In recent years, the use of presprouted setts (MPB, which stands for “mudas pre-brotadas” in Portuguese) to establish commercial sugarcane nurseries has grown in Brazil. MPB and single-bud setts (SBS) have the advantage of requiring less planting material and enabling a higher multiplication rate of the source material as compared with the conventional multibud sett (MBS) planting system. Sugarcane breeding programs could also potentially benefit from the precise spacing afforded by MPB or SBS planting materials, by reducing trial variability. However, the effect of planting material type on the performance ranking and consequent selection of sugarcane clones in a breeding program has not been previously investigated. We present results on possible interactions between genotype and the type of planting material (MPB, MBS, or SBS) on key performance parameters, like sugar content, cane yield, and sugar yield, in the context of the intermediate phase of a sugarcane breeding program. Our results indicate that trial quality does not necessarily improve with the use of MPB or SBS planting materials and that type of planting material has a significant effect on the ranking of sugarcane genotypes, and this needs to be taken into consideration when considering the use of new planting technologies in breeding trials of vegetatively propagated crops such as sugarcane.
Sugarcane is a vegetatively propagated crop. Manual planting of multibud setts (MBS) is the traditional planting material used in the planting of commercial nurseries and production fields. To minimize the risk of gaps in the resultant stand, manual planting rates are high (15–21 buds/meter), corresponding to 11–14 tonnes (T) of planting material/hectare (ha). With mechanized planting, the amount of planting material used is even larger, reaching levels greater than 20 T/ha. Sugarcane production costs have increased due to increased labor and agricultural input costs, with the cost of planting material accounting for almost 25% of operational production costs [
New planting systems have been developed to overcome some of the disadvantages of traditional methods. The presprouted seedling (MPB) planting system allows for a reduction in the quantity of planting material and better control of seedling vigor [
Genetic improvement of sugarcane is based on the selection and cloning of superior genotypes of segregating populations obtained through sexual crosses between different individuals [
Sugarcane breeding trials could benefit from using planting systems that increase efficiency and data quality. Higher trial data quality could result from more precise spacing in trial plots. Planting systems with the potential to do more replications in early breeding stages due to more efficient utilization of scarce planting material would provide an additional benefit. However, planting system modifications have the potential to affect the ranking and consequent selection of genotypes, since experimental results of important performance attributes such as yield and sugar content could differ depending on the planting system used. Studies on intrarow spacing and number of buds per sett in commercial varieties [
In the present study, we evaluate potential interactions between genotypes and the type of planting system and whether the type of planting material has an effect on trial data quality.
Three types of planting material were tested: 3-4 bud setts (MBS—conventional method), presprouted seedlings (MPB), and 5 cm, single-bud setts (SBS). All planting materials were generated from selected healthy stalks harvested approximately 9 months after planting.
All three types of planting material were planted at a single location in three different adjacent trials. All trials were in a randomized complete block design with 3 replicates. Plots consisted of two 10 m rows spaced 1.5 m apart. Adjacent plots were spaced 3 m apart along their length.
The same genotypes (cultivars and clones; see Table
Varieties and clones used in the study.
Varieties | Clones | ||
---|---|---|---|
RB86-7515 | S09-0001 | S09-0040 | S09-0114 |
RB96-6928 | S09-0007 | S09-0046 | S09-0122 |
SP81-3250 | S09-0011 | S09-0048 | S09-0140 |
S09-0022 | S09-0052 | S09-0144 | |
S09-0023 | S09-0055 | S09-0146 | |
S09-0031 | S09-0069 | S09-0148 | |
S09-0036 | S09-0080 | S09-0153 | |
S09-0037 | S09-0081 | S09-0154 | |
S09-0038 | S09-0098 |
The process for making and planting the different types of planting materials is described below and in the accompanying figures (Figures
Process for SBS (single-bud sett) production and planting.
Process for MPB (presprouted seedling) production and planting.
Process for MBS (multibud sett) production and planting.
Eight-month-old sugarcane stalks were harvested and 5 cm, single-bud setts were cut and planted in soil mix. The resultant sprouted seedlings were manually planted in the field trial after 50 days at an intrarow spacing of 0.5 m.
Ten-month-old sugarcane stalks were harvested, and 5-cm, single-bud setts were cut and treated with a slurry consisting of industrial proprietary treatment. Subsequently, these were planted manually in the field at a rate of 8 single-bud setts per meter.
Ten-month-old sugarcane stalks were harvested manually and placed in row furrows. These were cut with a machete in the furrow into 30–40 cm pieces, as per conventional manual cane planting practice.
The 3 field trials were planted in a single week in April 2014. Fertilization and cultural practices followed conventional commercial practice and were the same for all trials. Evaluations of sugarcane agronomic parameters were made over two harvest cycles (plant cane and 1st ratoon). In August 2015, a sample of 10 stalks per plot was subjected to laboratory POL analysis (a measure of sugar content). Subsequently, in the same month, the trial was mechanically harvested and whole, individual plots were weighed to estimate TCH (tonnes cane per hectare). From the POL and TCH parameters, the TPH (tonnes POL per hectare) was calculated for the plant cane harvest. It was not possible to measure POL in the 1st ratoon harvest, but in May 2016, the Brix of 5 stalks per plot was taken and averaged. Mechanized harvesting and weighing of trial plots were conducted in June 2016. Thus, Brix, TCH, and TBH parameters (tonnes Brix per hectare) were estimated for the 1st ratoon harvest.
Analysis of variance was done by planting material (MPB, SBS, and MBS) and harvest cycle (plant cane, 1st ratoon), considering the effects of genotype (26 clones and three varieties) and blocks (3 per planting material). For each of the three traits (POL or Brix; TCH; and TPH or TBH), the ratio between the largest and smallest mean residual squares was less than three. As a result, we performed joint analyses by traditional ANOVA and mixed model restricted maximum likelihood (REML)/best linear unbiased prediction (BLUP), in which planting material, harvest cycle, and blocks nested within planting material were fixed effects, and genotype, as well as genotypic interactions with planting material and harvest cycle, were random effects. A split-plot design was not used due to possible plot border effects resulting from different growth rates of different adjacent plant material types. As stated above, mean residual squares within each trial were similar; consequently, we performed a joint analysis by ANOVA (despite the absence of randomization), much as experiments across locations are analyzed.
Within each cycle (plant and ratoon cane), statistical modeling was done as for a split-plot design in time.
Mean values of TPH_TBH were similar for the three planting material types tested (Table
Average performance parameters and coefficients of variation (CV) in trials with 3 types of planting materials, 29 genotypes, and 3 blocks (replicates) per planting material.
Performance parameter | MBS average | SBS average | MPB average |
---|---|---|---|
POL-Brix | |||
|
12.42 | 13.55 | 13.05 |
|
13.59 | 14.71 | 14.71 |
|
7.47 | 5.89 | 7.34 |
|
8.25 | 7.23 | 7.46 |
|
|||
TCH | |||
|
136.11 | 134.78 | 139.10 |
|
104.79 | 97.35 | 106.95 |
|
12.54 | 15.15 | 13.95 |
|
12.19 | 16.69 | 14.29 |
|
|||
TPH_TBH | |||
|
16.85 | 18.10 | 17.94 |
|
14.29 | 14.21 | 14.84 |
|
14.44 | 17.01 | 16.85 |
|
15.81 | 15.53 | 16.81 |
Conventional analysis of variance (Table
Mean squares (MS) and
Source of variation | POL_BRIX | TCH | TPH_TBH |
---|---|---|---|
Planting material (PM) | 59.60 ( |
1484.92 ( |
24.17( |
Genotype | 19.83 ( |
4855.15 ( |
104.95 ( |
Genotype × PM | 1.48 ( |
494.80 ( |
12.48 ( |
Harvest cycle | 141.37 ( |
12,2717.39 ( |
1085.90 ( |
Harvest cycle × PM | 1.88 ( |
364.55 ( |
13.61 ( |
Harvest cycle × genotype | 3.87 ( |
1002.86 ( |
16.51 ( |
Random effect variances obtained using a mixed model (Table
Components and percentage of variance as obtained in a pooled joint analysis with a mixed REML/BLUP model, considering genotype, genotype × planting material, genotype × harvest cycle, and residual as random effects.
Variable | POL_BRIX | TCH | TPH_TBH |
---|---|---|---|
Genotypes | 0.8658 (37.08%) | 232.02 (36.41%) | 5.1067 (36.16%) |
Genotypes × PM | 0.0632 (2.71%) | 37.75 (5.92%) | 1.0028 (7.10%) |
Genotypes × harvest cycle | 0.3081 (13.20%) | 93.47 (14.67%) | 1.3193 (9.34%) |
Residual | 1.0978 (47.02%) | 274.07 (43.00%) | 6.6918 (47.39%) |
Predicted genotypic differences (PGDs) obtained in the mixed model (Tables
Predicted genotypic differences (PGD) for TPH_TBH across 29 genotypes (mean plant cane TPH and 1st ratoon TBH) and three planting material types (MBS, SBS, or MPB).
Rank | Genotype | MBS |
|
Genotype | SBS |
|
Genotype | MPB |
|
---|---|---|---|---|---|---|---|---|---|
1 | S09-0146 | 4.7444 |
|
RB966928 | 4.4965 |
|
RB966928 | 4.592 |
|
2 | RB867515 | 4.4646 |
|
S09-0144 | 4.1737 |
|
RB867515 | 4.5099 |
|
3 | RB966928 | 3.702 |
|
S09-0146 | 4.1348 |
|
S09-0122 | 3.0073 |
|
4 | S09-0031 | 3.0899 |
|
S09-0114 | 3.4487 |
|
S09-0114 | 2.614 |
|
5 | S09-0114 | 2.4153 |
|
S09-0038 | 3.2957 |
|
S09-0140 | 2.5809 |
|
6 | S09-0038 | 2.0233 | 0.07 | S09-0052 | 2.7208 |
|
S09-0144 | 2.304 | 0.0597 |
7 | S09-0052 | 1.887 | 0.09 | S09-0153 | 2.1413 | 0.0919 | S09-0031 | 1.773 | 0.1228 |
8 | S09-0140 | 1.6314 | 0.143 | S09-0140 | 2.0738 | 0.0607 | S09-0069 | 1.5078 | 0.1889 |
9 | S09-0144 | 1.2664 | 0.254 | S09-0148 | 1.6054 | 0.1454 | S09-0023 | 1.3682 | 0.2614 |
10 | S09-0148 | 1.2593 | 0.257 | RB867515 | 0.8213 | 0.4548 | S09-0052 | 1.0307 | 0.3682 |
11 | S09-0037 | 0.7224 | 0.515 | S09-0037 | 0.7444 | 0.555 | S09-0146 | 0.9092 | 0.4548 |
12 | S09-0122 | 0.3986 | 0.719 | S09-0031 | 0.3428 | 0.7548 | S09-0007 | 0.5837 | 0.6099 |
13 | SP813250 | 0.3901 | 0.725 | S09-0069 | 0.1064 | 0.9227 | S09-0153 | 0.0999 | 0.9345 |
14 | S09-0046 | 0.2438 | 0.826 | S09-0055 | −0.045 | 0.9713 | S09-0046 | −0.209 | 0.8549 |
15 | S09-0023 | 0.1558 | 0.888 | S09-0122 | −0.09 | 0.9431 | S09-0148 | −0.643 | 0.6231 |
16 | S09-0055 | −0.394 | 0.722 | SP813250 | −0.183 | 0.8674 | S09-0055 | −0.699 | 0.5416 |
17 | S09-0069 | −0.435 | 0.695 | S09-0154 | −1.439 | 0.1916 | S09-0038 | −0.912 | 0.4259 |
18 | S09-0153 | −0.659 | 0.552 | S09-0080 | −1.678 | 0.1282 | S09-0040 | −0.943 | 0.4101 |
19 | S09-0007 | −0.694 | 0.532 | S09-0022 | −1.793 | 0.1565 | S09-0001 | −1.12 | 0.3576 |
20 | S09-0036 | −0.708 | 0.524 | S09-0081 | −1.854 | 0.0932 | S09-0048 | −1.192 | 0.2983 |
21 | S09-0022 | −1.703 | 0.126 | S09-0040 | −2.074 | 0.0607 | S09-0037 | −1.501 | 0.218 |
22 | S09-0001 | −2.118 | 0.058 | S09-0023 | −2.299 | 0.0379 | S09-0081 | −1.512 | 0.2148 |
23 | S09-0154 | −2.368 | 0.034 | S09-0046 | −2.327 | 0.1421 | S09-0036 | −1.605 | 0.1621 |
24 | S09-0048 | −2.389 | 0.033 | S09-0007 | −2.401 | 0.0303 | S09-0022 | −1.733 | 0.1313 |
25 | S09-0081 | −2.808 | 0.012 | S09-0036 | −2.527 | 0.0228 | SP813250 | −2.164 | 0.0767 |
26 | S09-0098 | −2.91 | 0.01 | S09-0011 | −2.685 | 0.0157 | S09-0154 | −2.295 | 0.0464 |
27 | S09-0011 | −3.422 | 0.002 | S09-0048 | −2.789 | 0.0285 | S09-0098 | −2.682 | 0.0203 |
28 | S09-0080 | −3.856 | 0.0007 | S09-0001 | −2.907 | 0.0226 | S09-0080 | −3.669 | 0.0017 |
29 | S09-0040 | −3.93 | 0.0005 | S09−0098 | −3.015 | 0.0068 | S09-0011 | −4.001 | 0.0013 |
TM1 | — | 15.57 |
— | — | 16.16 |
— | — | 16.26 |
— |
1TM with different letters indicate significant (
Predicted genotypic differences (PGD) for TCH across 29 genotypes (mean plant cane and 1st ratoon TCH) and three planting material types (MBS, SBS, or MPB).
Rank | Genotype | MBS |
|
Genotype | SBS |
|
Genotype | MPB |
|
---|---|---|---|---|---|---|---|---|---|
1 | S09-0146 | 39.089 |
|
S09-0146 | 26.489 |
|
RB867515 | 28.893 |
|
2 | RB867515 | 29.224 |
|
RB966928 | 24.382 |
|
RB966928 | 22.466 |
|
3 | S09-0114 | 20.817 |
|
S09-0114 | 23.463 |
|
S09-0114 | 16.734 |
|
4 | S09-0038 | 20.557 |
|
S09-0153 | 22.079 |
|
S09-0146 | 15.104 | 0.0548 |
5 | RB966928 | 19.358 |
|
S09-0038 | 21.821 |
|
S09-0007 | 14.768 | 0.0461 |
6 | S09-0031 | 14.071 | 0.06 | S09-0144 | 21.342 |
|
S09-0069 | 13.874 | 0.0608 |
7 | S09-0144 | 12.829 | 0.086 | S09-0052 | 16.24 | 0.0677 | S09-0154 | 10.657 | 0.1486 |
8 | S09-0052 | 8.2784 | 0.266 | S09-0154 | 12.845 | 0.097 | S09-0140 | 9.5021 | 0.1974 |
9 | S09-0154 | 5.8661 | 0.43 | RB867515 | 8.122 | 0.2923 | S09-0038 | 9.2683 | 0.2086 |
10 | S09-0153 | 5.3894 | 0.469 | S09-0140 | 6.2557 | 0.4168 | S09-0023 | 8.135 | 0.2985 |
11 | S09-0007 | 4.4072 | 0.553 | S09-0148 | 5.5204 | 0.4735 | S09-0040 | 7.6597 | 0.2982 |
12 | S09-0140 | 3.4683 | 0.641 | S09-0069 | 3.8803 | 0.6142 | S09-0153 | 6.2699 | 0.4226 |
13 | S09-0148 | 3.4538 | 0.642 | S09-0037 | 1.7567 | 0.8423 | S09-0144 | 6.254 | 0.4238 |
14 | SP813250 | 2.9916 | 0.687 | S09-0040 | 0.8263 | 0.9145 | S09-0122 | 4.4561 | 0.5445 |
15 | S09-0069 | 0.5793 | 0.938 | S09-0055 | −0.536 | 0.9516 | S09-0031 | 4.0024 | 0.5862 |
16 | S09-0037 | 0.0882 | 0.991 | SP813250 | −2.002 | 0.7948 | S09-0052 | −0.356 | 0.9613 |
17 | S09-0023 | −2.079 | 0.7800 | S09-0031 | −2.242 | 0.7708 | S09-0148 | −1.780 | 0.8324 |
18 | S09-0040 | −2.310 | 0.756 | S09-0122 | −4.794 | 0.5873 | S09-0001 | −5.042 | 0.5189 |
19 | S09-0036 | −4.000 | 0.591 | S09-0022 | −6.746 | 0.4453 | S09-0036 | −7.231 | 0.326 |
20 | S09-0122 | −7.842 | 0.292 | S09-0080 | −8.124 | 0.2922 | SP813250 | −8.281 | 0.29 |
21 | S09-0055 | −9.301 | 0.212 | S09-0001 | −11.39 | 0.1986 | S09-0055 | −10.43 | 0.1572 |
22 | S09-0022 | −11.24 | 0.132 | S09-0007 | −12.61 | 0.1033 | S09-0046 | −11.11 | 0.1323 |
23 | S09-0046 | −11.71 | 0.117 | S09-0081 | −14.50 | 0.0614 | S09-0037 | −11.96 | 0.1274 |
24 | S09-0001 | −12.44 | 0.096 | S09-0023 | −20.16 | 0.0098 | S09-0048 | −14.78 | 0.046 |
25 | S09-0098 | −20.84 | 0.006 | S09-0011 | −21.57 | 0.0058 | S09-0022 | −15.45 | 0.0371 |
26 | S09-0081 | −23.99 | 0.002 | S09-0036 | −21.81 | 0.0053 | S09-0098 | −17.09 | 0.0214 |
27 | S09-0048 | −24.47 | 0.001 | S09-0098 | −22.26 | 0.0045 | S09-0081 | −18.45 | 0.0194 |
28 | S09-0011 | −28.56 | 2 |
S09-0048 | −22.57 | 0.0117 | S09−0080 | −25.76 | 0.0006 |
29 | S09-0080 | −31.69 | <0.001 | S09-0046 | −23.71 | 0.0327 | S09-0011 | −30.31 | 0.0002 |
TM1 | — | 120.45 |
— | — | 116.07 |
— | — | 121.62 |
— |
1TM with different letters indicate significant (
Predicted genotypic differences (PGD) for POL_Brix across 29 genotypes (mean plant cane POL and 1st ratoon Brix) and three planting material types (MBS, SBS, or MPB). TM = trial mean;
Rank | Genotype | MBS |
|
Genotype | SBS |
|
Genotype | MPB |
|
---|---|---|---|---|---|---|---|---|---|
1 | S09-0046 | 1.4759 |
|
S09-0046 | 1.7214 |
|
S09-0122 | 1.8558 |
|
2 | S09-0122 | 1.2755 |
|
S09-0140 | 0.9188 |
|
S09-0144 | 1.1144 |
|
3 | S09-0140 | 0.8705 | 0.0667 | S09-0144 | 0.7226 | 0.0828 | S09-0046 | 1.1046 |
|
4 | S09-0031 | 0.8431 | 0.0757 | S09-0052 | 0.7143 | 0.0864 | S09-0140 | 0.9496 |
|
5 | RB966928 | 0.8321 | 0.0795 | S09-0122 | 0.6489 | 0.119 | S09-0081 | 0.9468 |
|
6 | S09-0055 | 0.7827 | 0.0989 | S09-0036 | 0.6434 | 0.1222 | RB966928 | 0.9301 | 0.0536 |
7 | S09-0148 | 0.7676 | 0.1055 | S09-0023 | 0.6406 | 0.1238 | S09-0031 | 0.9022 | 0.0611 |
8 | S09-0048 | 0.7429 | 0.1171 | S09-0148 | 0.5182 | 0.2125 | S09-0052 | 0.8589 | 0.0744 |
9 | S09-0052 | 0.7291 | 0.124 | RB966928 | 0.489 | 0.2392 | S09-0048 | 0.6453 | 0.179 |
10 | S09-0037 | 0.6221 | 0.1889 | S09-0031 | 0.4834 | 0.2446 | S09-0055 | 0.6145 | 0.2005 |
11 | RB867515 | 0.3585 | 0.448 | S09-0011 | 0.3832 | 0.3558 | RB867515 | 0.44 | 0.3587 |
12 | S09-0023 | 0.3516 | 0.4567 | S09-0048 | 0.3053 | 0.4617 | S09-0011 | 0.3297 | 0.4913 |
13 | S09-0081 | 0.202 | 0.6687 | S09-0037 | 0.2511 | 0.5449 | S09-0037 | 0.2697 | 0.5734 |
14 | S09-0080 | 0.154 | 0.7443 | S09-0055 | 0.2191 | 0.5972 | S09-0148 | 0.1943 | 0.6849 |
15 | S09-0011 | 0.1306 | 0.782 | S09-0114 | 0.2038 | 0.623 | S09-0022 | 0.1859 | 0.6978 |
16 | S09-0114 | -0.1494 | 0.7517 | SP813250 | 0.1482 | 0.7208 | S09-0023 | 0.1105 | 0.8175 |
17 | S09-0146 | −0.1549 | 0.7429 | S09-0081 | 0.1384 | 0.7384 | S09-0114 | 0.01136 | 0.9811 |
18 | SP813250 | −0.1549 | 0.7429 | S09-0146 | 0.137 | 0.741 | S09-0069 | −0.2428 | 0.6122 |
19 | S09-0036 | −0.1919 | 0.6843 | S09-0098 | −0.1356 | 0.7436 | S09-0001 | −0.3237 | 0.4992 |
20 | S09-0022 | −0.2455 | 0.6032 | S09-0038 | −0.1982 | 0.6326 | S09-0080 | −0.3433 | 0.4737 |
21 | S09-0098 | −0.2798 | 0.5536 | RB867515 | −0.2858 | 0.4908 | S09-0098 | −0.5695 | 0.2353 |
22 | S09-0144 | −0.3567 | 0.4503 | S09-0069 | −0.4527 | 0.2757 | S09-0153 | −0.6351 | 0.1859 |
23 | S09-0069 | −0.439 | 0.353 | S09-0022 | −0.5598 | 0.1781 | S09-0146 | −0.691 | 0.1504 |
24 | S09-0038 | −0.4733 | 0.3168 | S09-0080 | −0.5765 | 0.1656 | S09-0036 | −0.751 | 0.1183 |
25 | S09-0001 | −0.542 | 0.2519 | S09-0153 | −0.7323 | 0.0789 | SP813250 | −0.8515 | 0.0769 |
26 | S09-0153 | −0.9648 | 0.0424 | S09-0007 | −0.7852 | 0.0597 | S09-0007 | −1.1126 | 0.0213 |
27 | S09-0007 | −1.2119 | 0.0111 | S09-0001 | −1.272 | 0.0025 | S09-0040 | −1.4477 | 0.0029 |
28 | S09-0154 | −2.1933 | <0.001 | S09-0040 | −1.7185 | <0.001 | S09-0038 | −1.7828 | 0.0003 |
29 | S09-0040 | −2.7808 | <0.001 | S09-0154 | −2.5698 | <0.001 | S09-0154 | −2.7127 | — |
TM1 | — | 13.00 |
— | — | 14.13 |
— | — | 13.45 |
— |
1TM with different letters indicate significant (
For TPH_TBH (Table
For TCH (Table
For POL and Brix (Table
Results of the correlations between predicted genotypic differences (PDG; Tables
Pearson’s correlation coefficients between average performance parameters for 29 genotypes across three different planting material types, using predicted genotypic differences (PDG) from Tables
Performance parameter | MBS | MPB | SBS | |
---|---|---|---|---|
POL_Brix | MBS | — | 0.82 | 0.85 |
MPB | — | — | 0.75 | |
|
||||
TCH | MBS | — | 0.85 | 0.79 |
MPB | — | — | 0.65 | |
|
||||
TPH_TBH | MBS | — | 0.77 | 0.78 |
MPB | — | — | 0.61 |
The observed CVs for the parameters analyzed (Table
Conventional analysis of variance (Table
Changes in rank order of genotypes can impact the effectiveness of clonal selection in sugarcane breeding. For example, the TPH_TBH parameter can be considered the most important one for selection in the intermediate phases of a program. Selection indices in different breeding stages vary by breeding program, as shown by [
Orgeron et al. [
On an average, good correlations of performance parameter were observed between the different types of planting material. These correlations mask the significant effect on the ranking of individual clones in these trials. MPB and SBS planting methodologies have generated enormous interest in the Brazilian sugarcane industry and have undeniable advantages in terms of reduction of planting costs and material handling logistics. However, the use of these new planting methodologies in a sugarcane breeding program will result in likely selection of genotypes well adapted to the particular type of planting material used, but may not have the best agronomic performance if used in commercial plantings using other planting systems, such as the current conventional MBS planting system.
Our study indicates that trial quality does not necessarily improve with the use of MPB or SBS planting materials compared with the conventional MBS. Additionally, the type of planting material has a significant effect on the ranking of sugarcane genotypes. Because of that, when considering the use of new planting technologies in breeding trials of sugarcane, this needs to be taken into consideration for the selection of genotypes for cane yield and sugar parameters.
The data used to support the findings of this study are available from the corresponding author upon request.
The authors declare that they have no conflicts of interest.
The authors acknowledge the support of Syngenta Proteção de Cultivos Ltda in funding this work and Marcia de Macedo Almeida for her critical reviewing of the paper.