry matter of aerial part and indicate the model that best describes the growth of two rye cultivars in five sowing seasons, as well as to characterize the growth of the cultivars regarding the fresh and dry matter of aerial part. Ten uniformity trials were conducted with the rye crop in 2016. A weekly sampling and evaluation of 10 plants per trial was performed from the time the plants presented one expanded leaf. For each plant, the fresh and dry matter of aerial part were weighed. The Gompertz and Logistic models were adjusted to the accumulated thermal time based on the measures of each trait in each assessment. Also the parameters a, b, and c for each model were estimated and calculated the interval of confidence for each parameter, as well as the inflection points, maximum acceleration, maximum deceleration and asymptotic deceleration. The quality of the model adjustments was verified using the coefficient of determination, Akaike information criterion, and residual standard deviation. The intrinsic nonlinearity and nonlinearity of the parameter effect was quantified. Both models satisfactorily describe the behavior of the fresh and dry matter of aerial part. The Logistic model best describes the growth of rye cultivars. The growth of the cultivars BRS Progresso and Temprano is distinct between sowing seasons. Cultivar BRS Progresso requires a lower thermal time until reaching 50% of its growth when compared to the Temprano cultivar.


Author(s):  
Ekaterina Maksimova ◽  
Ekaterina Maksimova ◽  
Vladimir Zhigulsky ◽  
Vladimir Zhigulsky ◽  
Vladimir Shuisky ◽  
...  

The macrophyte thicket ecosystems of higher aquatic vegetation in the Neva Bay (NB) and Eastern Gulf of Finland (EGoF) perform many important roles, including acting as the habitats, nesting sites and migration sites for aquatic and semi-aquatic birds, creating the specific conditions necessary for the spawning and growth of many species of fish, and taking part in the self-purification of the aquatic ecosystems. Many anthropogenic disturbances, hydraulic works in particular, have a significant negative impact on these macrophyte thicket ecosystems. In recent years, the active growth of a new type of macrophyte thicket has been observed in the NB. This is due to the aftereffects of the construction of the Saint Petersburg Flood Prevention Facility Complex (FPFC). It is quite likely that the total macrophyte thicket area in these waters is currently increasing. In the future, it will be necessary to assess the environmental impacts of the hydraulic works on the macrophyte thicket of the NB and EGoF, taking into account the background processes of the spatiotemporal dynamics of the reed beds in the waters in question. To do this, it will be necessary to carry out a comprehensive study of these ecosystems and identify patterns in their spatial and temporal dynamics. The program of the study has been developed and is currently being implemented by Eco-Express-Service, a St. Petersburg eco-design company.


Forecasting ◽  
2021 ◽  
Vol 3 (1) ◽  
pp. 39-55
Author(s):  
Rodgers Makwinja ◽  
Seyoum Mengistou ◽  
Emmanuel Kaunda ◽  
Tena Alemiew ◽  
Titus Bandulo Phiri ◽  
...  

Forecasting, using time series data, has become the most relevant and effective tool for fisheries stock assessment. Autoregressive integrated moving average (ARIMA) modeling has been commonly used to predict the general trend for fish landings with increased reliability and precision. In this paper, ARIMA models were applied to predict Lake Malombe annual fish landings and catch per unit effort (CPUE). The annual fish landings and CPUE trends were first observed and both were non-stationary. The first-order differencing was applied to transform the non-stationary data into stationary. Autocorrelation functions (AC), partial autocorrelation function (PAC), Akaike information criterion (AIC), Bayesian information criterion (BIC), square root of the mean square error (RMSE), the mean absolute error (MAE), percentage standard error of prediction (SEP), average relative variance (ARV), Gaussian maximum likelihood estimation (GMLE) algorithm, efficiency coefficient (E2), coefficient of determination (R2), and persistent index (PI) were estimated, which led to the identification and construction of ARIMA models, suitable in explaining the time series and forecasting. According to the measures of forecasting accuracy, the best forecasting models for fish landings and CPUE were ARIMA (0,1,1) and ARIMA (0,1,0). These models had the lowest values AIC, BIC, RMSE, MAE, SEP, ARV. The models further displayed the highest values of GMLE, PI, R2, and E2. The “auto. arima ()” command in R version 3.6.3 further displayed ARIMA (0,1,1) and ARIMA (0,1,0) as the best. The selected models satisfactorily forecasted the fish landings of 2725.243 metric tons and CPUE of 0.097 kg/h by 2024.


Agronomy ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 1152
Author(s):  
Rebekah Waller ◽  
Murat Kacira ◽  
Esther Magadley ◽  
Meir Teitel ◽  
Ibrahim Yehia

Recognizing the growing interest in the application of organic photovoltaics (OPVs) with greenhouse crop production systems, in this study we used flexible, roll-to-roll printed, semi-transparent OPV arrays as a roof shade for a greenhouse hydroponic tomato production system during a spring and summer production season in the arid southwestern U.S. The wavelength-selective OPV arrays were installed in a contiguous area on a section of the greenhouse roof, decreasing the transmittance of all solar radiation wavelengths and photosynthetically active radiation (PAR) wavelengths (400–700 nm) to the OPV-shaded area by approximately 40% and 37%, respectively. Microclimate conditions and tomato crop growth and yield parameters were measured in both the OPV-shaded (‘OPV’) and non-OPV-shaded (‘Control’) sections of the greenhouse. The OPV shade stabilized the canopy temperature during midday periods with the highest solar radiation intensities, performing the function of a conventional shading method. Although delayed fruit development and ripening in the OPV section resulted in lower total yields compared to the Control section (24.6 kg m−2 and 27.7 kg m−2, respectively), after the fourth (of 10 total) harvests, the average weekly yield, fruit number, and fruit mass were not significantly different between the treatment (OPV-shaded) and control group. Light use efficiency (LUE), defined as the ratio of total fruit yield to accumulated PAR received by the plant canopy, was nearly twice as high as the Control section, with 21.4 g of fruit per mole of PAR for plants in the OPV-covered section compared to 10.1 g in the Control section. Overall, this study demonstrated that the use of semi-transparent OPVs as a seasonal shade element for greenhouse production in a high-light region is feasible. However, a higher transmission of PAR and greater OPV device efficiency and durability could make OPV shades more economically viable, providing a desirable solution for co-located greenhouse crop production and renewable energy generation in hot and high-light intensity regions.


2006 ◽  
Vol 7 (1) ◽  
pp. 29
Author(s):  
S. N. Rampersad

Tomato production in Trinidad has suffered considerable losses in yield and fruit quality due to infections of hitherto surmised etiology. In order to develop strategies for controlling viral diseases in tomato, the relative distribution and incidence of seven viruses that commonly infect tomato were determined. Of the 362 samples tested, Potato yellow mosaic Trinidad virus (PYMTV) was found in every farm except two and was present at relatively high incidence throughout the country. Tobacco mosaic virus (TMV) and Tobacco etch virus (TEV) were found in fewer farms and at lower incidences while the other viruses were absent. Single infections of either virus were more common than double infections and multiple infections were rare but present. The results indicated that PYMTV is the predominant and most important viral pathogen in tomato production systems in Trinidad; however, begomovirus disease management strategies will also have to accommodate controls Accepted for publication 10 January 2006. Published 9 March 2006.


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