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TRS value of sugarcane according to bioenergy and sugar levels/ Valor de ATR da cana-de-acucar em funcao de teores de bioenergia e acucar.

Introduction

Biomass is an important energy source for the human race. It is the natural way of storing a fraction of incident solar energy in the planet, and even fossil fuels originated from biomass. The challenge facing humanity is to seek solutions for ever more efficient use of this natural resource (ROSSETO, 2012).

Analyzing the waste products from the most important commercial monocultures in the country, sugarcane stands out due to the abundance of straw residue (green leaves, dry leaves and tops) (SOUSA; MACEDO, 2010).

Historically, sugarcane has been harvested to obtain sugar, and more recently for ethanol production as well. In both cases, the interest is centered on maximizing production of sucrose and raw materials. A certain amount of fiber in the stem, which can vary between 10 and 15% in weight, was always able to meet the energy needs of a plant, even when operating rather inefficiently. Currently, special attention is being given to sugarcane fiber levels, as it is possible to use second-generation ethanol and lignin as energy sources in steam boilers. Under tropical conditions, some clones have been found to be able to accumulate more dry matter and higher levels of energy fiber (LEON et al., 2010). And according to Inman-Bamber et al. (2011), some sugarcane clones can yield higher amounts of fiber without significant losses in sucrose levels, but possibly reducing total recoverable sugars (TRS), compromising quality-based payment. According to Rosseto (2012), a more efficient manner to compare plants according to quality of produced biomass is to convert all biomass into a single energy unit, which could be Joule (J); Mega Joule (MJ); Giga Joule (GJ) or ton of oil equivalent (1 toe = 42 GJ).

The bioelectricity generated from sugarcane bagasse has gained importance as a product in Brazilian power plants (MARTINES FILHO et al., 2006). In 2008, about 30 plants in Brazil negotiated an average of 544 MW for sale annually over 15 years. That volume generated US$ 389.6 million in annual revenue (SOUSA; MACEDO, 2010).

With an increase of 4.3% over the previous harvest, sugarcane production in Brazil has expanded to an expected 8.5 million hectares in producing states for the 2012/13 season, with Sao Paulo state leading the pack with 4.42 million hectares. Total projections call for 596.63 million tons of sugarcane to be milled in the 2012/13 harvest, a 6.5% increase over the 2011/12 season, meaning that 36.3 million more tons will be milled than during the previous harvest (CONAB, 2012).

The essence of the current payment system (CONSECANA) is to reward sugarcane quality based on the prices of the final products obtained from this raw material; as such, there is no single price per ton, with variations according to climate factors, soil, variety, farming practices and marketing mix of the industrial unit. Soil tillage for crop placement can result in higher growth rates and lead to changes in quality at harvest time (TAVARES et al., 2010). Mechanized sugarcane harvest creates straw residue, which depending on the handling system can result in lower biomass and bioenergy production (CAMPOS et al., 2010). Revisions to the payment system are important to eliminate distortions and stimulate an improvement in the quality of raw materials (SACHS, 2007).

The research hypothesis was that the energy value of wet bagasse can create an additional parameter to calculate TRS in order to obtain a fair compensation for the material delivered at processing plants.

The objective of the project was to propose changes in the procedures used to mathematically determine TRS, estimated by the calorific value of moist cake and weight of moist cake, in addition to previously used factors--Calorific Value (CV), RSS and Industrial Fiber. The intent is to collaborate towards a more accurate payment formula for sugarcane--one that does not necessarily imply higher prices, but rather values that better fit existing profit margins for the different by-products produced from the raw material.

Material and methods

A total of 128 sugarcane samples from the experiment were analyzed--64 in 2010, and 64 in 2011. The soil in the experiments was characterized as a Dystrophic Red-Yellow Argisol, typical to moderate, with medium-clayish texture (SANTOS et al., 2006). The climate in the region is classified as Aw, with rainy summers and dry winters.

A DDS Cal2K bomb calorimeter was used to analyze the gross calorific value, in accordance with criteria set by the Brazilian Association for Technical Standards--ABNT in rule NBR 8693/84 (VALE et al., 2007). The analysis was carried out in moist cake obtained after milling (FERNANDES, 2003).

The Hawaiian method was used to analyze real fiber (VALSECHI, 1968).

All data were charted and subjected to correlation analysis and graph creation using Microcal Origin 6.0 mathematical software.

Results and discussion

Considering the distribution of energy in sugarcane, the following model can be written:

[[epsilon].sub.sugarcane] = [[epsilon].sub.fiber] + [[epsilon].sub.sugars] + [[epsilon].sub.others organics materials] (1)

In which:

[[epsilon].sub.sugarcane] = Total energy in sugarcane

[[epsilon].sub.fiber] = energy of fiber in the sugarcane

[[epsilon].sub.sugars] = energy of sugars in the sugarcane

[[epsilon].sub.other organic materials] = energy of non-sugars in the sugarcane

As the bioenergy of a material is determined by the gross calorific value, we get:

[CV.sub.sugarcane] = [F%sugarcane/100] * [CV.sub.fiver] + [TRS * [CV.sub.sugar]/90,5] + [[non - sugar organic * [CV.sub.nso]]/100] (2)

[CV.sub.sugarcane] = Calorific value of sugarcane F%sugarcane = Values of fiber in sugarcane in

(%)

[CV.sub.fiber] = Calorific value of sugarcane fiber

TRS = Total recove rable sugars (90.5% of all sugars in sugarcane)

[CV.sub.nso] = Calorific value of non-sugar organic materiais

As the level of non-sugar organic materiais in sugarcane is 1.16%, TRS values are near 12% of sugarcane, and fiber averages 12%, non-organic materials represent 4.83% of the sum of TRS plus Fiber, making it possible to exclude it from the formula or leave it as a constant C:

[CV.sub.sugarcane] = [F%sugarcane/100] * [CV.sub.fiver] + [[TRS * [CV.sub.sugar]]/90,5] (+ C) (3)

Isolating variable TRS, we get:

TRS = [[CV.sub.sugarcane] - [F7sugarcane/100] * [CV.sub.fiver] (-c)] * [90,5/[CV.sub.sugar]] (4)

The Calorific value of sugar ([CV.sub.sugar]) used was = 17 MJ [kg.sup.-1], the Calorific value of non-sugar organic materials ([CV.sub.nso]) used was = 20 MJ [kg.sup.-1]. Using the data in Table 1, regressions were done using Origin 6.0 software.

Figure 1 presents the regression between the Calorific value of sugarcane obtained from analyses directly in the material and Calorific value of sugarcane calculated with the value of the Calorific value of moist cake obtained after pressing for analysis. Despite the low value of the coefficient of determination [r.sup.2], it can be observed that the regression has a significant value at 1%. This denotes a strong correlation between the variables, indicating the possibility of calculating the Calorific value of sugarcane by performing analyses in the fibrous material (moist cake) produced by preparing the sample for payment purposes. In this case, as cited by Sachs (2007), revisions to the payment system can result in better quality sugarcane and stimulate producers; however, the COSECANA payment system is complex and quite structured, with the possibility of adding certain factors as long as they are mutually interesting for mill owners and sugarcane suppliers.

The inclusion of the Calorific value of sugarcane should occur naturally, as Rosseto (2012) reports that the best way to compare plants is by their bioenergy, and their assessment to that end should be simple and without great changes in methodology.

Figure 2 presents the regression between real fiber analyzed directly in sugarcane and Industrial fiber calculated using the weight of moist cake (WMC). Despite the low value for the coefficient of determination [r.sup.2], it can be seen that the regression has statistical value at 1%. This indicates a strong correlation between the variables. This consideration allowed CONSECANA to incorporate the calculation of Industrial fiber through WMC into the model already in place in Brazil.

[FIGURE 1 OMITTED]

[FIGURE 2 OMITTED]

Figure 3 presents the regression between the Calorific value of real fiber analyzed directly in sugarcane fiber and the Calorific value of moist cake (WB). It can be observed that the regression is statistically significant at 1%. This indicates a strong correlation between the variables.

[FIGURE 3 OMITTED]

In equation 4, the value of [CV.sub.cane] (the first independent variable) can be calculated through the calorific value of moist cake, as shown in Figure 1; those data showed a correlation coefficient at 1%. The second independent variable shown in this model is [F%.sub.Cane], which from Figure 2 can be calculated using the Weight of Moist cake (WMC), with a correlation coefficient at 1%, which is already used by the CONSECANA system. The third independent variable, [CV.sub.fiber], can be calculated from Figure 3 using the calorific value of moist cake. [CV.sub.sugar] is constant, equal to 17 MJ [kg.sup.-1]. Thus, the TRS value can be estimated by a mathematical model using the variables WMC and CVmc. As Figures 1, 2 and 3 show values for the regression coefficient of determination [r.sup.2] that are significant at 1%, it was decided to perform a multiple regression between TRS, Calorific value of sugarcane, calculated with the calorific value of moist cake, Fiber calculated with the weight of moist cake and calorific value of moist cake.

The following model is obtained (Table 2), adjusted to the values:

Y = 40.24 + 21.72*X1 + 13.4*X2 - 8.28*X3 (5)

in which:

Y = Total recoverable sugars, estimated; X1 = Calorific value of sugarcane calculated with the calorific value of moist cake; X2 = Fiber calculated with the moist cake obtained during pressing; X3 = Calorific value of moist cake; [R.sup.2] = 0.60 **; CV = 9.17% between calculated TRS values and real TRS values.

It has also (CONSECANA, 2011):

Y = 9. 6316*X4 + 9.15*X5 (6)

In which:

- X4 = Pol in Cane (PC);

- X5 = Reducing sugars in sugarcane (RSS).

By adding equations 5 and 6, we get:

Y = 40.24 + 21.72*X1 + 13.4*X2 - 8.28*X3 (5)

Y = 9. 6316*X4 + 9.15*X5 (6)

2Y = 40.24 + 21.72*X1 + 13.4*X2 - 8.28*X3 + 9. 6316*X4 + 9.15*X5 (7)

Y = [40.24 + 21.72*X1 + 13.4*X2 - 8.28*X3 + 9. 6316*X4 + 9.15*X5)]/2 (8)

Y = 20.12 + 10.86*X1 + 6.70*X2 - 4.14*X3 + 4.8158*X4 + 4.575*X5 (9)

or,

TRS = 20.12 + 10.86*PCCCCVMC + 6.70*Fpmc - 4.14*CVmc+ 4.8158*PC + 4.575*RSS (10)

The press methodology used 500 g of shredded sugarcane; WMC is obtained after pressing, ranging from 110 to 160 g. In order to transform the calorific value of WMC into the calorific value of sugarcane, the following model should be used:

PCCCCVMC = (CVmc/500) * WMC (11)

In the CONSECANA methodology, the industrial fiber calculated with WMC follows the model below:

[F.sub.industrial] = 0.08*WMC + 0.876 (12)

The final model is therefore:

TRS = 20.12 + 10.86* (CVmc/500) * WMC + 6.70 * (0.08*WMC+0.876) - 4.14*CVmc ++ 4.8158*PC + 4.575*RSS (13)

We therefore obtain TRS calculated as a function of the Calorific value of moist cake (CVmc), weight of moist cake (WMC), Pol in sugarCane (PC) and Reducing Sugars in Sugarcane (RSS), equations 14.

TRS = 25.9892 + 0.02172*CVmc* WMC+0.536*WMC - 4.14*CVmc + 4.8158*PC + 4.575*RSS (14)

Table 3 shows that of the 128 analyses undertaken, the proposed model estimated TRS, on average, to be 1.25 kg more per ton of sugarcane than the traditional CONSECANA formula, which obtained an average of 88.96. However, the model estimated both higher and lower values than the CONSECANA model, depending on the percentage composition of the components in the model. Therefore, the proposed formula estimated values with 11.08% more TRS; this may be related to the C constant obtained from the calorific value of non-sugar organic materials, for which there are no routine analyses in raw-material sugarcane for payment purposes.

Conclusion

It is possible to estimate TRS values using the Calorific value of moist cake, weight of moist cake, Pol in cane and Reducing Sugars in sugarcane.

The proposed model estimated TRS values to be 11.08% higher than in the CONSECANA model, due to non-sugar organic materials.

Doi: 10.4025/actasciagron.v37i3.19065

Acknowledgements

To FAPESP for providing the technical and financial feasibility for the project.

To CENTEC, Center for Advanced Studies in Bioenergy and Sugar-Ethanol Technology at UNOESTE, for the support in the development of the research study.

References

CAMPOS, L. H. F.; CARVALHO, S. J. P.; CHRISTOFFOLETI, P. J.; FORTES, C.; SILVA, J. S. Sistemas de manejo da palhada influenciam acumulo de biomassa e produtividade da cana-de-acucar (var. RB855453). Acta Scientiarum. Agronomy, v. 32, n. 2, p. 345-350, 2010.

CONAB-Companhia Nacional de Abastecimento. Acompanhamento de safra brasileira: cana-de-acucar, segundo levantamento. agosto/2012--Brasilia: Conab 2012.

CONSECANA-Conselho dos Produtores de Cana-deAcucar, Acucar e Alcool do Estado de Sao Paulo. Circular no. 01/11 de 29 de abril de 2011. Sao Paulo: Consecana 2011.

FERNANDES, A. C. Calculos na agroindustria da canade-acucar. 2. ed. Piracicaba: EME/STAB, 2003.

INMAN-BAMBER, N. G.; JACKSON, P. A.; HEWIT, M. Sucrose accumulation in sugarcane stalks does not limit photosynthesis and biomass production. Crop and Pasture Science, v. 62, n. 10, p. 848-858, 2011.

LEON, R. G.; GILBERT, R. A.; KORNDORFER, P. H.; COMSTOCK, J. C. Selection criteria and performance of energycane clones (Saccharum spp. X S. spontaneum) for biomass production under tropical and sub-tropical Conditions. Ceiba, v. 51, n. 1. p. 11-16. 2010.

MARTINES-FILHO, J.; BURNQUIST, H. L.; VIAN, C. E. F. Bioenergy and the Rise of Sugarcane-Based Ethanol in Brazil. Choices. 2nd quarter, v. 21, n. 2. p. 91-96, 2006.

ROSSETO, R. A bioenergia, a cana energia e outras culturas energeticas. Pesquisa e Tecnologia, v. 9, n. 1, p. 1-6, 2012. SACHS, R. C. C. Remuneracao da tonelada de cana-deacucar no Estado de Sao Paulo. Informacoes Economicas, v. 37, n. 2, p. 55-66. 2007.

SANTOS, H. G.; JACOMINE, P. K. T.; ANJOS, L. H. C.; OLIVEIRA, V. A.; OLIVEIRA, J. B.; COELHO, M. R.; LUMBRERAS, J. F.; CUNHA, T. J. F. Sistema brasileiro de classificacao de solos. 2. ed. Rio de Janeiro: Embrapa Solos, 2006.

SOUSA, E. L. L.; MACEDO, I. C. Etanol e bioeletricidade: a cana-de-acucar no futuro da matriz energetica. Sao Paulo: Luc Projetos de Comunicacao, 2010.

TAVARES, O. C. H.; LIMA, E.; ZONTA, E. Crescimento e produtividade da cana planta cultivada em diferentes sistemas de preparo do solo e de colheita. Acta Scientiarum. Agronomy, v. 32, n. 1, p. 61-68, 2010.

VALE, A. T.; GENTIL, L. V.; GONCALEZ, J. C. COSTA, A. F. Caracterizacao energetica e rendimento da carbonizacao de residuos de graos de cafe (Coffea arabica L.) e de madeira (Cedrelinga catenaeformis) Duke. Cerne, v. 13, n. 4. p. 416-420. 2007.

VALSECHI, O. Curso de aperfeicoamento para fiscalizacao de analises em cana-de-acucar. Piracicaba: CALQ, 1968.

Received on November 6, 2012.

Accepted on May 4, 2013.

Tadeu Alcides Marques (1) *, Larissa Carolina Goncalves Neves (1), Erick Malheiros Rampazo (1), Elvis Lima Deltrejo Junior (1), Fernando Caetano de Souza (1) and Patricia Angelica Alves Marques (2)

(1) Centro de Estudos Avancados em Bioenergia e Tecnologia Sucroalcooleira, Universidade do Oeste Paulista, Rod. Raposo Tavares, km 572, 19067-175, Presidente Prudente, Sao Paulo, Brazil. (2) Departamento de Engenharia de Biossistemas, Instituto Nacional de Ciencia e Tecnologia em Engenharia da Irrigacao, Escola Superior de Agricultura Luiz de Queiroz, Universidade de Sao Paulo. Piracicaba, Sao Paulo, Brazil. * Author for correspondence. E-mail: tmarques@uol.com.br
Table 1. Results obtained for variables Analyzed calorific value of
sugarcane, Calculated calorific value of sugarcane, Real fiber,
Fiber press method, Calorific value of real fiber, and Calorific
value of moist cake.

           (Figura 1)                       (Figura 2)

Calorific value   Calorific value   Real fiber   Fiber--Press
of sugarcane       of sugarcane        (%)        Calculated
Analyzed          Calculated with
Gj [kg.sup.-1]      Moist cake
                  Gj [kg.sup.-1]

3.25                    2.30            9.71         11.48
3.70                    3.03           10.65         11.35
3.75                    2.79           11.23         11.19
4.77                    2.04            9.62         10.74
5.09                    2.69           10.24         11.53
4.10                    3.07           10.32         12.21
4.49                    2.62           10.07         11.24
4.76                    2.53           10.43         11.01
3.88                    3.62           11.09         10.66
5.77                    2.91           11.44         13.51
6.00                    3.45           11.26         14.13
7.65                    2.69            9.62         12.26
5.27                    2.44           11.32         13.37
6.34                    2.27           13.02         12.20
6.47                    2.93           11.70         13.40
7.90                    3.18           12.26         12.78
4.64                    2.69           11.68         12.31
5.86                    3.36           11.20         12.60
5.35                    1.91           12.24         10.77
4.86                    2.68           11.66         11.98
5.14                    3.39           13.72         13.31
8.08                    2.72           12.26         13.27
6.47                    3.14           12.06         14.11
5.56                    3.18           10.68         13.21
5.10                    3.36           11.04         14.06
8.72                    3.83           11.88         13.53
5.49                    2.82           11.58         12.56
6.19                    3.68           14.22         13.95
8.46                    3.25           13.00         14.35
5.61                    2.45           11.52         12.32
6.12                    2.93            9.72         13.16
5.85                    2.77           13.18         13.04
5.58                    2.99            9.82         12.95
7.40                    4.27           11.62         12.79
6.73                    2.97           11.24         13.17
5.53                    2.76           11.18         12.09
5.87                    3.70           10.82         13.07

             (Figura 3)

Calorific value    Calorific value
Real fiber--        of moist cake
analyzed           (Mj [kg.sup.-1])
(Mj [kg.sup.-1])

18.08                   8.69
18.09                   11.57
17.46                   10.80
21.19                   8.27
18.39                   10.10
27.45                   10.82
17.69                   10.12
20.33                   10.00
18.01                   14.80
18.74                   9.21
16.21                   10.42
18.16                   9.46
18.40                   7.82
18.12                   8.03
16.42                   9.36
21.75                   10.69
18.24                   9.42
20.28                   11.48
18.12                   7.72
18.51                   9.66
18.70                   10.90
25.80                   8.79
18.32                   9.48
18.57                   10.30
26.60                   10.18
18.81                   12.11
17.09                   9.64
20.67                   11.26
18.40                   9.64
18.71                   8.57
14.94                   9.54
18.64                   9.11
17.15                   9.91
18.17                   14.33
18.60                   9.67
26.73                   9.83
17.52                   12.14

Table 2. Values of r, F-test and Coefficients of the multiple
regression model between TRS (Y), Calorific value of sugarcane,
calculated with the calorific value of moist cake (X1), Fiber
calculated with the moist cake obtained in pressing (X2) and
calorific value of moist cake (X3).

Regression statistic

R-multiple
R-squared
Adjusted R-squared
Standard error
Observation

ANOVA
                          Gl              SQ           QM

Regression                3            7703.30       2567.77
Waste material            69           5163.73        74.84
Total                     72           12867.03

                     Coefficients   Standard error   t-stat

Intersection            40.24           71.62         0.28
Variable X 1            21.72           23.92         0.45
Variable X 2             13.4            6.16         1.09
Variable X 3            -8.28            6.42         -0.65

Regression statistic

R-multiple                     0.773747483
R-squared                      0.598685168
Adjusted R-squared             0.581236697
Standard error                 8.650817496
Observation                         73

ANOVA
                        F      significance

Regression            34.31      1.09E-13
Waste material
Total

                     P-value    Bottom 95%

Intersection          0.78       -122.75
Variable X 1          0.65        -36.86
Variable X 2          0.28        -5.59
Variable X 3          0.52        -16.95

Table 3. TRS values calculated with the original CONSECANA model,
confronted against the proposed model, which takes into account the
calorific value of moist cake and the amount of moist cake produced
in 0.5kg of pressed sugarcane.

TRS        TRSproposed   dev.    [dev..sup.2]    PC     RSS

123.53       147.85      24.32      591.42      12.08   0.79
130.23       146.28      16.05      257.51      12.73   0.83
119.18       140.23      21.06      443.32      11.57   0.84
138.17       149.07      10.90      118.89      13.68   0.70
136.48       153.00      16.52      272.95      13.47   0.74
140.21       160.52      20.31      412.48      13.92   0.67
143.35       153.68      10.32      106.56      14.20   0.72
143.39       151.73      08.35      069.71      14.24   0.68
124.76       131.96      07.20      051.90      12.19   0.81
126.24       135.15      08.90      079.29      12.45   0.69
120.60       139.04      18.44      339.97      11.72   0.84
118.95       130.28      11.33      128.34      11.56   0.83
110.59       134.19      23.60      556.95      10.62   0.90
103.07       122.34      19.28      371.64      9.80    0.95
115.07       130.49      15.41      237.56      11.10   0.89
115.60       142.53      26.92      724.82      11.24   0.81
124.89       144.08      19.18      368.05      12.16   0.85
142.62       162.43      19.81      392.43      14.19   0.65
125.84       144.21      18.37      337.36      12.93   0.15
119.53       142.84      23.31      543.58      11.57   0.89
...            ...        ...        ...         ...    ...
113.63       131.62      17.99      323.56      11.06   0.78
140.58       157.00      16.42      269.71      16.32   0.00
147.73       161.78      14.04      197.23      15.34   0.00
150.38       167.97      17.59      309.31      14.92   0.73
136.13       152.46      16.33      266.82      13.12   1.07
140.81       149.31      08.50      072.33      14.47   0.16
146.01       159.74      13.73      188.57      14.63   0.55
136.75       155.96      19.21      368.91      13.38   0.86
149.50       166.79      17.29      298.81      14.75   0.81
145.75       175.19      29.45      867.05      14.35   0.82
159.85       162.66      02.81      007.92      16.20   0.42
152.04       163.20      11.16      124.57      15.08   0.74
152.67       164.34      11.67      136.18      16.34   0.00
154.72       171.15      16.43      270.02      15.65   0.44
138.41       160.52      22.11      488.87      13.77   0.63
151.49       174.51      23.02      529.92      15.10   0.66
162.85       185.24      22.39      501.32      16.43   0.50
159.70       175.45      15.75      248.14      16.10   0.51
171.75       176.18      04.44      019.67      17.36   0.50
178.67       184.21      05.53      030.63      18.11   0.47
149.37       172.35      22.98      528.20      15.01   0.52
179.49       182.83      03.34      011.13      18.16   0.50
179.64       186.08      06.44      041.52      18.14   0.54
172.16       178.92      06.76      045.74      17.39   0.51
150.66       206.94      56.28     3167.42      15.11   0.56
averages
140.30       156.47
VC =         11.08%

TRS        PCCCCVMC   Fpmc    CVmc

123.53       2.30     11.48   08.69
130.23       3.03     11.35   11.57
119.18       2.79     11.19   10.80
138.17       2.04     10.74   08.27
136.48       2.69     11.53   10.10
140.21       3.07     12.21   10.82
143.35       2.62     11.24   10.12
143.39       2.53     11.01   10.00
124.76       3.62     10.66   14.80
126.24       2.35     10.18   10.09
120.60       2.05     10.63   08.42
118.95       3.53     10.71   14.35
110.59       2.59     10.93   10.28
103.07       3.38     10.64   13.86
115.07       2.12     10.12   09.19
115.60       2.11     11.25   08.13
124.89       2.00     10.88   07.98
142.62       2.74     12.16   09.72
125.84       2.60     11.16   10.12
119.53       3.09     11.55   11.60
...          ...       ...     ...
113.63       2.36     10.44   09.87
140.58       2.90     11.80   10.62
147.73       2.67     11.82   09.77
150.38       2.68     12.30   09.40
136.13       1.68     10.98   06.64
140.81       2.27     10.77   09.18
146.01       3.23     11.93   11.70
136.75       2.60     11.76   09.56
149.50       2.93     12.32   10.25
145.75       3.24     13.41   10.33
159.85       2.71     11.35   10.36
152.04       2.77     11.79   10.15
152.67       2.82     11.89   10.23
154.72       3.00     12.51   10.32
138.41       2.89     12.23   10.18
151.49       3.02     13.00   09.96
162.85       3.18     13.54   10.04
159.70       2.46     12.51   08.46
171.75       2.77     12.09   09.89
178.67       2.69     12.51   09.25
149.37       3.13     12.92   10.39
179.49       2.67     12.33   9.34
179.64       3.18     12.80   10.67
172.16       3.06     12.44   10.60
150.66       2.62     12.40   09.40
averages
140.30
VC =
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Author:Marques, Tadeu Alcides; Neves, Larissa Carolina Goncalves; Rampazo, Erick Malheiros; Deltrejo, Elvis
Publication:Acta Scientiarum. Agronomy (UEM)
Date:Jul 1, 2015
Words:4292
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