Genotype x environment interactions occur when two or more genotypes are compared across different environments and their relative performance (responses to the environment) is different. Due to effect of this interaction, the association between phenotype and genotype is reduced. This raises the important issue of adaptation because a breeder’s selection in one environment of superior performers may not hold true in another environment. By measuring the G × E interactions, the breeder is usually better equipped to determine the best breeding strategy to use and develop the genotype that is most adapted to the target region (Acquaah, 2007).

Development of cultivars or varieties, which can be adapted to a wide range of diversified environments, is the ultimate goal of plant breeders in crop improvement programs. The adaptability of a variety over diverse environments is usually tested by the degree of its interactions with different environments under which it is planted. A variety or genotype is considered to be more adaptive or stable one if it has a high mean yield but a low degree of fluctuation in yielding ability when grown over diverse environments. G x E interactions become important when the rank of breeding lines changes in different environments. This change in rank has been defined as crossover G x E interaction (Baker, 1988). G x E interactions in general, and G x E interactions of crossover type in particular, are considered to have a negative impact on the success of breeding programs, because breeders search for a few widely adapted cultivars. Whilst this is probably the best strategy in the case of breeding programs in developed countries targeted to favorable environments, Stroup et al. (1993) suggested that, in case of unfavorable environments, breeders may look at G x E interactions in a different way. Measuring G x E is important in order to determine an optimum strategy for selecting genotypes with adaptation to target environments (Annicchiarico, 1997). In plant breeding programs, potential genotypes are usually evaluated in different environments (locations and years) before selecting desirable genotypes. For quantitative traits such as yield, the relative performance of different cultivars often varies from one environment to another. Such statistical interaction results from changes in the relative ranking of the genotypes or changes in the magnitudes of differences between genotypes from one environment to another. Changes in ranking make it difficult for the plant breeder to decide which genotype should be selected (Nguyen et al., 1980). The importance of G x E interactions in sugarcane selection is widely recognized (Milligan et al., 1990). Environmental effects on sugarcane yields may be due to differing nutrient deficiencies (Anderson et al., 1995), disease pressures or climatic differences among locations (Magarey and Mewing, 1994). However, the vast majority of studies addressing the effects of location on sugarcane yields have focused on the interaction of genotype x environment. Numerous studies have reported significant G x E interactions and recommended sugarcane selection in differing environments (Bissessur et al., 2010).

The objectives of the present research work to evaluate promising genotypes of sugarcane for their yield and associated parameters under two different agro-climatic conditions of Khyber Pakhtunkhwa (KP) Province of Pakistan and to determine the magnitude of yield differences in both locations.

1 Results and Discussion

Multi-location testing is desired in crop improvement program as elite breeding lines are normally tested across several locations over many years before the best one to be released to growers. The aim of this study was to check the performance of elite sugarcane genotypes under the two different agro-ecological conditions of the Khyber Pakhtunkhwa, Pakistan. The variations in varietal performance under the influence of different environmental conditions is defined as genotype by environment (G x E) interactions.

Mean results indicated that number of nodes plant-1 ranged from 17.16 to 23.72 at SCRI, Mardan vs. 19.00 to 23.62 at Harichand (Table 3). Approximately 68.75% of the sugarcane genotypes produced more nodes at Harichand than at SCRI, Mardan. At SCRI, Mardan, the maximum (23.72) nodes plant-1 were produced by genotype Hoth127 whereas the minimum (17.16) by genotype MS99HO675. Similarly, at Harichand, the highest nodes plant -1 (23.62) were produced by genotype MS99HO388 while the lowest (19.00) were produced by check genotype Mardan93. Averaged over 16 sugarcane genotype, nodes/plant at SCRI, Mardan and Harichand were 19.61 and 20.63, respectively.

Table 3 Mean performance for nodes plant-1, internode length and cane diameter of 16 sugarcane genotypes evaluated at two locations of Khyber Pakhtunkhwa during 2011-12 and 2012-13 Note: Ns = Non-significant, G X L = Genotype x location

1.1.5 Internode length

Analysis of variance results across locations and years exhibited highly significant (p≤0.01) genetic differences among the sugarcane genotypes for internode length (Table 1). Similarly, highly significant (p≤0.01) differences were also observed for both tested years and locations and interactions of year x location, genotype x year and genotype x location for this attribute. Jackson and Hogarth (1992) found that genotype x location interactions were more important than genotype x crop-year interactions in Australia. However, genotype x year x location interactions were non-significant.

The mean results indicated that internode length ranged from 12.54 to 18.83 cm at SCRI, Mardan vs. 13.08 to 15.96 cm at Harichand (Table 3). About 75% of the sugarcane genotypes had longer internode at SCRI, Mardan than at Harichand. At SCRI, Mardan, genotype MS94CP15 had longest (18.83 cm) internode while the genotype Hoth127 the shortest (12.54 cm). Similarly, at Harichand genotype MS99HO675 had the longest (15.96 cm) internode while genotype MS99HO388 the shortest (13.08 cm). Averaged over 16 sugarcane genotypes, internode length at SCRI, Mardan and Harichand were 15.59 and 14.40 cm, respectively.

1.1.6 Cane diameter

The combined over years and locations mean square results exhibited non-significant (p≥0.05) variations among the genotypes for cane diameter (Table 1). These results are in good agreement with those of Arain et al. (2011) who got similar results for the same parameter in a qualitative and quantitative traits study of sugarcane candidate varieties at Thatta. Two tested years and year x location interactions showed highly significant differences while locations showed significant differences for this trait. However, the interactions of genotype x year, genotype x location and genotype x year x location were non-significant.

Mean results indicated that cane diameter ranged from 20.01 to 24.52 mm at SCRI, Mardan vs. 18.27 to 23.84 mm at Harichand (Table 3). About 62.50% of the sugarcane genotypes had thicker diameter at SCRI, Mardan than at Harichand. At SCRI, Mardan, genotype S97CP288 was the thickest (24.52 mm) while genotype RS97N45 was the thinnest (20.01 mm). Similarly, at Harichand genotype MS99HO388 was the thickest (23.84 mm) while genotype MS99HO675 was the thinnest (18.27 mm). Averaged over 16 sugarcane genotypes, cane diameter at SCRI, Mardan and Harichand were 22.20 and 21.22 mm, respectively.

1.1.7 Cane yield

Combined over years and location mean square results showed significant (p≤0.05) differences among the genotypes for cane yield (Table 1). Similarly, three way interactions were also significant. Years, locations and year x location interactions showed highly significant (p≤0.01) variations for this trait. However, the interactions of genotype x location and genotype x year were non-significant. Similar results were reported by Rea and Vieira (2002) wherein they conducted experiment on genotype x environment interactions in sugarcane in the central-western region of Venezuela and got similar results for the same parameter. The results suggested that a single trial at single location could be sufficient for selection of superior genotypes.

Mean results indicated that cane yield ranged from 59.20 to 88.98 t/ha at SCRI, Mardan while 30.72 to 52.91 t/ha at Harichand (Table 4). All the genotype at SCRI, Mardan showed greater cane yield than at Harichand. At SCRI, Mardan, the maximum cane yield (88.98 t/ha) was recorded for the genotype MS99HO317 while the minimum (59.20 t/ha) for the genotype Hoth127. In this way, at Harichand the highest cane yield (52.91 t/ha) was recorded for genotype MS99HO391 while the lowest (30.72 t/ha) for genotype S96SP1215. Averaged over 16 sugarcane genotypes, cane yield at SCRI, Mardan and Harichand were 68.71 and 44.37 t/ha, respectively.

Table 4 Mean performance for cane yield and milliblecane of 16 sugarcane genotypes evaluated at two locations of Khyber Pakhtunkhwa during 2011-12 and 2012-13 Note: Ns = Non-significant, G X L = Genotype x loca

1.1.8 Number of millable canes

The mean squares across years and locations of the sugarcane genotypes showed similar performance (p≥0.05) for number of millable canes (Table 5). Similarly, interactions of genotype x year, genotype x location and genotype x year x location were also non-significant for this trait. However, two tested years and locations and year x location interactions were highly significant (p≤0.01) for this trait. Our result are in contrary with those of Okaz et al. (2011) who performed research on stability parameters of cane yield and its components under various planting dates and inter-row spacing for 10 sugarcane genotypes.

Table 5 Mean squares for millable cane, c. brix, pol, purity, sugar recovery and sugar yield of 16 sugarcane genotypes at two locations of Khyber Pakhtunkhwa, during 2011-12 and 2012-13 Note: * ,** =Significant at 5% and 1% levels of probability; ns = non-significant

1.2 Sugar yield

The mean squares across years and locations of the sugarcane genotypes were non-significant (p≥0.05) for sugar yield (Table 5). These results are in contrary with the findings of Panhwar et al. (2004) who evaluated new sugarcane genotypes for quality attributes and cane yield in different ecological zones of Sindh. Similarly, interactions of genotype x year, genotype x location and genotype x year x location were non-significant for this trait as well, while years, locations and year x location interactions were highly significant (p≤0.01) for this trait.

Table 6 Mean performance for sugar percentage recovery and sugar yield of 16 sugarcane genotypes evaluated at two locations of Khyber Pakhtunkhwa during 2011-12 and 2012-13 Note: Ns = Non-significant, G X L = Genotype x location

Mean results for sugar yield ranged from 6.44 to 10.01 t/ha at SCRI, Mardan vs. 2.94 to 5.33 t/ha at Harichand (Table 6). All sugarcane genotypes showed superior performance at SCRI, Mardan than at Harichand. At SCRI, Mardan, the highest sugar yield (10.01 t/ha) was produced by genotype MS99HO317 against check cultivars while the minimum (6.44 t/ha) by genotype Hoth127. Similarly, at Harichand, the highest sugar yield (5.33 t/ha) was produced by genotype MS94CP15 against the check cultivars while the lowest (2.94 t/ha) by genotype MS99HO388. Averaged over 16 sugarcane genotypes, sugar yield at SCRI, Mardan and Harichand were 7.49 and 4.24 t/ha, respectively.

2 Conclusions

Based on tillering ability, millable canes, cane yield, sugar recovery and sugar yield, the genotypes MS99HO317, MS99HO93, MS92CP979 and MS91CP238 were superior at SCRI, Mardan. The performance of other genotypes was also appreciable. At test location-II, the cultivars MS91CP272, MS99HO391, MS94CP15 and MS99HO391 were superior on the basis of tillers, millable canes, sugar recovery and sugar yield compared to other genotypes. A reason for the low performance of genotypes at location-II was the higher infestation of the sugarcane crop by termites in the soil, excessive rainfall, flood and fluctuations in sowing time. It could be concluded that none of the genotypes including check cultivars were superior with respect to all attributes across all environments. Based on combined over years and locations performance, it could be concluded that genotypes MS99HO317, MS91CP238, MS92CP979 and CP89831 exhibited comparatively superior performance in terms of percentage germination, cane yield, number of tillers, millable canes, sugar recovery and sugar yield. It is suggested that Mardan is the best location for sugarcane cultivation because all the genotypes showed relatively better performance there as the performance of some genotypes was almost double for some parameters. These genotypes may be put in further evaluation and uniform yield trials. Furthermore, it is suggested that the poor performed sugarcane genotypes may also be further tested under potential areas as two years screening is not sufficient to judge the performance of these genotypes.

3 Materials and Methods

3.1 Experimental location, material and design

To assess the genotype x environment interactions, a set of 16 promising sugarcane genotypes introduced from various international sugarcane research institutes (Table 7) was studied during the spring cropping seasons of 2011-12 and 2012-13. This experiment was conducted at two different locations of Khyber Pakhtunkhwa-Pakistan i.e., Sugar Crops Research Institute (SCRI), Mardan, and Sugarcane Seed Multiplication Farm (SSMF), Harichand-Charsadda. The two sites are regularly irrigated zones and have usually no water deficiency. Status of each site is given in the Table 8

Table 7 List of 16 sugarcane genotypes and their source used for genotype x location studies at scri, mardan and ssmf, harich and during 2011-12 and 2012-13 Note: MS: Mardan Selection, Hoth: Houma-Thatta, SP: São Paulo, HO: Houma, N: Natal USDA-ARS: United States Department of Agriculture-Agriculture Research Service

Table 8 Geographical characteristics of the two test locations of KPK

At each site triplicate RCB, design was used with plot area of 67 m² (10 m x 6.7 m). Each genotype was sown in seven rows with row to row distance of 90 cm. Double three budded sets were used as sowing material. The central row consisted of 150 buds. Data were recorded on five randomly selected genotypes from central row of each plot. Two plant crops were harvested from each location, successively. Ten parameters were examined in each plant crop. Recommended dose of fertilizer was applied as N (150 kg/ha), P (100 kg/ha), and K (100 kg/ha) from SOP, DAP and Urea as 225.00 kg DAP/ha at planting time and 250.00 kg SOP with 125 kg urea/ha in May/June. Urea was also additionally applied at 125.00 kg/ha at the time of earthing up. The detail description of eachparameters as following.

3.2 Description of morphological traits

3.2.1 Germination

Germination is the foundation of any crop and the success of a crop heavily depends on emergence. Sugarcane propagation occurs through cuttings of the stalk or seed cane containing usually three or more nodes with buds. Germination under field condition starts usually from 7 to 10 days. Two times germination data were recorded as:

1) Germination count in stage-i: Number of buds germinated per 150 buds in a 10m long central row was recorded after 30 days of sowing.

2) Germination count in stage-ii: This attribute was recorded as number of buds germinated per 150 buds in a 10 m long central row after 30 days of the 1^st germination. Both germinations data were first averaged and the germination percentage was then calculated.

Germination percentage = (Total germinated buds / Total sown buds) × 100

3.2.2 Number of tillers

Tillering behavior is a beneficial attribute of a variety because it provides the plants with appropriate number of stalks for a good yield. Tillering starts from around 35- 40 days after planting and may last up to 130-135 days. Tillering in sugarcane is not a synchronized process, therefore, it was also recorded twice as:

1) number of tillers count in stage-i: This parameter was counted as number of tillers in a 10 m long central row after 90 days of the plantation in the month of May.

2) number of tillers count in stage-ii: This was counted like stage-i, after one month of the stage-i.

Data recorded in both stages were averaged and used in final analysis.

3.2.3 Plant height

Plant height was measured form the soil surface to the top dewlap of the plant with the help of meter rod. This parameter was also recorded two times.

1) plant height in growth stage-i: Height of the standing five canes in the field was recorded using meter rod from soil surface to the top in the month of July.

2) plant height in growth stage-ii: This was also recorded on five plants after 30 days of the stage-i.

3.2.4 Cane diameter

At maturity stage, cane diameter was measured on five randomly selected canes with the help of digital Vernier Caliper by holding the individual cane (top, middle and base) between two jaws of the instrument. The averaged value was used as cane diameter.

3.2.5 Number of nodes plant-1

This was recorded at cane maturity stage by counting the number of buds per plant.

3.2.6 Inter node length

This was measured as the average value of the distance between two nodes recorded in the top, middle and base of the cane.

3.2.7 Cane yield

Cane yield was determined with the help of the following formula: 

Cane yield (t/ha) = (X ×10,000/Plot size × 1000)

Where “X” is sugarcane yield.

3.2.8 Number of millable canes

This parameter was recorded on plot basis by counting the number of canes that were millable (excluding the tillers which had not developed in to mature canes).

3.2.9 Sugar recovery (%)

Sugar recovery was calculated with the help of the relationship following (Islam et al., 2011).

Sugar recovery (%) = [Pol % – 0.5(Brix – Pol %)] x 0.70

For quality analysis of sugar quality attributes, five canes of each clone were collected from the field and samples were subjected to sugarcane quality analysis in the laboratory at SCRI, Mardan and the obtained data were analyzed statistically.

3.2.10 Sugar yield

It is the total recoverable percentage sugar in the cane. This was calculated by the following relationship following (Khaled, 2010).

Sugar yield (t/ha) = [Yield (t/ha) x Sugar recovery (%)] /100

3.3 Statistical analysis

Analysis of variance was calculated using the following model:

Yijk = μ + Gi + Ej + Lk + Bjkl+ GEij + GLik + ELjk + GELijK + eijk

Where Yijk is the corresponding variable of the i-th genotype in j-th year and k-th location or the expected yield of the ith genotype in the jth environment and kth location, μ is the overall mean or grand mean, Gi is the main effect of i-th Genotype, Ej is the main effect of j-th year, Bjkl is the effect of l-th replication in the j-th year and k-th location, GEij is the interaction of i-th genotype with j-th year, GLik is the interaction of i-th genotype with k-th location, ELjk is the interaction of j-th year with k-th location, GELijk is the interaction of i-th genotype with j-th environment and k-th location and eijk is the random error term. This model was used by (Bissessur et al., 2010) with little modification in notations regarding this study. Data recorded in each location and years were analyzed as combined experiment series in RCBD with the General Linear Model (GLM) procedure of the SAS statistical software (SAS Institute, 2007).

Authors’ contributions

Dr. Muhammad Khalid designed this research idea, carried out the analysis of data using different computer softwares and drafted this scientific article. Other all co-authors (Dr. Hidayt ur Rahman, Dr. Farhatullah, Dr. Ashiq Rabbani and Dr. Muhammad Iqbal) helped in various sections of the manuscript. Finally, Dr. David A. Lightfoot incorporated his valuable suggestion during writ-up of this manuscript to be published in Plant Gene & Trait. All authors read and approved the final manuscript.

Acknowledgments

This research was funded by the Higher Education Commission (HEC) of Pakistan and Sugar Crops Research Institute, Mardan, Pakistan. All the authors are very thankful to the staff of the Sugar Crops Research Institute (SCRI), Mardan-Paksitan from official to sub-ordinate for their co-operation and valuable advices regarding rising of the sugarcane crop. Special thanks are extended to Mr. Mohammad Tahir and Mr. Islam Zada working as Research Officers at Sugar Crops Research Institute (SCRI), Mardan-Paksitan who helped a lot in data collection of different parameters of sugarcane.

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