scholarly journals Production of annual ryegrass with different doses of nitrogen fertilization in topdressing

2019 ◽  
Vol 40 (3) ◽  
pp. 1329
Author(s):  
Delvacir Rezende Bolke ◽  
Ione Maria Pereira Haygert-Velho ◽  
Luiz Carlos Timm ◽  
Dileta Regina Moro Alessio ◽  
Andréa Mittelmann ◽  
...  
Keyword(s):  
Growth Model ◽  
Exponential Growth ◽  
Lolium Multiflorum ◽  
Block Design ◽  
Control Treatment ◽  
Time Interval ◽  
Annual Ryegrass ◽  
Nitrogen Application ◽  
Exponential Growth Model ◽  
Different Doses

The objective of this study was to assess the growth of annual ryegrass (Lolium multiflorum) cv. BRS Ponteio with different doses of nitrogen applied in the pasture, thereby adjusting their growth to the exponential growth model. A randomized block design was used with five nitrogen application rates (0, 150, 250, 350, and 450 kg N ha-1) and four replicates, applied in installments. Each plot measured 9 m2. On April 15, 2014, 25 kg ha-1 of viable pure seeds of annual ryegrass were sown at a depth of 0.02 m, in 18 rows spaced at 0.17 m in each plot. Growth in the control treatment (zero nitrogen) pasture lasted 167 days with only three cuts, whereas in pastures treated with 350 and 450 kg N ha-1, growth was extended for an additional 45 days with a 333% increase in the number of cuts. The pastures were used for the same duration (188 days) in the treatments with 150 and 250 kg N ha-1, however, increased nitrogen resulted in two additional cuts and a shorter time interval between cuts. The time interval between each cut and the degree-days interacted dynamically causing distinct growth. Growth of the annual ryegrass BRS Ponteio without nitrogen application is poor and cannot be represented even by a first order linear model. The application of nitrogen topdressing, in the form of urea, decreases the time interval between cuts, increases the dry matter production per hectare, stimulates this production, and follows the exponential growth model.

scholarly journals Ryegrass (Lolium multiflorum) BRS Ponteio and wheat (Triticum aestivum) BRS Tarumã pasture with different doses of ammonium sulfate as topdressing

2019 ◽  
Vol 41 (1) ◽  
pp. 44026
Author(s):  
Luiz Carlos Timm ◽  
Ione Maria Pereira Haygert-Velho ◽  
Delvacir Rezende Bolke ◽  
Gustavo Veiverberg Antunes ◽  
Dileta Regina Moro Alessio ◽  
...  
Keyword(s):  
Triticum Aestivum ◽  
Ammonium Sulfate ◽  
Growth Model ◽  
Exponential Growth ◽  
Dry Matter ◽  
Lolium Multiflorum ◽  
Randomized Design ◽  
Matter Production ◽  
Exponential Growth Model ◽  
Different Doses

This study analyzed the behavior of the annual ryegrass (Lolium multiflorum) BRS Ponteio and dual-purpose wheat (Triticum aestivum) BRS Tarumã with different doses of ammonium sulfate as topdressing and evaluated the exponential growth model to explain the physiological development of both species. For each species, a completely randomized design was used with four replications per treatment with 9m2 area, in which the following treatments were distributed: 0, 150, 250, 350 and 450 kg nitrogen per hectare applied as ammonium sulfate. The cumulative and adjusted productions to the exponential growth model at the end of the cycle were, respectively: BRS Ponteio 150 = 5,620; 250 = 5,920; 350 = 7,585 and 450 = 8,491 and BRS Tarumã 150 = 3,922; 250 = 5,060; 350 = 7,024 and 450 = 7,491 kg dry matter per hectare. The cultivars analyzed without nitrogen application had limited growth and showed no adjustment even to the first order linear model. The application of nitrogen decreased the interval between cuts and increased dry matter production per hectare following the exponential growth model.

scholarly journals Estimating COVID-19 cases infected with the variant alpha (VOC 202012/01): an analysis of screening data in Tokyo, January-March 2021

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Hiroaki Murayama ◽  
Taishi Kayano ◽  
Hiroshi Nishiura
Keyword(s):  
Confidence Interval ◽  
Growth Model ◽  
Exponential Growth ◽  
Reproduction Number ◽  
Hypergeometric Distribution ◽  
Actual Number ◽  
Growth Data ◽  
Exponential Growth Model

Abstract Background In Japan, a part of confirmed patients’ samples have been screened for the variant of concern (VOC), including the variant alpha with N501Y mutation. The present study aimed to estimate the actual number of cases with variant alpha and reconstruct the epidemiological dynamics. Methods The number of cases with variant alpha out of all PCR confirmed cases was estimated, employing a hypergeometric distribution. An exponential growth model was fitted to the growth data of variant alpha cases over fourteen weeks in Tokyo. Results The weekly incidence with variant alpha from 18–24 January 2021 was estimated at 4.2 (95% confidence interval (CI): 0.7, 44.0) cases. The expected incidence in early May ranged from 420–1120 cases per week, and the reproduction number of variant alpha was on the order of 1.5 even under the restriction of contact from January-March, 2021, Tokyo. Conclusions The variant alpha was predicted to swiftly dominate COVID-19 cases in Tokyo, and this has actually occurred by May 2021. Devising the proposed method, any country or location can interpret the virological sampling data.

scholarly journals Estimated Effect of COVID-19 Lockdown on Skin Tumor Size and Survival: An Exponential Growth Model

2020 ◽  
Vol 111 (8) ◽  
pp. 629-638
Author(s):  
A. Tejera-Vaquerizo ◽  
J. Cañueto ◽  
A. Toll ◽  
J. Santos-Juanes ◽  
A. Jaka ◽  
...  
Keyword(s):  
Growth Model ◽  
Exponential Growth ◽  
Tumor Size ◽  
Skin Tumor ◽  
Exponential Growth Model

scholarly journals Models for Predicting Global Plastic Waste

2021 ◽  
Vol 1 (2) ◽  
Author(s):  
Yuexing Hao ◽  
Glenn Shafer
Keyword(s):  
Growth Model ◽  
Real World ◽  
Exponential Growth ◽  
Plastic Waste ◽  
The Self ◽  
Scientific Models ◽  
Adaptive Model ◽  
The Real ◽  
Exponential Growth Model ◽  
Self Adaptive

For more than half a century, plastic prod-ucts have been a part of people’s lives. When plastic waste is thrown into nature, it can cause a sequence of dangerous effects. Previous researchers esti-mated that global plastic waste in 2020 will be more than 400 million tons. To reduce plastic waste, they built scientific models to analyze the sources of plas-tic and provided solutions for regenerating these plastic wastes. However, their models are static and inaccurate, which may cause some false predictions.In this paper, we first observe the distribution of the real-world plastic waste data. Then, we build simple exponential growth model and logistics model to match these data. By testing different models on our plots, we discover that the SELF-ADAPTIVE MODEL is the best to describe and correctly predict our future plastic waste production, as this model combines the benefits of SIMPLE EXPONENTIAL GROWTH MODEL and the LOGISTIC MODEL. The self-Adaptive model has the potential to minimize the error rate and make the predictions more accurate. Based on this model, we can develop more accurate and informative solu-tions for the real-world plastic problems.

scholarly journals Predicting the COVID-19 positive cases in India with concern to Lockdown by using Mathematical and Machine Learning based Models

2020 ◽  
Author(s):  
Ajit Kumar Pasayat ◽  
Satya Narayan Pati ◽  
Aashirbad Maharana
Keyword(s):  
Machine Learning ◽  
Linear Regression ◽  
Regression Model ◽  
Growth Model ◽  
Linear Regression Model ◽  
Exponential Growth ◽  
Time Window ◽  
Epidemic Curve ◽  
First Case ◽  
Exponential Growth Model

In this study, we analyze the number of infected positive cases of COVID-19 outbreak with concern to lockdown in India in the time window of February 11th 2020 to Jun 30th 2020. The first case in India was reported in Kerala on January 30th 2020. To break the chain of spreading, Government announced a nationwide lockdown on March 24th 2020, which is increased two times. The Ongoing lockdown 3.0 is over on May 18th, 2020. We derived how the lockdown relaxation is going to impact on containment of the outbreak. Here the Exponential Growth Model has been used to derive the epidemic curve based on the data collected from February 11th 2020, to May 11th 2020, and the Machine Learning based Linear Regression model that gives the epidemic curve to predict the cases with the continuous flow of the lockdown. We estimate that if the lockdown is continuing with more relaxation, then the estimated infected cases reach up to 1.16 crores by June 30th 2020, and the lockdown would persist with current restriction, then the expected predicted infected cases are 5.69 lacs. The Exponential Growth Model and the Linear Regression Model are advantageous to predict the number of affected cases of COVID-19. These models can be used for forecasting in long term intervals. It shows from our result that lockdown with certain restriction has a vital role in preventing the spreading of this epidemic in this current situation.

scholarly journals Herbage production, botanical and plant-part composition of mixed black oat (Avena strigosa Scherb.) annual ryegrass (Lolium multiflorum Lam.) pastures under different management strategies

2019 ◽  
pp. 1826-1832
Author(s):  
André Brugnara Soares ◽  
André Luis Finkler da Silveira ◽  
Tangriani Simioni Assmann ◽  
Daniel Schmitt
Keyword(s):  
Accumulation Rate ◽  
Lolium Multiflorum ◽  
Block Design ◽  
Management Strategies ◽  
Sampling Technique ◽  
Experimental Period ◽  
Plant Part ◽  
Canopy Height ◽  
Annual Ryegrass ◽  
Forage Production

Mixing annual ryegrass and black oat can improve forage production in subtropical and temperate areas with integrated crop-livestock systems. Thus, we evaluated the forage production dynamics of mixed annual ryegrass-black oat pastures under different management strategies based on canopy height and supplement level. Pastures were continuously stocked with Boer goats at two grazing heights (12 or 21 cm); animals received or did not receive energy supplements (0 and 15 g kg-1 of body weight). These treatments were applied using a factorial scheme (2 × 2) and randomized block design with three replications. We evaluated the herbage accumulation rate (kg of DM h-1 day-1) using the exclusion cage technique, herbage mass (HM, kg of DM ha-1) using the double sampling technique, and botanical and plant-part composition (%) of destructive samplings. Supplementation had no effect on the parameters measured (P ≤ 0.05). Annual ryegrass become the predominant species during the experimental period and mainly at the lowest canopy height. Total herbage production during the 131 days of pasture utilization was 10,280 kg of DM ha-1. The herbage accumulation rate was similar between the two canopy heights; however, it varied throughout experimental period. Leaf lamina mass was lower in treatments 12 cm up to 102 after sowing; after that, they were equivalent. At the end of the study, herbage mass was 2720 kg DM ha-1 with the 21-cm treatment and 2170 kg DM ha-1 with the 12-cm treatment. It is recommended to maintain mixed annual ryegrass-black oat pastures at 12 cm in height. Reasons are discussed throughout the text.

Exponential growth model of Nile tilapia (Oreochromis niloticus) strains considering heteroscedastic variance

Aquaculture ◽  
2008 ◽  
Vol 274 (1) ◽  
pp. 96-100 ◽  
Author(s):  
Vander Bruno dos Santos ◽  
Eidi Yoshihara ◽  
Rilke Tadeu Fonseca de Freitas ◽  
Rafael Vilhena Reis Neto
Keyword(s):  
Growth Model ◽  
Exponential Growth ◽  
Oreochromis Niloticus ◽  
Nile Tilapia ◽  
Nile Tilapia Oreochromis Niloticus ◽  
Exponential Growth Model ◽  
Heteroscedastic Variance

NUMBER OF INSTARS OF THE PITCH PINE TIP MOTH, RHYACIONIA RIGIDANA (LEPIDOPTERA: TORTRICIDAE, OLETHREUTINAE)

1982 ◽  
Vol 114 (6) ◽  
pp. 531-534 ◽  
Author(s):  
Paul M. Gargiullo ◽  
C. W. Berisford
Keyword(s):  
Growth Model ◽  
Exponential Growth ◽  
Head Capsule ◽  
Normal Distributions ◽  
Multimodal Analysis ◽  
Pitch Pine ◽  
Exponential Growth Model

AbstractHead capsule widths were measured on 962 larvae of Rhyacionia rigidana (Fernald). Five instars were detected using multimodal analysis, and normal distributions of head widths for each instar are given. Regression using an exponential growth model was used to generate mean head widths according to Dyar's rule. These widths did not differ significantly from observed widths.

scholarly journals Emergence, growth, and flowering of castor beans as a function of the cationic composition of irrigation water

2016 ◽  
Vol 37 (2) ◽  
pp. 651 ◽  
Author(s):  
Geovani Soares de Lima ◽  
Hans Raj Gheyi ◽  
Reginaldo Gomes Nobre ◽  
Diego Azevedo Xavier ◽  
Lauriane Almeida dos Anjos Soares ◽  
...  
Keyword(s):  
Irrigation Water ◽  
Castor Bean ◽  
Sandy Loam ◽  
Saline Water ◽  
Block Design ◽  
Control Treatment ◽  
Time Interval ◽  
Inflorescence Development ◽  
Cationic Composition ◽  
Bean Cultivar

The use of saline water in agriculture has contributed to the expansion of irrigated areas, especially in arid and semiarid regions, where water deficits occur during various months of the year. In this context, this study aimed to evaluate the emergence, growth, and flowering of the castor bean cultivar “BRS Energia” as a function of the cationic composition of irrigation water, including water containing single and multiple types of cations. The experiment was carried out in a greenhouse in the municipality of Campina Grande-PB, Brazil using drainage lysimeters filled with a sandy loam Ultisol. The experiment was set in a randomized block design, with four replicates each of six water salinity treatments: Control; Na+; Ca2+; Na+ + Ca2+; K+; and Na+ + Ca2+ + Mg2, totaling 24 experimental plots, each consisting of five plants. Plants in the control treatment were subjected to irrigation using water having low electrical conductivity (ECw = 0.6 dS m-1), while the plants receiving other treatments were irrigated using 4.5 dS m-1 water containing different ions. Emergence and growth were more affected by the ECw than by the cationic composition of the irrigation water. The order of the cations in the irrigation water, in terms of negative effects, was Na+ > Na+ + Ca+ > Ca2+ > Na+ + Ca2+ + Mg2+ > K+. The cationic composition of the irrigation water influenced the time interval for inflorescence development and the opening of flower buds of the castor bean cultivar “BRS Energia”, and the most pronounced effects were observed in plants irrigated with calcic water.

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