Skip to main content
NCBI home page
Wiley Open Access Collection logoLink to Wiley Open Access Collection
. 2021 Sep 12;139(2):136–144. doi: 10.1111/jbg.12647

Genetic parameters in traits of productive importance in lines of Bombyx mori L.

Giselle Zambrano‐Gonzalez 1,✉, Martha I Almanza‐Pinzon 2, Mauricio Vélez‐T 3
PMCID: PMC9293116  PMID: 34510553

Abstract

In the textile industry, complex cocoon traits are closely related to silk production. The aim of the present study was to estimate genetic parameters of economic importance traits—cocoon length (CL), cocoon weight (CW) and shell weight (SW)—in three B. mori lines—Chinese (C6), Japanese (J7) and Indian (C. Nichi)—reared under different temperature and photoperiod conditions. For each of these lines, data were collected from several generations with a full‐sibling family structure and variance‐covariance component were obtained via restricted maximum likelihood (REML) estimates based on a bi‐trait animal model analysed through the multiple‐trait derivative‐free restricted maximum likelihood (MTDFREML) software. Genetic parameters of the traits varied between the silkworm lines were evaluated. Heritabilities were highest in J7 line (0.71, 0.89 and 0.93 for CL, CW and SW, respectively) followed by C6 (0.48, 0.54 and 0.50 for CL, CW and SW, respectively) and C. Nichi (0.36, 0.43 and 0.40 for CL, CW and SW, respectively). Phenotypic correlations among these lines were positive, with values ranging between 0.36 and 0.767. Similarly, genetic correlations between the analysed silkworm lines were observed to be positive, with high values ranging from 0.86 to 0.94. The evidence for environmental correlation in these lines was found only between CW‐SW traits with moderate to high values ranging from 0.600 to 0.940. The magnitude of heritability and genetic correlations implies that phenotypic variations of the CL, CW and SW traits depend mainly on genotypic variation within the J7, C6 and C. Nichi lines, and that simultaneous genetic gains are possible by implementing selection processes for any of the evaluated traits.

Keywords: Bombyx mori, genetic parameters, productive traits

1. INTRODUCTION

The silkworm, Bombyx mori, is a domesticated insect native to Northern Asia that is fully adapted for commercial breeding. Its development and productivity depend on biotic factors such as competition, predation and pathogens and abiotic factors such as temperature and photoperiod (Kumar et al., 2003). The success of silkworm farming is important to the textile industry, which relies on the productive efficiency of quantitative and qualitative traits associated with cocoon production and the optimization of by‐products resulting from sericulture activity (Neshagaran et al., 2016).

B. mori has more than 3,000 improved lines and approximately 400 heritable mutants, for an estimated 4,310 geographic races, lines and mutants, which are distributed in different gene banks around the world (Doira et al., 1992; Goldsmith et al., 2005). The principles of silkworm breeding and the genetics of qualitative and quantitative traits have been previously documented by Singh et al. (2011). Traits contributing to silk performance are controlled by numerous genes influenced by environmental factors, making it difficult to judge whether the observed phenotypic variability is inherited or influenced by the environment (Reza & Rahman, 2005; Zhao et al., 2007). Genetic and environmental contribution to the phenotypic expression can be evaluated through quantitative genetic methods that generate useful information for genetic improvement programmes.

The genetic parameters of complex traits associated with silk production are essential for establishing effective genetic improvement programmes. Heritability, for instance, is a useful precision parameter for identifying the genetic potential of individuals from its phenotypic expression (Singh et al., 1994) and the magnitude of the selection response for a trait (Nyquist, 1991). Similarly, phenotypic and genetic correlations provide additional information on the degree of association between the observed and genetic values of two quantitative traits (Searle, 1961). Special attention is placed on genetic correlations because they make it possible to maintain the genetic gain within populations through the selection process with fewer traits, low heritability traits or even traits that are difficult to measure (Falconer, 1981). The heritability and correlations of quantitative traits have considerable impact on the observed genetic progress of any breeding program; hence, their knowledge is fundamental to the creation, evaluation, improvement or development of highly productive pure or hybrid breeds (Hemmatabadi et al., 2016).

Genetic studies conducted on B. mori silkworms have focussed mainly on silk production traits, such as cocoon weight, bark weight and bark percentage (Zamani et al., 2019). Based on these traits, breeders have selected parents within and between different silkworm populations and environments (Bharat & Shunmugan, 2014). This has resulted in geographically differentiated races with a particular source of genes useful in breeding programmes for conservation purposes or hybridization to identify genotypes with superior genetic performance (Jolly et al., 1989). The objective of the present study was to estimate genetic parameters (heritability and genetic, phenotypic and environmental correlations) of economic importance traits in three lines of silkworm reared under different temperature and photoperiod conditions.

2. MATERIALS AND METHODS

2.1. Silkworm lines

Three silkworm B. mori lines were used in the present study: Chinese 6 (C6), Japanese 7 (J7) and Indian (C. Nichi). These were chosen according to their productive performance and voltinism (number of generations per year). The C6 and J7 lines are bivoltine and were selected for their high yield in important productive characters, while C. Nichi line is polyvoltine and is characterized by its rapid growth rate and tolerance to tropical conditions (Rao et al., 2006). These silkworm genetic lines were imported from the Experimental Station of Sericulture and Agriculture (SAES) in Vratsa, Bulgaria (National Environmental Licensing Authority [ANLA] Resolution 00431 of March 2018), specifically from the Department of Genetics Research for B. mori improvement.

2.2. Rearing conditions

The experimental research was carried out at La Rejoya Plant Studies Center, attached to the Agrarian Sciences Faculty of the University of Cauca, located at Popayán in Northeast Colombia. The La Rejoya village is located in Cauca at 1,800 meters above sea level, has an average temperature of 18℃, and receives an average rainfall of 1,750 mm annually (Vivas & Morales, 2005). The experimental phase was conducted from July 2018 to April 2020. The lines were kept in optimal feeding and sanitary conditions in accordance with the protocols of Cifuentes and Sohn (1998) and Pescio et al. (2008). They were reared in incubators under controlled environmental conditions from egg stage to complete pupation stage, according to the modified protocols of Kumar et al. (2002) and Lakshminarayana et al. (2002), and during the number of generations required to estimate the lines voltinism—two generations for J7 and three for C6 and C. Nichi. The incubators used for silkworm rearing were locally designed according to the technical characteristics described in Duque‐T et al. (2018) and were equipped with instruments to control and monitor temperature, humidity, light, air speed, and CO2 concentration.

The data used to estimate silkworm genetic parameters are part of a research project dedicated to analysing the effects of variables such as temperature and photoperiod conditions on the changes in voltinism recorded for the evaluated lines (Figure 1). The effects of these variables, as environmental factors, were chosen since they are recognized for influencing different development stages of B. mori and their voltinism expression (Kamili & Masoodi, 2004; Takamiya, 1974). Similarly, the evaluated levels of each environmental variable were chosen considering the maximum and minimum values reported to influence the silkworms' behaviour (Rahmathulla, 2012; Vermana et al., 2003). Other environmental factors, such as relative humidity (75 ± 5%), feeding (fresh mulberry), CO2 concentration (<2%) and air speed (0.5–1 m/s), remained constant at levels considered optimal for B. mori rearing (Rahmathulla, 2012).

FIGURE 1.

FIGURE 1

Open in a new tab

Rearing experimental conditions of the evaluated silkworm lines per generation

2.3. Experimental design

The experimental rearing conditions are depicted in Figure 1. Briefly, three temperatures (24 ± 1℃, 26 ± 1℃ and 28 ± 1℃) and photoperiod conditions (8–16, 12–12 and 16–8 of photophase or scotophase, respectively) were evaluated per generation (two generations for J7 and three for C6 and C. Nichi) and sex. The measurement of productive important traits, such as cocoon length (CL), cocoon weight (CW) and shell weight (SW), were recorded for each individual (Seidavi, 2010). In total, nine treatments (factorial combination of temperature * photoperiod) with three repetitions were evaluated per generation. On each repetition, a group of approximately 100 individuals was observed, and seven to ten females and males were randomly taken for phenotypic measurements. Within each group, next generation parents were also randomly selected and mated. No selection process for the evaluated traits was exercised on the individuals chosen as parents of each generation. A total of 3,566 individuals were used, divided into 163 full‐sibling families—61, 32 and 70 for C6, J7 and C. Nichi, respectively. The lengths and weights were measured individually in millimetres and grams, respectively. The shell weight was measured after removing the pupa, and this process was repeated throughout the different generations.

2.4. Genetic analysis

Heritability and genetic, phenotypic and environmental correlations were estimated for CL, CW and SW variables in C6, J7 and C. Nichi lines. The variance‐covariance components were obtained by the restricted maximum likelihood (REML) based on information of full‐sibling family structure. A bi‐trait animal model was used through the multiple‐trait derivative‐free restricted maximum likelihood (MTDFREML) software (Boldman et al., 1995). The evaluated models took into consideration the fixed effects of temperature, photoperiod, generations and sex. Meanwhile, the random effects were the direct additive‐genetic component and error term. The relationship matrix included 1,337, 775 and 1,355 animals in C6, J7 and C. Nichi lines, respectively. The convergence criterion for variance‐covariance estimation was 10–8, with a maximum of 500 iterations.

3. RESULTS AND DISCUSSION

Table 1 presents the descriptive statistics of the evaluated traits on each line, obtained through the combination of fixed effects. In general, the highest average values of CL, CW and SW productive traits were found in line J7, while C6 and C. Nichi lines behaved similarly. The CL values ranged between 28.34–35.24 mm, the CW values ranged between 1.14–1.34 g, and the SW values ranged between 0.18–0.27 g. The CW and SW values obtained here are low compared to those obtained by Kumar and Kumar (2011) (1.476–1.890 g for CW and 0.241–0.351 g for SW). According to coefficient of variation among lines, CL was the trait with the least variation (7.42%–8.7%), while CW and SW presented the greatest values (20.95–25.17 and 25.05%–32.8%, respectively). The variability observed between lines and traits could be a direct reflection of environmental rearing conditions. It should be noted that highest coefficients of variation was found in the C6 line, which is in line with Kinoshita et al. (1982), who claimed that Chinese lines show greater susceptibility to environmental changes.

TABLE 1.

Descriptive statistics of the general performance of each line through the combination of fixed effects

Line Trait Mean SE CV (%)

C6

(n = 1,220)

 CL (mm) 28.98 2.52 8.70
CW (g) 1.24 0.31 25.17
SW (g) 0.23 0.07 32.80

J7

(n = 711)

 CL (mm) 35.24 2.75 7.80
CW (g) 1.34 0.31 23.41
SW (g) 0.27 0.07 25.43

C. Nichi

(n = 1,259)

 CL (mm) 28.34 2.10 7.42
CW (g) 1.14 0.24 20.95
SW (g) 0.18 0.04 25.05
Open in a new tab

Abbreviations: CL, Cocoon length; CV, coefficient of variation; CW, cocoon weight; SE, standard error; SW, shell weight.

Table 2 shows the variance–covariance components and estimated heritability for the three evaluated traits. Phenotypic variance was highest in the CL trait (7.530, 5.072 and 3.525 for J7, C6 y C. Nichi, respectively), while the CW and SW traits ranged between 0.001 and 0.088 among the lines. The greater phenotypic variance observed in the CL character suggests that deeper phenotypic plasticity exists among individuals within each family group (Geber & Griffen, 2003).

TABLE 2.

Variance–covariance components and heritability values of economic important traits in C6, J7 and C. Nichi silkworm lines

Line Trait Additive Phenotypic Environmental h 2 (SE)
CL CW SW CL CW SW CL CW SW
C6 CL 2.411 0.254 0.069 5.072 0.254 0.069 2.661 0.000 0.000 0.48 ± 0.033
CW 0.254 0.035 0.008 0.254 0.066 0.128 0.000 0.031 0.005 0.54 ± 0.030
SW 0.069 0.008 0.002 0.069 0.128 0.004 0.000 0.005 0.002 0.50 ± 0.031
J7 CL 5.346 0.561 0.133 7.530 0.561 0.133 2.184 0.000 0.000 0.71 ± 0.055
CW 0.561 0.078 0.016 0.561 0.088 0.015 0.000 0.010 −0.001 0.89 ± 0.082
SW 0.133 0.016 0.004 0.133 0.015 0.005 0.000 −0.001 0.001 0.93 ± 0.081
C. Nichi CL 1.269 0.125 0.026 3.525 0.125 0.026 2.255 0.000 0.000 0.36 ± 0.035
CW 0.125 0.014 0.002 0.125 0.034 0.005 0.000 0.019 0.003 0.43 ± 0.032
SW 0.026 0.002 0.001 0.026 0.005 0.001 0.000 0.003 0.001 0.40 ± 0.033
Open in a new tab

Abbreviations: CL, Cocoon length; CW, cocoon weight; SE, standard error; SW, shell weight.

Additive variance was highest in the CL trait with values of 5.346, 2.411 and 1.269 for J7, C6 and C. Nichi, respectively, meanwhile the lowest values were observed in SW (0.001–0.004). Low additive‐genetic variance is expected in traits exposed to a strong directional selection and are closely related to biological adequacy, where alleles have been fixed over time within the populations. In contrast, traits exposed to a weak selection process tend to present high levels of additive‐genetic variation (Teplitsky et al., 2009). It is possible that the SW trait is less variable because it has been a manipulated character for centuries due to its economic importance (Trochez‐Solarte et al., 2019).

Environmental variance ranged from 0.001 to 2.661 among the lines, with the highest values associated with the CL trait. Environmental variance is part of the phenotypic variance and reflects the phenotypic differences of individuals managed under similar environments, where the differences occur due to small variations found within that environment (Falconer, 1981; Molina, 1992; Schou et al., 2020). In general, environmental variance in the present study was low among the traits and lines, indicating that the environmental conditions associated with the treatments—temperature and photoperiod—were handled correctly during the experimental period.

Heritability varied between silkworm lines (Table 2); the highest values were obtained in J7 line (0.71, 0.89 and 0.93 for CL, CW and SW, respectively) followed by C6 (0.48, 0.54 and 0.50 for CL, CW and SW, respectively) and C. Nichi (0.36, 0.43 and 0.40 for CL, CW and SW, respectively). The CW heritability obtained between lines (0.89, 0.54 and 0.43 for J7, C6 and C. Nichi, respectively) are within the 0.21–0.97 range reported for races of Chinese, Indian, and Iranian origin (Hassan et al., 2011; Kumaresan et al., 2007; Seidavi et al., 2008; Talebi et al., 2001). The estimated heritability of SW trait (0.93, 0.50 and 0.40 for J7, C6 and C. Nichi, respectively) also agreed with the 0.35–0.80 values reported in other studies (Bashir et al., 2015; Govindan et al., 1991; Seidavi, 2010; Singh et al., 2011). The heritability values associated with the CL trait were 0.71 for J7, 0.48 for C6 and 0.36 for C. Nichi. Reports of CL heritability are scarce in literature, possibly because silkworm studies on genetic parameters focus mainly on other traits that are easy to measure and also fundamental for sericulture economy (Ghanipoor et al., 2007). According to the scale proposed by Bavera (2000), the estimated heritability in the present study was high, suggesting that phenotypic variations of traits depend mainly on genetic variation with scarce influence from the environment (Ramírez et al., 2020). These results indicate that CL, CW and SW traits can be improved through selection processes within the evaluated populations (Quijano & Echeverri, 2015; Sabhat et al., 2009). Some studies indicate that high heritability in economic importance traits can be commonly found in domesticated varieties of B. mori (Kumaresan et al., 2000; Mirhosseini et al., 2005; Mu et al., 1995), especially those populations that have been subjected to the effects of genetic improvement programmes (Maqbool et al., 2005; Petkov & Nguyenvan, 1987).

The wide range of estimated heritability values is due to the fact that this parameter is particular to each trait and specific to each population (Nyquist, 1991). Based on the observations recorded under the particular rearing conditions of the present study, the contribution of genetic and environmental components to the phenotypic expression of a trait (CL, CW or SW) varies between the lines. The highest heritability values were found in the J7 line, indicating that CL, CW and SW can be rapidly improved in genetic terms through selection processes. However, a slower response is expected in the C6 and C. Nichi lines. The differences between the Japanese, Chinese and tropical lines may be the result of reproductive isolation and significant genetic differentiation among lines, especially the Japanese breed (Yukuhiro et al., 2011).

Phenotypic, genetic and environmental covariance are also reported in Table 2. Phenotypic covariance among lines was highest for CL‐CW traits, with values ranging between 0.125 and 0.561. Meanwhile the lowest values were found in SW‐CL traits (0.069) in C6 line, and CW‐SW traits (0.005–0.015) for J7 and C. Nichi lines. Phenotypic covariance is further divided into genetic and environmental covariance. The former represents the part of phenotypic covariance attributed to common genetic factors, while the latter corresponds to the phenotypic covariance due to common environmental factors (Gao et al., 2021). The results showed that genetic covariance presented a similar tendency between lines, with greater values between CL‐CW, followed by SW‐CL and CW‐SW traits. Environmental covariance was found in CW‐SW traits, with values ranging from −0.001 to 0.005. Meanwhile, in CL‐CW and SW‐CL traits, a zero value was observed, indicating that the contribution of common environmental factors to the phenotypic covariance was negligible in these cases.

Phenotypic, genetic and environmental correlations are shown in Table 3. Between lines and traits, the phenotypic correlations were lower than genetic correlations, suggesting that the phenotypic expression of CL, CW, and SW traits is likely to be determined by genotype × environment interaction (G × E) (Irvine‐Lopez et al., 2020; Rahman, 1984).

TABLE 3.

Phenotypic (rp ), genetic (rg ) and environmental correlation (re ) among the evaluated productive traits

Line Parameter CL ‐ CW CW ‐ SW SW ‐ CL
C6 rp 0.438 0.767 0.457
rg 0.860 0.940 0.890
re 0.000 0.600 0.000
J7 rp 0.695 0.736 0.721
rg 0.890 0.860 0.900
re 0.000 0.940 0.000
C. Nichi rp 0.360 0.759 0.366
rg 0.890 0.880 0.900
re 0.000 0.690 0.000
Open in a new tab

Abbreviations: CL, Cocoon length; CW, cocoon weight; SW, shell weight.

Phenotypic associations between traits and lines are shown in Figure 2. Linear tendencies were observed corresponding to positive phenotypic correlations in all cases. CW‐SW correlation was similar among the lines, with values ranging between 0.736 and 0.767. CL‐CW and SW‐CL correlations were highest for J7 line (0.695 and 0.721, respectively), followed by C6 (0.438 and 0.457, respectively) and C. Nichi (0.36 and 0.366, respectively). These positive phenotypic associations are expected since SW is part of CW, and the latter was greater when CL increased. Kumar et al. (1995) and Grekov (1989) also identified significant and positive phenotypic correlation between CL, CW and SW traits (0.55–0.659).

FIGURE 2.

FIGURE 2

Open in a new tab

Phenotypic (a, c, e) and additive genetic values (b, d, f) relationships between CW, CL and SW traits obtained with the evaluated silkworm lines

The genetic correlations of CL‐CW, CW‐SW and SW‐CL presented positive and high values between the analysed silkworm lines (0.86–0.94). These values are within the 0.709–0.989 range presented by Nagaraja et al. (1996) and Mirhosseini et al. (2007), Mirhosseini et al. (2002). These results suggest that the observed correlated response among traits are determined by the same or linked genes (Molina, 1992). The positive and high genetic correlations between CL, CW and SW traits indicate that selecting one of them would lead to the improvement of the others, resulting in simultaneous genetic progress (Seidavi, 2010). The genetic correlation results are illustrated in Figure 2, where the additive‐genetic value relationship among the traits and lines are plotted. An evident linear and positive association is depicted in all cases. CW and SW are important traits in the sericulture chain for silkworm breeders and researchers, as well as those involved in the silk thread industry. According to the genetic parameters estimated in this research, any of these two traits are potential candidates for the establishment of selection processes in breeding programmes within the J7, C6 and C. Nichi lines.

The environmental correlation for CW‐SW traits was positive, with moderate to high values between the lines (0.600–0.940), suggesting that the evaluated rearing environmental conditions influenced both traits in a similar manner. These values are higher to the average 0.666 environmental correlation obtained in pure lines (Seidavi, 2010). On the other hand, environmental correlations between CL‐CW and SW‐CL were zero, as expected, since their environmental covariance was also zero. Such null environmental correlations suggest that factors like those evaluated in the present study—temperature, photoperiod and other breeding conditions—do not contribute to the possible causal relationship between CL‐CW and SW‐CL traits (Gao et al., 2021).

The implementation of genetic improvement strategies is successful only when the inheritance patterns of economic importance traits and genotype × environment interactions are clearly understood (Murthy & Subramanya, 2007). The estimations of genetic parameters in silkworm farming are critical for understanding phenotypic changes in the population as a response to domestication, which would enable the improvement of economically valuable traits useful for increasing the profits of the sericulture industry (Darmand et al., 2011; Hemmatabadi et al., 2016). With regard to the J7, C6 and C. Nichi silkworm lines, selection is one of the best approaches that can be applied in their genetic improvement programmes, and in particular, individual selection of parental lines could provide better results (Hemmatabadi et al., 2016).

4. CONCLUSIONS

The genetic parameters of CL, CW and SW traits showed differences within the J7, C6, and C. Nichi silkworm lines. However, both heritability and genetic correlations were high in all cases, indicating the possibility of obtaining genetic gains in economic importance traits through the implementation of selection processes for any of the evaluated traits within the genetic improvement programmes for the silkworm lines that were evaluated.

CONFLICT OF INTERESTS

Authors declare no Conflict of Interests for this article.

AUTHOR CONTRIBUTIONS

Giselle Zambrano‐Gonzalez: conceptualization, formal analysis, data collection, preparation of the original draft, methodology, writing, revision and editing. Martha I. Almanza‐Pinzon: formal analysis, methodology, writing and revision. Mauricio Velez‐T: methodology, statistical analysis, writing and review.

ACKNOWLEDGEMENTS

The authors wish to thank the University of Cauca and the following research groups: The Geology, Ecology and Conservation research group (GECO), and the Integrated Production Systems Research Group (SISINPRO). Also, to the projects InnovAccion‐Cauca and Technical Development for Organic and Innovative Silk Products Project, from the General Royalties System, and the Government of Cauca. We are especially grateful to Colin McLachlan for suggestions relating to the English text.

Zambrano‐Gonzalez, G. , Almanza‐Pinzon, M. I. , & Vélez‐T, M. (2022). Genetic parameters in traits of productive importance in lines of Bombyx mori L.. Journal of Animal Breeding and Genetics, 139, 136–144. 10.1111/jbg.12647

Contributor Information

Giselle Zambrano‐Gonzalez, Email: gzambranog@unicauca.edu.co.

Martha I. Almanza‐Pinzon, Email: malmanza@unicauca.edu.co.

Mauricio Vélez‐T, Email: ovelez@unal.edu.co.

REFERENCES

  1. Bashir, M. , Kamili, A. S. , Ashraf, B. M. , & Mir, S. A. (2015). Estimates of genetic traits in silkworm (Bombyx mori L.) under temperate conditions of Kashmir. Applied Biological Research, 17, 250–258. [Google Scholar]
  2. Bavera, G. A. (2000). Selección. Cursos de Producción Bovina de Carne, FAV UNRC. http://www.produccion‐animal.com.ar [Google Scholar]
  3. Bharat, B. B. , & Shunmugan, M. M. (2014). Genetic divergence, implication of diversity, and conservation of silkworm, Bombyx mori . Review. International Journal of Biodiversity, 2014, 15–22. [Google Scholar]
  4. Boldman, K. G. , Kriese, L. A. , Van Vleck, L. D. , Van Tassell, C. P. , & Kachman, S. D. (1995). A manual for use of MTDFREML: A set of programs to obtain estimates of variances and covariances [Draft]. ARS, USDA. [Google Scholar]
  5. Cifuentes, C. A. , & Sohn, K. W. (1998). Manual técnico de sericultura: Cultivo de la morera y cría del gusano de seda en el trópico. Convenio SENA‐CDTS. [Google Scholar]
  6. Darmand, S. , Lavvaf, A. , Seidavi, A. R. , Ella, N. , Nematollahian, S. , & Farahvash, T. (2011). Estimation of genetic parameters in three commercial silkworm lines of Iran. African Journal of Biotechnology, 10, 13324–13330. [Google Scholar]
  7. Doira, H. , Fujii, H. , Kawaguchi, Y. , Kihara, H. , & Banno, Y. (1992). Genetic stock and mutation of Bombyx mori . Institute of Genetic Resources, Kyushu University. [Google Scholar]
  8. Duque‐Torres, A. , Rodriguez‐Pabon, C. , Ruiz‐Rosero, J. , Zambrano‐Gonzalez, G. , Almanza‐Pinzon, M. , Caicedo Rendon, O. M. , & Ramirez‐Gonzalez, G. (2018). A new environmental monitoring system for silkworm incubators. F1000Research, 7, 1–18. 10.12688/f1000research.13633.1 [DOI] [Google Scholar]
  9. Falconer, D. (1981). Introduction to quantitative genetics. Longman & Co. [Google Scholar]
  10. Gao, B. , Yang, C. , Liu, J. , & Zhou, X. (2021). Accurate genetic and environmental covariance estimation with composite likelihood in genome‐wide association studies. PLoS Genetics, 17, e1009293. 10.1371/journal.pgen.1009293 [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Geber, M. , & Griffen, L. (2003). Inheritance and natural selection on functional traits. International Journal of Plant Sciences, 164, 21–42. 10.1086/368233 [DOI] [Google Scholar]
  12. Ghanipoor, M. , Shadparvar, A. A. , Mirhosseini, S. Z. , & Seidavi, A. R. (2007). Estimation of economic values of productive and reproductive traits for three Iranian commercial silkworm lines in minimum cost interest. Journal of Agricultural Science, 1, 45–57. [Google Scholar]
  13. Goldsmith, M. R. , Shimada, T. , & Abe, H. (2005). The genetics and genomics of the silkworm, Bombyx mori L. Annual Review of Entomology, 50, 71–100. [DOI] [PubMed] [Google Scholar]
  14. Govindan, R. S. , Satanahali, B. , Goad, I. V. , Guraraja, M. V. , & Magadam, S. B. (1991). Graphic analysis of gene action for some larval and cocoon traits in silkworm. Mysore Agriculture Science, 24, 474–481. [Google Scholar]
  15. Grekov, D. (1989). Selection‐genetic evaluation of some white cocoon races of the silkworm (Bombyx mori L.). Heritability and genetic correlations of qualitative traits. Zhivotnov'dni Nauki, 26, 70–73. [Google Scholar]
  16. Hassan, A. , Rahman, S. M. , & Ahsan, K. (2011). Genetic variability, correlation, path analysis and construction of selection index in mulberry silkworm, Bombyx mori L. I. Genetic variability. University Journal of Zoology, 30, 33–36. [Google Scholar]
  17. Hemmatabadi, R. N. , Seidavi, A. , & Gharahveysi, S. (2016). A review on correlation heritability and selection in silkworm breeding. Journal of Applied Animal Research, 44, 9–23. 10.1080/09712119.2014.987289 [DOI] [Google Scholar]
  18. Irvine‐Lopez, B. , Santiago, K. G. , Seo, K. , Jeong, T. , Jong‐Eun, P. , Han‐Ha, C. , Park, W. , & Lim, D. (2020). Genetic parameters of birth weight and weaning weight and their relationship with gestation length and age at first calving in Hanwoo (Bos taurus coreanae). Animals, 10, 1083–1092. 10.3390/ani10061083 [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Jolly, M. S. , Datta, R. K. , Noamani, M. K. R. , Iyengar, M. N. S. , Nagaraj, C. S. , Basavaraj, H. K. , Kshamarani, G. , & Rao, P. R. (1989). Studies on the genetic divergence in mulberry silkworm Bombyx mori L. Sericologia, 29, 545–559. [Google Scholar]
  20. Kamili, S. , & Masoodi, M. A. (2004). Principles of temperate sericulture. Kalyani. [Google Scholar]
  21. Kinoshita, D. , Takamiya, K. , & Kato, M. (1982). Effects of food and environmental conditions on the voltinism of silkworm, Bombyx mori . The Journal of Sericultural Science of Japan, 51, 106–110. [Google Scholar]
  22. Kumar, J. S. , & Kumar, N. S. (2011). Production efficiency of cocoon shell of silkworm, Bombyx mori L. (Bombycidae: Lepidoptera), as an index for evaluating the nutritive value of mulberry, Morus sp. (Moraceae), varieties. Psyche, 2011, 1–3. [Google Scholar]
  23. Kumar, N. S. , Basavaraja, H. K. , Kumar, C. M. , Reddy, N. M. , & Datta, R. K. (2002). On the breeding of “CSR18 x CSR19”‐ A robust bivoltine hybrid of silkworm, Bombyx mori L. for the tropics. International Journal of Industrial Entomology, 5, 155–162. [Google Scholar]
  24. Kumar, N. S. , Basavaraja, H. K. , Reddy, N. M. , & Dandin, S. B. (2003). Effect of high temperature and high humidity on the quantitative traits of parents, foundation crosses, single and double hybrids of bivoltine silkworm, Bombyx mori L. International Journal of Industrial Entomology, 6, 197–202. [Google Scholar]
  25. Kumar, P. , Bhutia, R. , & Ahsan, M. M. (1995). Estimates of genetic variability for commercial quantitative traits and selection indices in bivoltine races of mulberry silkworm, Bombyx mori L. Indian Journal of Genetic and Plant Breed, 55, 109–116. [Google Scholar]
  26. Kumaresan, P. , Sinha, R. K. , & Rajeurs, S. (2007). An analysis of genetic variation and divergence in Indian tropical polyvoltine silkworm (Bombyx mori L) genotypes. Caspian Journal of Environmental Sciences, 5, 11–18. [Google Scholar]
  27. Kumaresan, P. , Sinha, R. K. , & Sekar, S. (2000). Genetic variability and selection indices for economic quantitative traits of multivoltine mulberry silkworm, Bombyx mori L. genotypes. Sericologia, 40, 595–605. [Google Scholar]
  28. Lakshminarayana, R. P. , Naik, S. S. , & Reddy, N. S. (2002). Implications of temperature and humidity on population patterns in the silkworm, Bombyx mori L. International Journal of Industrial Entomology, 5, 67–71. [Google Scholar]
  29. Maqbool, A. , Malik, G. N. , Dar, H. U. , Afifa, S. , Kamili, S. , & Zaffar, G. (2005). Genetic analysis of 12 quantitative characters in somebivoltine silkworm (Bombyx mori L.) genotypes. Indian Journal of Sericulture, 44, 156–158. [Google Scholar]
  30. Mirhosseini, S. Z. , Ghanipoor, M. , Gholami, M. R. , & Shadparvar, A. (2002). Estimation of genetic parameters for cocoon traits in six Iranian commercial lines. In Proceedings of the 15th Iranian plant protection congress. Razi University of Tabriz. [Google Scholar]
  31. Mirhosseini, S. Z. , Ghanipoor, M. , Seidavi, A. , Shadparvar, A. , & Bizhannia, A. (2007). Heritabitity and genetical, environmental and phenotypic correlations of cocoon traits in Japanese lines of silkworm Bombyx mori L. In Proceedings of the International congress of insect biotechnology and industry, Degu. [Google Scholar]
  32. Mirhosseini, S. Z. , Ghanipoor, M. , Shadparvar, A. , & Etebari, K. (2005). Selection indices for cocoon traits in six commercial silkworm (Bombyx mori) lines. Philippine Agricultural Scientist, 88, 328–336. [Google Scholar]
  33. Molina, G. J. D. (1992). Introducción a la Genética de Poblaciones y Cuantitativa. AGT Editor. [Google Scholar]
  34. Mu, Z. M. , Liu, Q. X. , Liu, X. L. , Li, W. G. , & Sun, Z. Y. (1995). Genetic research of vitality and cocoon quality traits of silkworm. Journal Shandong Agricultural University, 26, 157–163. [Google Scholar]
  35. Murthy, N. , & Subramanya, G. (2007). Heritability and genetic variation of few quantitative traits in the silkworm, Bombyx mori . Indian Journal of Sericulture, 46, 103–105. [Google Scholar]
  36. Nagaraja, M. R. , Govindan, R. , & Narayanaswamy, T. K. (1996). Estimation of combining ability in Eri silkworm Samia Cynthia ricini Boisduval for pupal allied traits. Mysore Journal of Agricultural Science, 30, 48–51. [Google Scholar]
  37. Neshagaran, H. R. , Seidavi, A. R. , & Gharahveysi, S. (2016). A review on correlation, heritability and selection in silkworm breeding. Journal of Applied Animal Research, 44, 9–23. 10.1080/09712119.2014.987289 [DOI] [Google Scholar]
  38. Nyquist, W. E. , & Baker, R. J. (1991). Estimation of heritability and prediction of selection response in plant populations. Critical Reviews in Plant Science, 10, 235–322. 10.1080/07352689109382313 [DOI] [Google Scholar]
  39. Pescio, F. , Zunini, H. , Basso, C. , & Divo, S. M. (2008). Sericultura. Manual para la producción. Editorial INTI. [Google Scholar]
  40. Petkov, N. , & Nguyenvan, L. (1987). Breeding genetic studies on some lines of the silkworm, Bombyx mori L. Genetika‐iSelektsiya, 20, 384–394. [Google Scholar]
  41. Quijano, J. , & Echeverri, J. (2015). Genética cuantitativa aplicada al mejoramiento animal (1st ed.). Universidad Nacional de Colombia. [Google Scholar]
  42. Rahman, S. M. (1984). Studies on the genetic improvement of eri silkworm, Philosamia ricini Boisd of Bangladesh [dissertation]. Rajshahi University, Bangladesh. [Google Scholar]
  43. Rahmathulla, V. K. (2012). Management of climatic factors for successful silkworm (Bombyx mori L.) crop and higher silk production: A review. Psyche, 2, 1–12. [Google Scholar]
  44. Ramírez, E. J. , Burgos, W. O. , Elzo, M. A. , Martínez, R. A. , & Cerón‐Muñoz, M. F. (2020). Genetic parameters and trends for growth traits in Blanco Orejinegro cattle. Translational Animal Science, 4, 1–9. 10.1093/tas/txaa174 [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Rao, C. G. P. , Seshagiri, S. V. , & Ramesh, C. (2006). Evaluation of genetic potential of the polyvoltine silkworm (Bombyx mori L.) germplasm and identification of parents for breeding programme. Journal of Zhejiang University Science B, 7, 215–220. [DOI] [PMC free article] [PubMed] [Google Scholar]
  46. Reza, A. M. S. , & Rahman, S. M. (2005). Genetic parameters of some yield and yield contributing traits in silkworm, Bombyx mori L. University Journal of Zoology, 24, 55–58. [Google Scholar]
  47. Sabhat, A. , Farooq, M. , Sofi, A. M. , & Malik, M. A. (2009). Heritability, genetic advance and correlation analysis of some reproductive traits in silkworm, Bombyx mori L. Journal of Experimental Zoology, 12, 307–310. [Google Scholar]
  48. Schou, M. F. , Kristensen, N. T. , & Hoffmann, A. A. (2020). Patterns of environmental variance across environments and traits in domestic cattle. Evolutionary Applications, 13, 1090–1102. 10.1111/eva.12924 [DOI] [PMC free article] [PubMed] [Google Scholar]
  49. Searle, S. R. (1961). Phenotypic, genetic and environmental correlations. Biometrics, 17, 474–480. 10.2307/2527838 [DOI] [Google Scholar]
  50. Seidavi, A. (2010). Estimation of genetic parameters and selection effect on genetic and phenotype trends in silkworm commercial pure lines. Asian Journal of Animal and Veterinary Advances, 5, 1–12. [Google Scholar]
  51. Seidavi, A. R. , Bizhannia, A. , Ghanipoor, M. , & Qotbi, A. (2008). Investigation on improvement possibility of resistance, production and reproduction traits in 3P, 2P, and P generations in three Japanese pure lines of silkworm Bombyx mori L. using individual selection in P3 generation. Asian Journal of Animal and Veterinary Advances, 3, 443–447. [Google Scholar]
  52. Singh, T. , Bhat, M. M. , & Khan, M. A. (2011). Critical analysis of correlation and heritability phenomenon in the silkworm, Bombyx mori (Lepidoptera: Bombycidae). Advances in Bioscience and Biotechnology, 2, 347–353. 10.4236/abb.2011.25051 [DOI] [Google Scholar]
  53. Singh, T. , Chandrashekharaiah, A. , & Samson, M. V. (1994). Selection strategies in relation to correlation and heritability in the silkworm, Bombyx mori (L). Bulletin of Sericultural Research, 5, 37–41. [Google Scholar]
  54. Takamiya, K. (1974). Studies on temperature and photoperiodic conditions on the larval growth of the silkworm, Bombyx mori, fed on artificial diet. II. Effects of temperature and photoperiod throughout the larval stages on the moltinism and voltinism. Journal of Sericultural Science of Japan, 43, 35–40. [Google Scholar]
  55. Talebi, E. , Edris, M. A. , & Ebadi, V. R. (2001). Genetic specifications estimation of silkworms several important characters. Journal of Science and Technology of Agriculture and Natural Resources, 5, 199–204. [Google Scholar]
  56. Teplitsky, C. , Mills, J. A. , Yarrall, J. W. , & Merila, J. (2009). Heritability of fitness components in a wild bird population. Evolution, 63, 716–726. 10.1111/j.1558-5646.2008.00581.x [DOI] [PubMed] [Google Scholar]
  57. Trochez‐Solarte, J. D. , Ruiz‐Erazo, X. , Almanza‐Pinzon, M. , & Zambrano‐Gonzalez, G. (2019). Role of microsatellites in genetic analysis of Bombyx mori silkworm: A review. F1000Research, 8, 1424. 10.12688/f1000research.20052.1 [DOI] [PMC free article] [PubMed] [Google Scholar]
  58. Vermana, G. , Venkatachalapathy, M. , & Kamble, C. K. (2003). Temperature induced sterility in silkworm, Bombyx mori L. In Proceedings of the national seminar on silkworm seed production, Kodathi, Bangalore. [Google Scholar]
  59. Vivas, N. , & Morales, S. (2005). Evaluación agronómica y producción de grano de diez accesiones de guandul (Cajanus cajan) en la meseta de Popayán – Cauca. Bioecnología En El Sector Agropecuario Y Agroindustrial, 3, 36–40. [Google Scholar]
  60. Yukuhiro, K. , Sezutsu, H. , Tamura, T. , Kosegawa, E. , & Kiuchi, M. (2011). Nucleotide sequence variation in mitochondrial COI gene among 147 silkworm (Bombyx mori) strains from Japanese, Chinese, European and moltinism classes. Genes y Genetic Systems, 86, 315–323. 10.1266/ggs.86.315 [DOI] [PubMed] [Google Scholar]
  61. Zamani, P. , Ghanipoor, M. , Mirhosseini, S. Z. , Abdolo, R. , & Seidavi, A. (2019). Comparison of different selection strategies for mulberry silkworm, Bombyx mori . International Journal Tropical Insect Science, 39, 139–145. 10.1007/s42690-019-00015-8 [DOI] [Google Scholar]
  62. Zhao, Y. , Chen, K. , & He, S. (2007). Key principles for breeding spring and autumn using silkworm varieties: From our experience of breeding 873x874. Caspian Journal of Environmental Sciences, 5, 57–61. [Google Scholar]

Articles from Journal of Animal Breeding and Genetics are provided here courtesy of Wiley

RESOURCES