All submissions of the EM system will be redirected to Online Manuscript Submission System. Authors are requested to submit articles directly to Online Manuscript Submission System of respective journal.
Research Article

Agricultural performance and genetic parameters for yield-related traits of sugar- and energy cane families derived from planned crosses

Received: July 10, 2017
Accepted: August 28, 2017
Published: September 27, 2017
Genet.Mol.Res. 16(3): gmr16039773
DOI: 10.4238/gmr16039773


The forecast of a growing energy demand in the coming years has aroused particular interest in biomass for energy cogeneration, to diversify the energy matrix by using clean and renewable sources. To meet the new demands of the sugarcane industry, this study evaluated the agronomic performance and estimated genetic parameters for yield traits in sugar- and energy cane families derived from planned crosses. The cane families were assessed in the northwest of the State of Paraná, county of Paranavaí, in a randomized complete block design, with three replications. The evaluations were carried out 12 months after the first cut, in the ratoon cane cycle, in December 2014, under very unfavorable conditions for the crop, due to the low fertility and water-holding capacity of the soil. Besides, the crop was evaluated at the end of the harvest, when the agricultural and industrial quality of the crop is reduced. The following traits were evaluated at the plot level: soluble solids content, apparent sucrose content (PC), fiber content, tons of cane per hectare, tons of sucrose per hectare (TSH), and tons of fiber per hectare (TFH). High genetic variability was observed for all evaluated traits, with accuracy estimates from 0.69 (TSH) to 0.92 (PC), and high heritability (up to 0.84), indicating the possibility of genetic progress. The sugarcane families derived from crosses of Saccharum spontaneum and Saccharum robustum species with sugarcane hybrids had the highest fiber contents. Highest sugar contents were found in sugarcane families resulting from crosses of sugarcane clones and conventional cultivars. The TSH means were highest in the families F160 x MEX68- 200 and RB855156 x RB987935. The highest genotypic mean for TFH was observed in the special polycross involving cultivar RB036066 with S. spontaneum accessions as pollen donors.


Sugarcane (Saccharum spp) is one of the most efficient crops regarding solar-tochemical energy conversion, for being a C4 species with high biomass production (Tew and Cobill, 2008). In Brazil, it is one of the main, economically most competitive options for biomass production, mainly because of the well-established and equipped processing industry, the high standards of cultivation and processing techniques, as well as the considerable number of sugar mill plants distributed throughout the country (Matsuoka et al., 2014).

Biomass has been identified as one of the main alternatives for the diversification of the energy matrix, contributing to the reduction of the use of fossil fuels. This energy source has attracted interest due to the expected strong growth in energy demand in the coming years (Vichi and Mansor, 2009).

According to Dal-Bianco et al. (2012), breeding work with sugarcane has obtained increases in sucrose yield over centuries, and the current commercial cultivars were selected for a higher sucrose content and lower fiber production. With the feasibility of using straw and the prospect of using the entire cane biomass in the production of cellulosic ethanol and other products, new lines of sugarcane research have arisen in Brazil and other countries, mainly focused on increasing the fiber content and biomass production of future cultivars (Matsuoka et al., 2014; Silveira et al., 2016).

The species Saccharum spontaneum and Saccharum robustum have higher fiber contents than the current cultivars (Saccharum spp). To increase the fiber content of future cultivars, some researchers propose the exploitation of crosses between accessions of these species with sugarcane cultivars with high yields, aiming at the selection of clones with high biomass production and higher fiber contents, called energy cane (Ming et al., 2006; Wang et al., 2008; Silveira et al., 2015a,b, 2016; Ramos et al., 2017; de Azeredo et al., 2017).

According to Tew and Cobill (2008), the currently grown sugarcane cultivars contain approximately 12% fiber, 13% sugar, and 75% water. By breeding, energy cane cultivars can be developed containing 30% fiber, 5% sugar, and 65% water. The development of genotypes with this composition is a relatively long process. It should also be remembered that the industry of the sector is not yet ready to process biomass with fiber contents above 20%, but the development of cultivars with fiber contents of around 17% that maintain a sucrose content of approximately 13% would meet the current needs of the sugar-energy sector. This type of cultivar would increase the electric power production capacity by increasing fiber percentage and consequently bagasse quality, without causing losses in sugar production (Matsuoka et al., 2014).

For many researchers, after hybridization, the families must be tested, performing individual selection in families with high genotypic values, increasing the probability of finding superior clones in the progenies (Simmonds, 1996; Kimbeng and Cox, 2003; Barbosa et al., 2005; Resende and Barbosa, 2006). Several breeding programs have routinely applied family selection and demonstrated the advantages of developing transgressive clones, promoting genetic progress and contributing to the establishment of new cultivars (Stringer et al., 2011; Oliveira et al., 2011; Barbosa et al., 2012; Zeni Neto et al., 2013; Brasileiro et al., 2016).

In view of the need to obtain cultivars that meet the current and future demands of the sugarcane industry, parents previously not used in sugarcane hybridization programs, such as accessions of S. spontaneum and S. robustum, started to arouse the interest of the breeders, mainly due to the need for a new biotype for the crop, i.e., the search for energy cane cultivars, created a new demand and new parents were incorporated into the hybridization programs. Accordingly, given the need to know the potential of these parents, the objective of this study was to evaluate the agricultural performance and to estimate genetic parameters for yieldrelated traits of sugar- and energy cane families derived from planned crosses.

Material and Methods

In this study, 30 families of crosses planned according to their genealogy were evaluated, 5 of them for sugarcane (SC), with elite sugarcane parents (clones and cultivars); 12 intermediate (INT) families of the second and third generations of S. spontaneum, 13 energy cane (EC) accessions and descendants of S. spontaneum and S. robustum (Table 1).

Mother Father Parents Mother Father Parents
B35187 Co617 MEX68-200 RB72454 TUC71-7 RB855156
Co421 Co313 CoS245 RB72454 ? RB867515
Co951 Co419 Co62175 RB855156 RB815690 RB966928
CP71-321 US72-19 TUC77-42 SP71-1088 H57-5028 SP80-3280
L65-69 SES297A US74-103 Co740 SP70-1143 IAC87-3396
NCo310 PT43-52 F150 Co62175 RB72454 RB01640
NCo310 F141 F160 SP70-1143 SP77-5181 RB036066
NG28288 S. spontaneum B70710 RB745464 RB92524 RB04813
POJ2364 EK28 POJ2878 NA56-79 SP70-1143 RB83102
POJ2878 Co285 Co421 RB75126 RB72199 RB92579
POJ2878 Co285 Co617 RB72454 ? RB93509
S. robustum ? IM76-228 CP70-1547 SP71-1279 SP81-3250
S. robustum ? 28NG289 RB835867 ? RB01623
S. robustum ? IM76-229 RB72454 RB83102 RB987935
S. spontaneum US60-313 US85-1008 RB855536 NA73-1454 RB965518
S. spontaneum ? IN84-58 SP80-3280 ? RB996961
S. spontaneum ? IN84-88 CP48-124 ? RB813804
Str. Mauritius S. spontaneum Co285 RB931013 RB72910 RB04823

Table 1: Genealogy of the parents used to obtain the 30 families evaluated in Paranavaí - PR, Brazil.

The crosses were carried out in 2012 at the Experimental Station Serra do Ouro (9°13'S, 35 °50'W, 450 m asl), of the Federal University of Alagoas, in the county of Murici, Alagoas.

After processing, the caryopses originated from the crosses were sent to an experimental station of the Federal University of Paraná, in Paranavaí, State of Paraná (23°05'S; 52°27'W; 503 m asl). The soil was of the LVE type, sandy texture (16% clay). Sowing, seedling production and planting of the experimental plots were carried out in February 2013, in a randomized complete block design, with three replications. Each plot consisted of 20 seedlings spaced 0.50 m apart, distributed in two 5-m long furrows spaced 1.40 m apart.

The mechanical cutting of the cane crop occurred in December 2013. The experiment was evaluated after 12 months (December 2014), in the ratoon cane cycle, which is a rather unfavorable harvest season due to the increased drought stress, causing losses in the agricultural and industrial quality of the crop.

The following traits were evaluated in the families at the plot level: a mean number of stalks per seedling (NSt), calculated as:

Equation (equation 1)

where n is the number of surviving clumps per plot; weight of one stalk (W1St), estimated by weighing 20 stalks per plot; sampling of 20 random stalks per plot for technical analysis in the laboratory, where the percentage values of soluble solids content (BRIX), apparent sucrose, also known as pol%cane (PC), and fiber (FIB) were determined.

The stalk weight (WSt) was calculated by weighing all plants per plot (total plot weight) and counting the number of stalks per plot, according to the expression:

Equation (equation 2)

The yield in tons of cane per hectare (TCH) was obtained by the expression:

Equation (equation 3)

where AP is the area occupied per clump per plot in m2 (AP = 1.12), and 10 is the constant used to convert plot weight to t/ha. Due to the dead plants in some plots of the experiment, there was a concern to calculate TCH by the above expressions, without penalizing the families with lower number of surviving plants, since a major part of the deaths was caused by sedimentation in the planting furrow due to heavy rainfall in the beginning of the experiment.

Based on TCH and PC the trait tons of sucrose per hectare (TSH) was estimated:

Equation (equation 4)

To calculate tons of fiber per hectare (TFH), the traits TCH were used in the expression:

Equation (equation 5)

For the analyses, the mean plot data were used, and the SELEGEN program (Resende, 2016), model 20 (random blocks, a test of independent clones, one plant per plot, or plot mean) was used, indicated in the form of a matrix by:

Equation (equation 6)

where: y is the known, observed data vector; r is the vector of effects of unknown replications (assumed as fixed); g is the vector of unknown genotypic effects (assumed as random); e is the vector of (random) errors; and X and Z are incidence matrices for the said effects, where g ~ N(0, G), e ~ N(0, R), E(y) = Xr, and V(y) = ZGZ’ + R. G is the matrix of variances and covariances of the genetic effects and R the matrix of variances and covariances of errors. For this model, the mixed model equations are as follows (Resende, 2002):

Equation (equation 7)

Results and Discussion

According to deviance analysis, the genotypic variance was significant for all traits, indicating the existence of genetic variability that can be explored by family selection (Table 2).

Traits General mean Vg CVg (%) CVe (%) h2 Ac
BRIX 19.85 1.31** 5.77 6.41 0.71 0.84
PC 12.96 2.46** 12.10 9.00 0.84 0.92
FIB 15.71 0.78** 5.62 6.24 0.71 0.84
TCH 87.71 339.94** 21.02 32.59 0.56 0.75
TSH 11.36 5.24* 20.15 36.79 0.47 0.69
TFH 13.67 9.02** 21.97 30.59 0.61 0.78

Table 2: General mean, genotypic variance (Vg), coefficient of genetic variation (CVg), coefficient of environmental variation (CVe), mean broad-sense heritability (h2), and accuracy (Ac) of yield and processing traits evaluated in 30 sugar- and energy cane families in Paranavaí, Paraná, Brazil.

The coefficients of genetic variation (CVg), which expressed the amount of genetic variation as a percentage of the general mean, were moderate for the processing traits: FIB and BRIX (5.62 and 5.77%, respectively); and high for PC (12.10%). For the yield-related traits TSH, TCH, and TFH, the values were high (20.15, 21.02, and 21.97%, respectively). In the studies of sugarcane families of Moraes et al. (2010), the results of CVg for TCH and TSH were very similar (19.51 and 19.56%), and lower for FIB, BRIX, and PC (1.46 to 5.08%). Balsalobre et al. (2016) reported very close values for BRIX, PC, and FIB, and lower values for the traits TCH and TSH.

The coefficient of environmental variation (CVe) is the parameter that indicates the level of experimental precision. The CVe for the processing traits were considered low, ranging from 6.24% for FIB to 9% for PC. However, the coefficients of variation of TCH, TSH, and TFH were higher (32.59, 36.78, and 30.60%, respectively) (Table 2). In studies with sugarcane families, Jackson et al. (1995) and Moraes et al. (2010) found similar values for these traits. In studies of energy cane families, Silveira et al. (2016) found very similar values of CVe for the traits PC, FIB, TCH, TSH, and TFH to those obtained in this study. The high value of CVe for TCH, according to the classification proposed by Gomes (1990), can be attributed in part to the data heterogeneity and the strong environmental influence on this complex trait. The same is true for TSH and TFH, which are dependent and highly correlated with TCH. In general, the experimental precision can be considered adequate considering the coefficient of environmental variation and the significance of genetic variability among the families evaluated (Table 2).

According to the classification proposed by Resende (2002), the estimated heritability (h2) values were considered high for all traits (above 0.50) except for TSH (very similar result, with 0.47). This indicated the influence of the genetic component of the expression of the respective traits, and consequently the possibility of success with selection (Table 2). These results are consistent with the study of Kang et al. (1983) for BRIX and TCH; of Melo et al. (2006), for PC, BRIX, FIB, and TCH; and in the stufy of Silva et al. (2011), for the traits BRIX, PC, TCH, and TSH. Silveira et al. (2016) found very close heritability values for PC, FIB, and TCH, and lower values for TSH and TFH in evaluations of sugarcane families.

Accuracy (Ac) indicates the precision of inferences about the genotypic means because, according to Resende (2002), this property informs about the correct ranking of families for selection purposes, and also about the efficacy of inference about the genotypic value, i.e., the correlation between predicted and true genotypic values. According to Resende and Duarte (2007), the results are moderate (0.69 or 69%) for TSH and very high (0.92 or 92%) for PC. The traits of interest for selection and classification of families were intermediate values (TCH = 0.75, TSH = 0.69; TFH = 0.78), indicating good precision and, therefore, the reliability of the estimated genetic values, ensuring security in the selection. According to Resende (2002), values of this order are adequate in the initial phase of breeding programs.

The crosses RB867515 x RB965518, MEX68-200 x F150, CoS245 x RB813804, MEX68-200 x RB93509, RB867515 x RB996961, and RB855156 x RB987935 had the highest values for BRIX and PC . This higher genotype means for soluble solids, and apparent sucrose contents were because these families resulted from crosses between elite clones and commercial cultivars of sugarcane (SC). An exception was the INT families of crosses involving the parents MEX68-200, CoS245, and F150, all of the third generation of S. spontaneum, i.e., very close to Saccharum spp, with higher sugar contents (Table 3).

Families* Traits**
Mother Father Type BRIX PC FIB TCH TSH TFH
RB855156(1) RB987935(1) SC 20.98 14.75 15.90 14° 98.20 13.65 15.73
RB867515(1) RB965518(1) SC 21.26 14.67 14.78 27° 78.71 23° 11.06 17° 11.61 24°
RB867515(1) RB996961(1) SC 21.06 14.72 15.89 15° 81.43 21° 11.47 15° 12.64 20°
RB966928(1) TUC77-42(1) SC 20.64 13.81 12° 16.10 10° 64.29 29° 8.97 28° 9.87 29°
SP80-3280(1) RB867515(1) SC 20.70 13.97 10° 15.24 19° 94.02 11° 12.90 14.48 14°
Co62175(1) 28NG289(3) EC 17.86 30° 10.64 28° 16.27 92.01 15° 10.53 21° 14.82 12°
IAC87-3396(1) US85-1008(4) EC 19.29 20° 12.38 19° 16.30 92.42 14° 11.61 13° 15.00
IM76-228(3) RB867515(1) EC 19.04 22° 10.64 28° 16.80 91.27 16° 10.51 22° 15.22
RB01640(1) IN84-58(2) EC 19.00 23° 11.33 26° 17.07 73.65 25° 9.24 27° 12.13 22°
RB036066(1) ? (2) EC 18.89 26° 11.37 25° 15.87 16° 115.13 13.21 18.62
RB04813(1) US85-1008(4) EC 18.92 24° 11.65 24° 15.96 12° 81.56 20° 10.16 25° 12.83 19°
RB83102(1) IM76-229(3) EC 19.57 18° 12.67 17° 16.00 11° 106.53 13.34 17.26
RB867515(1) B70710(4) EC 19.16 21° 11.76 23° 14.81 26° 99.04 12.21 11° 14.75 13°
RB92579(1) IM76-228(3) EC 18.36 29° 10.60 30° 16.44 99.39 11.20 16° 16.47
RB92579(1) IM76-229(3) EC 19.64 17° 12.43 18° 16.93 86.00 18° 11.00 18° 14.25 16°
RB93509(1) Co285(4) EC 19.94 14° 13.58 15° 15.18 20° 94.06 10° 12.34 10° 14.37 15°
SP81-3250(1) US85-1008(4) EC 19.33 19° 11.97 21° 16.41 68.60 28° 8.93 29° 10.75 27°
Co421(5) POJ2878(6) INT 18.76 28° 11.85 22° 16.18 54.83 30° 7.55 30° 8.17 30°
Co421(5) RB93509(1) INT 20.28 12° 14.03 14.72 29° 93.10 13° 12.50 13.88 18°
CoS245(6) RB813804(1) INT 21.15 14.56 15.09 22° 73.47 26° 10.35 24° 10.90 26°
Co617(5) POJ2878(6) INT 18.92 24° 12.02 20° 15.96 12° 97.56 11.98 12° 15.48
F150(6) IN84-88(2) INT 18.82 27° 10.85 27° 16.84 89.04 17° 10.41 23° 14.91 10°
F160(6) MEX68-200(6) INT 20.48 11° 13.87 11° 15.09 22° 105.09 13.78 15.83
MEX68-200(6) F150(6) INT 21.19 14.64 14.94 25° 82.35 19° 11.51 14° 12.28 21°
MEX68-200(6) RB040823(1) INT 19.83 15° 13.61 14° 14.50 30° 100.98 13.23 14.84 11°
MEX68-200(6) RB93509(1) INT 21.14 14.87 15.00 24° 75.37 24° 10.74 20° 11.18 25°
RB01623(1) MEX68-200(6) INT 19.82 16° 13.22 16° 15.59 17° 71.24 27° 9.66 26° 10.71 28°
RB93509(1) Co421(5) INT 20.59 10° 14.32 14.77 28° 94.02 11° 12.81 13.99 17°
RB93509(1) MEX68-200(6) INT 20.05 13° 13.78 13° 15.10 21° 99.06 13.10 14.97
US74-103(5) RB92579(1) INT 20.75 14.36 15.46 18° 78.95 22° 10.95 19° 12.10 23°

Table 3: Family parents, classification of crosses (type), genotypic means, and their respective ranking for the yield-related traits evaluated in 30 sugar- and energy cane families in Paranavaí, Paraná, Brazil.

For FIB, the crosses with highest values were RB01640 x IN84-58, RB92579 x IM76-229, F150 x IN84-88, IM76-228 x RB867515, RB92579 x IM76-228, and SP81-3250 x US85-1008, which are energy cane (EC) families of crosses with sugarcane hybrids and S. spontaneum (IN84-58 and IN84-88), S. robustum (IM76-229 and IM76-228), and the first generation of S. spontaneum (US85-1008) (Table 3).

The relationship between PC and FIB (Figure 1) shows a negative correlation between sugarcane (SC) and energy cane (EC) families, where crosses with sugarcane hybrids were concentrated in the first quadrant, showing a higher sucrose content at the expense of fiber content.


Figure 1: Scatter plot illustrating the correlation between the means of apparent sucrose percentage [PC (%)] and fiber content [FIB (%)] in an evaluation of 30 sugar- and energy cane families.

The S. spontaneum and S. robustum families were concentrated in the fourth quadrant, with higher fiber at the expense of sugar contents. This pattern demonstrates the importance of these species for fiber increment in breeding programs for energy cane. The exploitation of these parents has generated plants with higher fiber content than of other species of the genus Saccharum (Ming et al., 2006; Tew and Cobill, 2008). This has been the strategy to increase biomass in breeding programs in several countries, e.g., in Puerto Rico (Alexander, 1985), the United States (Giamalva et al., 1985; Eggleston et al., 2007), Barbados (Rao et al., 2007), and Mauritius (Ramdoyal and Badaloo, 2007). In Brazil, studies on energy cane are more recent (Matsuoka et al., 2014; Carvalho-Netto et al., 2014; Silveira et al., 2015a,b, 2016; Ramos et al., 2017; de Azeredo et al., 2017).

In the INT families, a different behavior was observed for the traits PC and FIB, with higher sucrose contents in some and higher fiber contents in others. The crosses Co617 x POJ2878 and Co421 x POJ2878, both parents of second and third generations of S. spontaneum, respectively, originated families with a stronger trend of fiber accumulation and a considerable decrease in sucrose content. For the crosses F160 x MEX68-200 and MEX68-200 x F150, both third-generation accessions of S. spontaneum, an opposite trend was observed, with higher sucrose accumulation and lower fiber contents (Figure 1).

For TCH, the best-performing families were RB036066 x ? (SC, 115.13 t/ha); RB83102 x IM76-229 (EC, 106.53 t/ha); F160 x MEX68-200 (INT, 105.09 t/ha); MEX68- 200 x RB040823 (INT, 100.98 t/ha); RB92579 x IM76-228 (EC, 99.39 t/ha); and RB93509 x MEX68-200 (INT, 99.06 t/ha) (Table 3). It is worth remembering that the parents RB040823, RB036066, RB93509, RB92579, and RB83102 are current sugarcane cultivars (except the parents of cross F160 x MEX68-200), which contributed to increase TCH in these families.

For TSH, the results are shown more clearly in the isoquant-type graph (Figure 2). The following families appear above the first isoline: F160 x MEX68-200 (INT, 13.78 t/ha), and RB855156 x RB987935 (SC, 13.65 t/ha). The cross F160 x MEX68-200, with parents of the third S. spontaneum generation, had a particularly interesting performance, with a considerable contribution to sucrose and stalk yield increase, generating progenies with higher TSH; the other crosses with the same parents did not have the same behavior pattern. The crosses between the first and second isolines were RB83102 x IM76-229 (EC), MEX68-200 x RB040823 (INT), RB036066 x ? (EC), RB93509 x Co421 (INT), Co421 x RB93509 (INT), and RB93509 x Co285 (INT), in descending order of TSH values (EC), RB93509 x MEX68- 200 (INT), and SP80-3280 x RB867515 (SC) (Table 3). The energy cane (EC) families had a high performance for TSH, improved by TCH, whereas PC was far below the mean; the other families had above-mean TCH and PC values.


Figure 2: Isoquant diagram of tons of sucrose per hectare (TSH) in the evaluation of 30 sugar- and energy cane families in Paranavaí - PR.

The performance of the families for TFH is also shown in isoquant diagrams (Figure 3). Cross RB036066 x ? (EC), of a half-sib with S. spontaneum accessions, appears above the first isoline. This is the most productive family (TFH = 18.62), with an average performance for FIB (15.87%), while the high fiber yield was averaged by TCH (115.13 t/ha). Between the first and second isoline are the crosses RB83102 x IM76-229 (EC) and RB92579 x IM76-228 (EC), both families with good performance in TCH and high FIB content; the parents of these families are high-yielding sugarcane hybrids and S. robustum accessions.


Figure 3: Isoquant diagram of tons of fiber per hectare (TFH) in the evaluation of 30 sugar- and energy cane families in Paranavaí - PR.


The families F160 x MEX68-200 and RB855156 x RB987935 had the highest sucrose yields per hectare. The family RB036066 x ? had the highest fiber yield per hectare since the cane yield (TCH) was the highest and the fiber content intermediate. The excellent performance of TFH was also observed in families derived from crosses of sugarcane cultivars with S. robustum accessions.

Heritability and accuracy were high for all evaluated traits, reflecting a considerable presence of the genetic component in trait expression and evidencing precision in the prediction of the genotypic means, indicating efficiency in the selection of sugar- and energy cane families for processing and yield-related traits.

Conflicts of interest

The authors declare no conflict of interest.


The authors are indebted to the Brazilian Federal Agency for Support and Evaluation of Graduate Education (CAPES), the Brazilian Council for Scientific and Technological Development (CNPq), the Foundation of the Federal University of Paraná (FUNPAR), and the Sugarcane Breeding Program of the Federal University of Paraná/Inter-University Network for the Development of Sugarcane Industry PMGCA/UFPR/RIDESA.

About the Authors

Corresponding Author

A.A.C. de Azeredo

Departamento de Fitotecnia e Fitossanitarismo, Universidade Federal do Paraná, Curitiba, PR, Brasil

[email protected]


  • Alexander AG (1985). The Energy Cane Alternative. Elsevier, Amsterdam.
  • de Azeredo AAC, Bhering LL, Brasileiro BP, Cruz CD, et al. (2017). Comparison between different selection indices in energy cane breeding. Genet. Mol. Res. 16: 1-12.
  • Balsalobre TWA, Mancini MC, Pereira GS, Anoni CO, et al. (2016). Mixed modeling of yield components and brown rust resistance in sugarcane families. Agron. J. 108: 1824-1837.
  • Barbosa MHP, Resende MDV, Bressiani JA, Silveira RCI, et al. (2005). Selection of sugarcane families and parents by REML/BLUP. Crop Breed. Appl. Biotechnol. 5: 443-450.
  • Barbosa MHP, Resende MDV, Dias LAS, et al. (2012). Genetic improvement of sugarcane for bioenergy: the Brazilian experience in network research with RIDESA. Crop Breed. Appl. Biotechnol. 12: 87-98. S1984-70332012000500010
  • Brasileiro BP, Mendes TOP, Peternelli LA, et al. (2016). Simulated Individual Best Linear Unbiased Prediction versus Mass Selection in Sugarcane Families. Crop Sci. 56: 570-575.
  • Carvalho-Netto OV, Bressian IJA, Soriano HL, et al. (2014). The potential of the energy cane as the main biomass crop for the cellulosic industry. Chem. Biol. Technol. Agric 1: 1-20.
  • Dal-Bianco M, Carneiro MS, Hotta CT, Chapola RG, et al. (2012). Sugarcane improvement: how far can we go? Curr. Opin. Biotechnol. 23: 265-270.
  • Eggleston G, Salassi M, Richard E, et al. (2007). Sustainability of the sugar industry: Future value addition from sugarcane. Int. Sugar J. 109: 415-432.
  • Giamalva M, Clark S and Stein J (1985). Conventional vs high fiber sugarcane. J. Am. Soc. Sugar Tech 4: 106-109.
  • Gomes FP (1990). Curso de estatística experimental. 13. ed. Ed. da USP, Piracicaba.
  • Jackson PA, Mcrae TA and Hogarth DM (1995). Selection of sugarcane families across variable environments. In. Sources of variation and optimal selection index. Field Crops Res. 43: 109-118.
  • Kang MS, Miller JD and Tai PYP (1983). Genetic and phenotypic path analysis and heritability in sugarcane. Crop Sci. 23: 643-647.
  • Kimbeng CA and Cox MC (2003). Early generation selection of sugarcane families and clones in Australia: a review. J. Am. Soc. Sugar Tech 23: 20-39.
  • Matsuoka S, Kennedy AJ, Santos EGD, et al. (2014). Energy Cane: Its Concept, Development, Characteristics, and Prospects. Adv. Bot. 1-13.
  • Melo LJOT, Oliveira FJ, Bastos GQ, Anunciação Filho CJ, et al. (2006). Interação genótipo x ciclos de colheita de cana-de-açúcar da Zona da Mata Norte de Pernambuco. Bragantia 65: 197-205.
  • Ming R, Moore PH, D’Hont A, Glaszmann JC, et al. (2006). Sugarcane Improvement through Breeding and Biotechnology. In: Plant breeding reviews (Janick J, ed.). John Wiley & Sons, New York.
  • Moraes MF, Bastos GQ, Filho CJA, et al. (2010). Avaliação agroindustrial e parâmetros genético de progênies de cana-de-açúcar em fase inicial na zona canavieira do litoral norte de Pernambuco. Cienc. Agrotec. 34: 1086-1092. https://doi. org/10.1590/S1413-70542010000500002
  • Oliveira RA, Daros E, Resende MDV, et al. (2011). Procedimento Blupis e seleção massal em cana-de-açúcar. Bragantia 796-800.
  • Ramdoyal K and Badaloo GH (2007). An evaluation of interspecific families of different nobilised groups in contrasting environments for breeding novel sugarcane clones for biomass. In: Proceedings of the International Society of Sugar Cane Technologists Conference, 26: 632-645.
  • Ramos RS, Brasileiro BP, Silveira LCI, et al. (2017). Selection of parents, families and clones to obtain energy cane. Agron. J. 109: 1-7.
  • Rao PS, Davis H and Simpson C (2007). New sugarcane cultivars and year round sugar and ethanol production with bagasse-based cogeneration in Barbados and Guiana. Proceedings of the 2007 Congress, Int. Soc. Sugar Cane Technol. 26: 1169-1176.
  • Resende MDV (2002). Genética biométrica e estatística no melhoramento de plantas perenes. Embrapa Informação Tecnológica, Brasília.
  • Resende MDV (2016). Software Selegen-REML/BLUP: a useful tool for plant breeding. Crop Breed. Appl. Biotechnol. 330-339.
  • Resende MDV and Barbosa MHP (2006). Selection via simulated Blup base on family genotypic effects in sugarcane. Pesqui. Agropecu. Bras. 41: 421-429.
  • Resende MDV and Duarte JB (2007). Precisão e controle de qualidade em experimentos de avaliação de cultivares. Pesqui. Agropecu. Trop. 37: 182-194.
  • Silva GC, Oliveira FJ, and Anunciação Filho CJ, Simões Neto DE, et al. (2011). Divergência genética entre genótipos de cana-de-açúcar. Ver. Bras. Ciênc. Agrá. 6: 52-58.
  • Silveira LCI, Brasileiro BP, Kist V, et al. (2015a). Genetic diversity and coefficient of kinship among potential genitors for obtaining cultivars of energy cane. Rev. Ciên. Agronôm. 46: 358-368.
  • Silveira LCI, Brasileiro BP, Kist V, et al. (2015b). Selection strategy in families of energy cane based on biomass production and quality traits. Euphytica 204: 443-455.
  • Silveira LCI, Brasileiro BP, Kist V, et al. (2016). Selection in energy cane families. Crop Breed. Appl. Biotechnol. 16: 298-
  • Simmonds NW (1996). Family selection in plant breeding. Euphytica 90: 201-208.
  • Stringer JK, Cox MC, Atkin FC, et al. (2011). Family selection improves the efficiency and effectiveness of selecting original seedlings and parents. Sugar Tech 13: 36-41.
  • Tew TL and Cobill RM (2008). Genetic Improvement of Sugarcane (Saccharum spp.) as an Energy Crop. In: Genetic Improvement of Bioenergy Crops (Vermerris W, ed.). Springer, New York.
  • Vichi FM and Mansor MTC (2009). Energia, meio ambiente e economia: o Brasil no contexto mundial. Quim. Nova 32: 757-767.
  • Wang L, Jackson PA, Lu X, et al. (2008). Evaluation of sugarcane x Saccharum spontaneum progeny for biomass composition and yield components. Crop Sci. 48: 951-996.
  • Zeni Neto H, Daros E, Bespalhok Filho JC, et al. (2013). Selection of families and parents of sugarcane (Saccharum spp.) through mixed models by joint analysis of two harvests. Euphytica 193: 391-408.

Full PDF