The Mixture Chemistry Soil-pasture and Qualitative Brachiariagrasses Priors Results in the Largest Differences Between
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Brazilian Journal of Development 8437
ISSN: 2525-8761
The Mixture Chemistry Soil-pasture and Qualitative
Brachiariagrasses Priors Results in the Largest Differences Between
Systems
Estrutura química em solo e resultados qualitativos para
Brachiariagrass em diferentes sistemas
DOI:10.34117/bjdv7n1-572
Recebimento dos originais: 21/12/2020
Aceitação para publicação: 21/01/2021
Aluisio Fernando Alves Ferreira
Especialista em Zootecnia
Universidade Federal de Goiás - UFG, Departamento Zootecnia, Campus Universitário
Samambaia, Goiânia, Goiás – Brazil – CEP 74690-900 -
ferreira.consult2020@icloud.com
https://orcid.org/0000-0003-0213-438X
Cristian Ephifanio Toledo
Doutor em Engenharia Agricola - Endereço: Universidade Estadual de Goiás, Instituto
Acadêmico de Ciências Agrárias e Sustentabilidade, Campus Oeste - Unidade Palmeiras
de Goiás, Goiás – Brazil – CEP: 76190-000
cristian.toledo@ueg.br
https://orcid.org/0000-0003-3312-6980
João Carlos Mohn Nogueira
Mestre em Produção Vegetal - Endereço: Universidade Estadual de Goiás, Instituto
Acadêmico de Ciências Agrárias e Sustentabilidade, Campus Oeste - Unidade Palmeiras
de Goiás, Goiás – Brazil – CEP: 76190-000
jcmnogueira1@gmail.com
https://orcid.org/0000-0001-5597-7386
Alexandre de Amorim Camargo
Mestre em Engenharia Agricola - Endereço: Universidade Estadual de Goiás, Instituto
Acadêmico de Ciências Agrárias e Sustentabilidade, Campus Oeste - Unidade Palmeiras
de Goiás, Goiás – Brazil – CEP: 76190-000
cmrgo.alexandre@gmail.com
https://orcid.org/0000-0003-3634-3622
Geovana de Freitas Alves
Mestre em Engenharia Agricola - Endereço: Universidade Estadual de Goiás, Instituto
Acadêmico de Ciências Agrárias e Sustentabilidade, Campus Oeste - Unidade Palmeiras
de Goiás, Goiás – Brazil – CEP: 76190-000
geo.freitass12@gmail.com
https://orcid.org/0000-0003-0144-9633
Brazilian Journal of Development, Curitiba, v.7, n.1, p.8437-8450 Jan. 2021Brazilian Journal of Development 8438
ISSN: 2525-8761
Fernando Couto de Araujo
Doutorando em Produção Animal - Endereço: Universidade Estadual de Goiás, Instituto
Acadêmico de Ciências Agrárias e Sustentabilidade, Campus Oeste - Unidade Palmeiras
de Goiás, Goiás – Brazil – CEP: 76190-000
fernandoagrocouto@hotmail.com
https://orcid.org/0000-0002-4455-4596
ABSTRACT
Objectives were the mixtures chemistry soil-pasture and qualitative Brachiariagrasses
priors results in the largest differences between systems. Evaluations compost in systems
are grassland and formed per Europhyla urograndis plants in spaced by 4 (3 x 3 m) + 14
m compost per palisade grass (Urochloa brizantha cv. Marandu). We was of crude protein
estimate over-dominance total nitrogen, available method-analyses kjeldahl, calculated
further factor [N*6.25 = -1 < P > 1:. -0.7= SD±1.14 g.kg], when extending the analysis
[N.E: P2O5 > N, recycle efficiency of conversion per linear correlation of process of
formation tale > leaf – metrical plants] it pays to make the redefined the equations for
mutations micro-biologic-crops are exactly mutate bite biologic the states of each off-
steps with probability 3/4 times we immediately the effects of truncation > forage-mass
[RCBD] x chemistry [split-plot - RCBD] were analyzed using a distribution evolution
from total efficiency of the nitrogen x gravimeter x macroporosity crops, favorable from
formation initial and final in herbage fits. Finally, quantitative forage for animal
production, was relate integral work, observation fits response potential in qualitative in
arrangement by models, what are the optimal parameters settings.
Keywords: Behavior; Composition; Designs; Selection; Variables
RESUMO
Os objetivos foram disponibilizar a dinâmica e os atributos químicos da braquiária em
diferentes sistemas de pastejo. Avaliações de composto em sistemas são pastagens e
formadas por plantas Europhyla urograndis em espaçamento de 4 (3 x 3 m) + 14 m em
(Urochloa brizantha cv. Marandu). A estimativa de proteína bruta sobredominância ao
nitrogênio total, pelo método de kjeldahl e correlacionando correlacionado linearmente
[N * 6,25 = -1 1 :. -0,7 = SD ± 1,14 g.kg], ao estender as análises [NE: P2O5 > N,
por eficiência de utilização e conversão nos processos de formação das plantas em
sistema em ILPF] que foi definido variações químicas no valor nutritivo pelos efeitos de
truncamento> massa da forragem [RCBD] x química [split-plot – RCBD], entre as
relativas de distribuição e evolução a partir da eficiência total o nitrogênio total x umidade
gravimétrica x macroporosidade, favorável para a conformação inicial e final em ajuste
para a formação da forragem. A massa de forragem e densidade animal por hectare é um
potencial em resposta qualitativa nos arranjos destes modelos.
Palavra-chaves: Comportamento; Composição; Design; Seleção; Variáveis
1 INTRODUCTION
Effects environmental can make provide options by accord how a utilization in
scale form quantitative and qualitative mass in systems. At illustrates linear regression
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ISSN: 2525-8761
problems over-accumulation from management, conducing in qualitative of forage mass
at techniques utilities thought truncate and selection gives forages are elevates per a
systems appliances in growth + utilization + conversion + total efficiency of production.
The effects and parameters similarities are relatives among the values residuals of forage
mass and qualitative mass. Are insufficient the results and availability quantitative and
quantitative mass among-st the stocking densities, associates the agricultural and
livestock cattle. At selects gives grasses with higher densities from leaves and lower
proportions stems increases the potential from quality and quantity formation for
accumulation from one complex truncates, under points simulations among-st animals
and residues forages observations on relation to process gives cultivates.
Variables of forage mass brachiariagrasses, are specifics from forage mass in
insensitive densities over structure of analyzes among leaf:colm, observed the using of
nitrogenous total in systems integral, this is insufficient to explain the qualitative
agreement with simulations [growing and conversion, efficiencies: SD=±0.025>160%,
alteration nutrition values] we show the how the agreement did be improving by using
more parameters to describe the associate and by introduction finite efficiencies
corrections [utilizing, efficiencies SD=±0.012>70%] (Silva et al., 2020).
To obtain a deeper understanding of how dynamics work we must only model the
algorithm the mixture chemistry soil-pasture and qualitative mass Brachiariagrasses
priors results in the largest differences between systems (Allen et al., 2011; Andreolla et
al., 2014; Araujo et al., 2013; Detmann, 2012; Brusewitz et al., 1993; D’Andrea et al.,
2002; Bransby and McClaurin, 2000).
We simulation dates from the linear regression model, considerate a simulation
conditional, are equalizes to the considerations at condition of over-quality and quantity
fitness in larges effects of corrections, including investigation among normal distribution
and variables.
The hypothesis and annalist structural mixture chemistry soil-pasture and
qualitative mass Brachiariagrasses priors results in the largest differences between
systems in relation at constants impacts stocking rate over-quality and quantity fitness.
The objectives indicates that when the shrinkage parameters is fixes, only the local
regularizes priors allow for shrinkage of small effects while estimating though mixtures
chemistry soil-pasture and qualitative mass Brachiariagrasses priors in results largest in
differences among-st systems over at relation constants the of impacts stocking rates.
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1.1 MATERIAL AND METHODS
The studied was conduced in Farm Savanna, in municipality Waterfall Golden, in
south of state from Goias [altitud 459 m, longitudinal 49°28'30"W and latitudinal
18°29'30"S] from accorded with an classification Köppen and Geiger [Aw]. The average
annual from precipitation was 1.200 at 1.500 mm -1. Evaluations compost in systems are
grassland and formed per Europhyla urograndis plants in spaced by 4 [3 x 3 m] + 14 m
compost per palisade grass [Urochloa brizantha cv. Marandu]. An evaluated for palisade
grass [wood + forage] were captured: light interception 69%, medium temperature 36ºC,
humidity medium 25% and conventional pasture the light interception 90%, medium
temperature 37°C, medium humidity 24% period registered at 11:00 a.m. and 12:05 p.m.
Randomized statistical, were two appliances of fertilizers, divided in two times
66% and 34%, distribution to cased, a 35 days. The nitrogen was applied on end of each
grazed; 2 kg per paddock or equivalent 100 kg of N ha-1 year-1 Silva et al. (2015) and
subjected at adaptation of each grazed. Moreover, drought periods. We had employed
irrigation cures one or twice hours per weeded [i.e., equivalent to 75 mm monthly].
1.2 CHEMISTRY SOILS
At characteristics chemistry are of medium texture, collected in depth 0.0-0.2 m:
pHH2O = 4.8; P = 4.1 mg/kg; Ca+Mg = 1.6 cmolc/dm-3; K = 0.18 cmolc/dm-3; Al = 0.1
cmolc/dm-3; H+Al = 3.1 cmolc/dm-3 and total carbon = 13.8 g/kg-1 (Embrapa, 1997).
1.3 STOCKING DENSITY
Soil samples collected twelve points an every 28 days, utilized one are squad 1m2
with cut in biased forage. Forage and soil samples collected twelve points an every 28
days. The vigor give planted evaluated through stock rate in produced give dry matter to
21 days hereafter cuties and a revelation of day what initial an entire of first cut, available
a quantity mass: forage mass [kg/ha-1] and residues [kg/ha-1]. The treatments were
Brachiaria brizantha cv. Marandu grass with natural only completely randomized design
with twelve replicates.
Reasonable predictions usually, were dependency upon the numbered of testers to
be assigned to each based-forage and the productively of the based-forage. Accurately
numbered steers experiment permitted at higher mean between lower squad mean error.
Stocked rates grazed management and five based-forage per treatment, analyst quality
and quantity. Numbered testers, put and taken pasture per treatments necessary for hider
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an eighteen intercepted changed for detected at differences between the systems,
calculated 38.46 per cycle pastures in five hectares.
Growled x weights - [i.e., feed and water withheld for 16h] were obtained before
to start and at the end of each grazing cycle [28 days], and then the weight gain [kg animal
-1] per grazing cycle, calculated thorough difference between final and initial weights.
Daily weight gain [kg animal-1 day -1] was accounted from the weight gain per cycle
divided by twenty-eight days. The supplement intake was obtained subtracting the
number of supplements offered during the grazing cycle and collected “orts”. Bull were
randomized in paddock, the fed were 0630, 1400, and 1930 h day, with access - “water”;
divided in two groups of eight animals, represented [Animal unit: 4.29 ha -1]. The
2
experimental area consisted of 28 paddocks of 400m [total: 1.2 ha] of Brachiaria
brizantha cv. Marandu grass supplement with “space box” of 45 cm animal -1. Type of
measurement and number - stocked densities, quality [A.D.G, ha] and quantity [TDN per
ha], for four bulls per pastures were evaluated quantification: forage accumulated [kg/ha
-1], paddock [ha] and [TDN, ha]: C = error of a stocked densities mean for averaged
daily produced per steers expressed at coefficient of variation; C’ = error of a stocked
densities mean for yield of TDN per hectare; expressed as coefficient of variation; t =
length of grazed period in days; a = numbered of differentiated steers grazed the stocked
densities dried the trials; d = numbered of steers days the stocked densities was grazed
and s = pasture size in hectare.
1.4 ANALYSIS LABORATORY
The grass biomass were determined per paddock. The analyzes were carried out
to determine the dry matter. Mixed samples of grass from each grazing cycle were
collected to determine levels were analyzed for dry matter [105°C for 5 h], crude
protein [method 988.05; AOAC, 1990], crude ash [method 942.05; AOAC, 1990], acid
and neutral detergent fibers [method 973.18; AOAC, 1990]. Acid and neutral detergent
fibers were analyzed addition sodium sulfate and amylase, described per Van Soest et al.
(1991).
1.5 STATISTICAL
The effects of truncation: chemical soil [split-plot arrangement in a randomized
complete block designs] x stocking density [randomized complete block designs] x
analyses laboratories [split-plot arrangement in a randomized complete block designs],
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were analyzed using the MIXED procedure in SPSS software version 2012 (SPSS
Institute Inc., Cary, NC), with linear correlation type AR (1) for repeated measures
analysis. Alternative designs with repeated measures were used for the analysis,
treatment, interaction of treatment x wk and block as the main effects and qualifies and
quantifies within the random effects. The linear effect of treatment on the variables were
evaluated with orthogonal polynomials accounted for unequal spacing of nitrogenous
levels. The results “j” were listed as least squares means and were separated “i” using
curtness the option when the fixed effects considered at tendencies signification, of
accorded with the author (Ferreira, 2018).
2 RESULTS
We have also considered two additional conditions in which “p > n” and the
predictors are highly dimensional [fibers (neutral detergent fibers) principal
determinant from ingested of the aliments; and digestible protein g/kg of matter dry per
hectare yearly]. Unfortunately, most shrinkage priors resulted in too much convergence
[forage mass, kg/ha-1 x protein mass, g/kg-1 x stocked densities, body weight / kg-1 >
conversion + utilized efficiencies] to trust the results (Table 1). A description of these
additional conditions and the available results for the priors that can obtained enough
convergence is available at attained at quantity necessary for aliment stocked densities,
identifiable indicators ideal-types gametic duties the stages from developed gives plants.
We illustrate the shrinkage priors [resilience 2.8 MPa with the used phosphorus
therm reactive + nitrogenous in Biomass of Cerrado in data set contained 10.7%
variable of coefficients were high-dimensional residents in differences between
resilience 2.4 MPa with the used nitrogenous mineral in Biomass of Cerrado in data
set contained 14.2%; the predictor variables included 0; 100 and 150 kg N ha-1 and the
values comparable with characteristics occupied thought gravimeter humid and
organic matter residuals] – two nominal predictors in the data set, resulted on a total of
[n = 144] predictors. The number of observations is earlier removing all cases with the
values in split-plots standards were approximately equal training [n = 288] predictors and
test [n = 576] sets. All predictors were normalized to have zero “mean :. normal
statistical” and units variances and the outcome variable was transformed in values
proximate to values calculates.
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Table 1. Fertilizers, N and P uptake (2012 at 2017), overview of the included to predictors
Fertilizer N rate df Forage mass Df Composition nutrient - (CP) df Resilience
Kg ha-1 Kg ha-1 g M.P.a
0 * ** ***
bA
100 41.7 9.7 2.4
150 63.5 15.0‡ 2.4
P.A.D rate (N + P) 20.2 10.5Ab 2.8
ANOVA
Source of variation
N rate (N) *** 1 ** 2 *
P.A.D rate (N + P) NS 1 NS 1 NS
Resilience (MPa) NS 1 NS 1 NS
Plot (M) NS 4 NS‡ 4 NS
N x M.P.a NS 3 NS 6 NS
P.A.D x M.P.a NS 3 NS 6 NS
VC, % 14.2ba 10.7a
*Mean and squad error mean significantly at the 0.05 < p > 0.10 levels (2-tailed);
‡NS, non-significant.
The normal mixture prior is a discrete mixture of a peaked prior around zero [the
stocking density] and at values properly prior to substantially different from the priors
considered an continuous mixtures of fertilizers: [nitrogenous + humid gravimeter;
P.A.D + total porosity + humid gravimeter + organic matter + total carbon +
phosphorus + nitrogenous] of normal densities. Based on the data, regression
coefficients close to “zero or one – in scale of stocking density” will be assigned to the
variances in results in shrinkage were high-dimensional in qualitative mass and few-
dimensional in quantitative mass in coefficients to what were a derivative substantial of
the results presentation.
Additionally, we would like to refer process in accumulation where at more sparse
forage mass + animal unit, ha-1 modified version of condition is considered contrary to
few-dimensional effects environmental at results [forage mass + qualitative mass =
stocked densities] from temperature decrease of the 30ºC and high-dimensional effects
environmental at results [forage mass + quantitative mass = stocked densities] from
temperature increase of the 30ºC and the cross-dates considered are refers at two
dimensional light incidence for temperature and humidity, of accorded with period
collected at 11:00 p.m. and 12:05 a.m.
We have also considered the scaled criteria correlation positively perfect between
soil-plant, and a fixed “cut-off values” from forage mass to select the predictors -
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attained favorably stocking density, quantitative and qualitative mass and nutrition
values.
The scaled from increment in systems, excludes 18% predictors if the posterior
probability contained in Brachiariagrasses 82% exceeds a certainty in relation positively
perfects from function qualitative mass and wood, this criterion generally performed of
developed to the present treatments than the credibility interval criterion. For the fixed
“brachiariagrasses: cuts-residual” value we excluded predictors when the posterior
estimate p < 0.5 based in favorable positively perfect for conditions in function of levels
results in nitrogenous total in conditions environmental.
The choice of this quantitative mass is rather arbitrary and resulted in very high-
dimensional in adjusted of management including at phenology stocking rates. For the
qualitative mass in difference significance prior, all replications resulted in one or more
divergent [systems] transitions, despite repartmentalization of the models. The
regularized at availability initials also resulted in divergent transitions [quantitative and
qualitative mass] – most replications, thought the percentage of divergent transitions
were in average much high for the regularized intensity pastures compared to the stress
“environmental”.
The percentage divergent transitions are available at equations indicates from
detection relevant predictors:
“Partial efficiencies = forage mass, kg/ha-1 + protein mass, g/kg-1 = stocked
densities; Body weight^0,75 per kg-1 :. growled + utilized + convergence =
total efficiencies; Production animal quantitative = mixture chemistry soil-
pastures + qualitative “ideotype grasses”:. Priors results in the largest
differences between systems.”
To be able to included these priors in the overview, we have only considered the
dominance nitrogenous-nutritional availability to asses convergence and manually
chemical the trace-plots [Kjeldahl Analyses, methodologies] were calculated a deeper
investigation into the divergent transitions and alternative parametrizations “real” of the
[N*6.25 = -1 < p > 1:. -0.7= SD±1.14 g/kg] - extended the analyses: leaf:colm
relationships; in general, the theoretical predictor mean error squad did differ substantive
[P2O5 + N] from the variables recycles of conversion in linear correlation of formation
initials in except in condition it pays to make the redefined the equations for mutations
micro-biologic-crops are exactly mutate bite biologic the states of each off-steps with
probability 3/4 times we immediately the effects of truncation in analyzed using the
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ISSN: 2525-8761
MIXED procedure in SPSS software distribution between put-and-take and stocking rate
and density equations how favorable transient of period of management intense in
pasture.
In used remains constant and the equation of mean is a linear is no recall
differences equation mathematical to total efficiency in gain residual, as characteristics
rates which is appliance this predicts approximations are too crude protein:energy; this
simple model does explain the overall behavior; initial from effects variable decays
rapidly to then there is a long period as the mean appropriate its equilibrium values and
obtained estimates for the characteristics importance associate with linear a phase by
equilibrium values between mean is variable to consumed. We can sensed which from 60
and 80% due protein, were available these analyses on relationships a digestible crude
protein, to long of development the value nutrient increase on relation to management
and environmental.
3 DISCUSSION
These effects on physical, chemical and microbial are importations for the
processes from decomposition give organic matter utilize thought plants (Balota et al.,
2003). An action physical of soil and correlate forage mass are variables relation between
of the points interconnect with soil-plant per an average gain forage mass on response
interactive with possible by modify between systems. Drying is necessary in the herbage
(usually, 750-850 g/kg-1) depends upon the stage of growth, plant species or variety,
fertilizer nitrogen use and the amount of external water in form rain (Frame and Hunt,
1971).
The microbial and total carbon support the development give plant, cycling the
nutrients for plant, maintain a health soil to long of time (Jousset et al., 2011; USDA-
NRCS, 2019; Fierer, 2017). The microbial biomass drives nutrient mineralization and is
a small but labile source of major plants [fertilizer-nutritional] (Jenkinson and Ladd
1981; Dick 1992).
The growth of the tropical pasture is basically initial by the forage mass per light
interception 95%, the pattern of regrowth changes, occur reduction in the residue – forage
remaining on the land after harvest (Kichel et al., 2014; Marchezan et al., 1998; Marten,
1981; Silva et al., 2015; Souza et al., 2013). Research techniques in forage evaluation to
evolves at forage characterization therefor grass ecosystem are important to concentrate
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enforce and energy with high forage mass, intermittent or variable stocks, regulator put-
and-take and with good production mass (Sollenberg, 1993).
A chemical impacts from pasture management on soils acids, to long-time, the
impacts for microbiology reduce considerably and reduce total carbon, considerable
crops (Yang et al., 2019).
This is gravimeter humid soil and important for reduce the heat of soil surface
layer salient a conductivity thermal and response fertilizer with efficiency reactive by
transfer efficient for plant (Tornema et al., 2002).
The model applicant on area by integration on texture medium for tillage crops
from growing physiology for productions grass crop and infrequent under management
continuous grassland with short modification (Tormena et al., 2002; Vogel and Fey,
2016).
4 CONCLUSIONS
Is that we considers macroscopic suggestions pastures sum supplemental
associates to process from developers effects environmental did make provides options
by utilization scales production for models dynamics and yours technique:. A composite
chemistry were superiors for over particles ad equates indicators for detection over
as parts between: Partial efficiencies = forage mass, kg/ha-1 + protein mass, g/kg-1 =
stocked densities; Body weight^0,75 per kg-1 :. growled + utilized + convergence = total
efficiencies; Production animal quantitative = mixture chemistry soil-pastures +
qualitative “ideotype grasses”:. Priors results in the largest differences between
systems, for fitness, how in general parameters similarities the cost relatively per total
efficiency per hectare over time [P2O5 + N] and return residual stocking rate [beef cattle]
in relation conventional systems sea the management the point intrinsic express
resultant light incidence, climate and crops; the effects of truncation + forage mass
+ animal unit, ha-1 > forage mass + qualitative mass = stocked densities =
brachiariagrasses:. Cuts-residual > [randomized complete block design] :. PMSE.
We have gone through a lot of calculations observes a matrices of accords how a
biologic efficiencies in performance positively per two parameters cites, linearly
correlation directions from availability and introducing higher obtain of the calculates.
“What are formations of the process mathematical appliance in micro-
biologic to long times per effects truncates in systems general relatively from
high-dimensional cutting, is better return total of efficiency?”
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Notes, which results are available for the groups in conditional -1 < p > 1, since
“yes” conditional structure is present in the conditions; denotes the prior guess for the
number of relevant variables, “p0” which was set to the true number of relevant variables,
except in conditions 2 where all “number” variables are relevant, so we set “p0” and for
the classical analyses eventual in penalization methods, were selection automatically
shrink some coefficients to exactly zero so that no criterion such as a confidence interval
for variable selection is needed and included process mathematical applicability in
different correct or false stocking rates.
Imputation of missing values high-dimensional cutting and qualitative mass per
total of efficiencies, removing all cases with missing values to provide an illustration of
the shrinkage methods in a sparse data set from the treatments.
ACKNOWLEDGMENTS
The Ministry of Science, Technology, Innovation and Communications to the lengths and
support the bases of scientific research in support of technical and practical development
for the understanding and use of scientific techniques that take into consideration the
young teachers and doctors.
Compliance with ethical standards
CONFLICT OF INTEREST
The authors declare that they have no conflict of interest.
SUPPLEMENTAL
A classification of Köppen and Geiger (Aw) were registered an average annual by 1.200
mm. At fertilization plain soil were application on formation by urea 100.0 and 150.0 kg
-1
ha N and monodic phosphate 100.0 ha-1 N and 187.5 kg ha-1 P, respectively. A
fertilization yearling and with the intuit by attained the dry matter ingestion of cattle.
Randomized complete block design sensed two fertilizers divided on two time 66% and
34% a cased 35 days. A characteristic of soil in area and type Oi-soil, medium texture,
with a depth 0.0-0.2 m: pHH2O = 4.8; P = 4.1 mg kg; Ca+Mg = 1.6 cmolc dm-3; K = 0.18
cmolc dm-3; Al = 0.1 cmolc dm-3; H+Al = 3.1 cmolc dm-3 and total carbon = 13.8 g kg-1.
The calculation for samples area scissors was completely expanded green leaves with the
obtained per area by 200cm2. The residue forage was renamed on the land after harvest.
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ISSN: 2525-8761
Afterwards, there were samples taken to the oven with forced air at 85ºC until reached
constant weight, obtained forage mass total dry weight of forage per unit area of land. A
sub-part give sample 20 g ground to pass per Willey Hammer Crusher per moist screen
1 mm analyses dry matter, ash, crude protein, total nitrogen, indigestible and acid neutral
detergent nitrogen, acid and neutral detergent fibers and lignin (Detmann, 2012). The
vigor give plant evaluated through stock rate on production give dry matter to 21 days
after cut and a relation of day what initial an entire of first cut, available a quantity mass:
forage mass (kg/ha-1) and residue (kg/ha-1). The treatments were palisade grass
(Urochloa brizantha cv. Marandu) pastures and grazing systems or mixture of signal
grass, palisade grass grazing systems only completely randomized design with twelve
replicates. Forage and soil samples collected twelve points an every 28 days.
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ISSN: 2525-8761
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