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This study investigates the effectiveness of various acaricides and application techniques in controlling the two-spotted spider mite (Tetranychus urticae) in sugar beet fields. The research focuses on the impact of different acaricides, application methods, and environmental conditions on sugar beet yield and quality. Field experiments were conducted over two years, comparing traditional horizontal boom sprayers with Fragaria booms equipped with 3-nozzle curved spray lances. The study found that acaricide treatments significantly improved sugar beet yield and technological quality parameters compared to untreated control plots. The effectiveness of the treatments varied between years, highlighting the strong influence of environmental conditions. The traditional horizontal boom sprayer generally provided higher root and biological sugar yields, although the effectiveness of both spraying methods depended on seasonal conditions. The study concludes that spider mite management should be based on regular monitoring, timely treatment decisions, appropriate selection and rotation of active ingredients, the use of adjuvants, and careful choice of spraying technique to ensure coverage of both leaf surfaces.
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Abstract
Field experiments were carried out in 2020–2021 to assess the chemical control of Tetranychus urticae (TSSM) in sugar beet. Several acaricides representing different chemical classes and modes of action were tested. Treatments included spirodiclofen at 240 g (22.11%), a combination of hexythiazox at 250 g (23.15%) and fenpyroximate at 51.2 g (5.02%), paraffin oil-based insect/oacaricide at 770 g L−1 (89.6%), and abamectin at 18 g (1.88%). Untreated plants were used as the control. Applications were performed at the peak of the growing season, during the leaf rosette formation stage (July–August). Yield and technological quality parameters were recorded after treatment. Significant differences were found between treated and control plots. Across the two years, 12 of 13 traits showed significant variation, except for the alkalinity factor. Chemical treatments improved both yield and sugar quality compared with the control. These results confirm the effectiveness of chemical control in reducing TSSM damage and improving sugar beet production.
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Introduction
Spider mites are highly destructive pests that annually infest orchards, berry crops, vegetables, ornamentals, and, more recently, field crops, including sugar beet. These pests exhibit a strong preference for feeding on well-managed sugar beet plantations. The primary species responsible for extracting fluids from sugar beet leaves are the two-spotted spider mite Tetranychus urticae Koch, 1836, and the greenhouse red spider mite Tetranychus cinnabarinus Boisduval, 1867 (Jakubowska and Fiedler 2014; Jakubowska et al. 2017, 2021). Monitoring all species of spider mites on sugar beet plantations is crucial, as their population dynamics are influenced by weather conditions, temperature, precipitation, and air humidity. Spider mites are particularly damaging because they feed on cell sap and degrade chlorophyll, leading to chlorosis and, in severe cases, defoliation. Damage to leaf blades hinders plant growth and reduces yield. Effective management of these pests is challenging due to their tendency to feed in inaccessible areas (such as the underside of leaves, often covered by a silk web). Additionally, their rapid reproduction, especially under favorable weather conditions prevalent in recent years in Poland, exacerbates their impact. Spider mites can produce 5 to 10 new generations within a single growing season. In extreme cases, large mite populations can cause premature defoliation, forcing sugar beet plants to use stored nutrients for regrowth (Legrand et al. 2000; Ulatowska et al. 2015; Jakubowska et al. 2018).
The variability in root yield and sugar content (%) in sugar beet roots is primarily influenced by weather conditions. The period from July to September is particularly critical, as sugar beet development during this time is highly dependent on water availability. Optimal levels of solar radiation, along with appropriate distribution and total precipitation, as well as favorable air and soil temperatures, are essential for high germination rates and proper seedling development. Under these optimal conditions, full plant density in the field can be achieved. Additionally, favorable weather conditions support normal photosynthesis and enhance the accumulation of sugars within the plant (Pidgeon et al. 2001; Podlaski et al. 2017; Hoffmann and Kenter 2018). Sugar beet is a crop that requires high-quality soil to thrive. When growth conditions are favorable, the plant can rapidly produce significant green mass. In addition to maintaining an adequate soil pH, sugar beet cultivation necessitates fertilization with nitrogen, phosphorus, magnesium, and potassium, as well as supplementation with the essential micronutrient boron (Bouras et al. 2021; Romaneckas et al. 2020). However, imbalances in the supplementation of these nutrients—whether through excess, deficiency, or incorrect proportions—can lead to abnormal plant development, reduced sugar yield, and a decline in sugar quality, primarily due to the increased formation of molasses (Armin and Asgharipour 2012; Barłóg and Grzebisz 2004; Köchl 1977; Mehrandish et al. 2012; Neseim et al. 2014; Nemeata Alla et al. 2018; Wakeel et al. 2010). Moreover, the timing of sowing (Michalska-Klimczak and Wyszyński 2010) and harvesting (Alami et al. 2021) is crucial in determining the final yield and quality of the crop.
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Previous research and practical observations in fruit-growing have consistently indicated multiple factors that complicate the effective control of spider mites. These include insufficient field surveys during periods favorable to pest reproduction and limited knowledge regarding the characteristics of acaricides, particularly their efficacy across different developmental stages, their mode of action on leaves and pests, and their selectivity toward predatory mites. Additional difficulties arise from inappropriate application practices, such as reduced pesticide doses, inadequate water volumes, and treatments conducted under unsuitable weather conditions. The problem is further exacerbated by the heterogeneity of pest populations among plant species and varieties, as well as infestation pressure from adjacent plantations. Other contributing factors include the absence of systematic monitoring of treatment efficacy, delayed implementation of control measures after significant pest population growth and crop damage, misconceptions concerning the residual activity of contact acaricides, omission of sticker adjuvants that facilitate penetration, and insufficient or incorrect acaricide rotation, which accelerates the development of resistant populations.
Given these challenges, effective spider mite management requires the rotation of compounds with different mechanisms of action and the appropriate selection of application techniques, considering that spider mites colonize both surfaces of the leaf blade (Ulatowska et al. 2015). The objective of this study was to evaluate the impact of selected insecticides/acaricides applied with two different spraying techniques on sugar beet yield.
Materials and Methods
Experimental Site
Field experiments were conducted at the Department of Field Experiments of the Institute of Plant Protection—National Research Institute in Winna Góra, Poland (52°12′17″N, 17°26′48″E), during the years 2020–2021 (Table 1). The experiments were designed as a two-factor randomized block design each year. Different combinations of acaricides and treatment dates were treated as a single composite factor, while the two methods of chemical application—using a horizontal boom sprayer (traditional method) versus a Fragaria boom equipped with 3‑nozzle curved spray lances designed for strawberry spraying (Renal, Poland)—constituted the second factor. The traditional spraying technique involves full coverage with no gaps, ensuring that an even number of plant rows align with the entire sprayer boom. This method guarantees uniform application of the pesticide across the entire plantation surface during successive passes of the sprayer. For the commonly used beet row spacing of 45 cm, this uniformity is achieved with field booms of working widths of 18 m and 36 m, and less commonly in agricultural practice, booms with a width of 13.5 m.
Table 1
Weather conditions during the 2020–2021 growing season in Winna Góra (Field Experiment Station), Poland
Years
2020
2021
Month
Decade
Temp.[°C]
Precipitation [mm]*
Relative humidity [%]
Temp.[°C]
Precipitation [mm]*
Relative humidity [%]
April
III
12.06
0.6
59.0
7.52
2.6
66.10
May
I
12.03
5.9
71.0
9.9
45.5
74.3
II
10.80
0.4
69.6
15.68
5.7
72.3
III
12.82
1.2
69.1
12.94
9.7
74.09
June
I
15.71
0.7
72.0
18.98
1.6
61.0
II
19.83
0.1
77.2
21.49
6.9
62.4
III
19.18
23.6
84.9
21.41
8.1
71.5
July
I
15.56
25.4
72.0
20.35
17.1
76.8
II
18.39
14.3
71.5
21.95
2.5
76.7
III
19.59
2.2
64.82
21.49
0
66.45
August
I
21.38
38.5
70.30
17.94
23.1
75.7
II
21.59
1.6
62.70
19.32
6.3
70.6
III
18.29
9.0
74.64
15.64
1.0
85.09
September
I
15.59
11.2
78.89
16.43
0.4
76.9
II
16.47
0
73.20
16.05
3.8
81.01
III
15.29
12.9
78.70
15.01
7.1
71.1
*Precipitation total for the decade
Six experimental variants were tested: five acaricide treatments and one control (no chemical pest management) (Table 2). The experiment included four replicates per treatment, resulting in a total of 24 plots (Fig. 1). Acaricides targeting the two-spotted spider mite Tetranychus urticae (TSSM) were applied after determining the optimal timing for pesticide application and when pest pressure reached the economic injury level. Chemical treatments in sugar beet should be conducted from the phase of complete inter-row coverage until the end of root growth (BBCH 39–49), while considering a waiting period of 28 days before harvest. In this experiment, chemical treatments were applied when pest density reached the economic threshold, defined as 10 mobile mite specimens per sugar beet leaf.
Table 2
Insecticide/acaricide treatment against Tetranychus urticae and criteria used for application.
Insecticide/acaricide
Variant
Active ingredients
Criterium for application
Mite stage
Dose (ha−1)
Envidor 240 SC
(E)
Spirodiclofen—240 g—22.11%
Feeding symptoms
Moving stages
and eggs
0.4 l
Nissorun Strong 250 EC + Ortus 05 SC
(NO)
Heksytiazoks—250 g—23.15%
Feeding symptoms
Egg stage
0.4 l
Fenpiroksymat—51.2 g—5.02%
Moving stages
1.5 l
Ortus 05 SC
(O)
Fenpiroksymat—51.2 g—5.02%
Feeding symptoms
Moving stages
1.5 l
Treol 770 EC
(T)
Paraffin oil—770 g l−1 (89.6%) acaricide
Feeding symptoms
Moving stages
1.5 l/100 l
Vertigo 018 EC
(V)
Abamectine—18 g—1.88%
Feeding symptoms
Moving stages
0.75 l
Control
C
No pesticide
–
–
–
Fig. 1
Scheme of the experimental design. A total of 24 plots were treatment, each plot has four replications and five acaricides per treatment (n = 5 plots per treatment) and one control. Two treatment techniques were used: the traditional method with a horizontal lance and the 3‑nozzle curved lance
Each plot consisted of six rows, with an individual plot area of 13.5 m2 (width = 1.8 m, length = 7.5 m). Sowing was conducted using a precision seeder. The average number of plants per plot was 115, with a planting distance of 24.0 cm between plants and 45.0 cm between rows. The average final plant density ranged from 86 to 90 sugar beet plants per plot. The total experimental area encompassed approximately 350 m2.
The soil in the experimental plots had a neutral pH, with moderate phosphorus (P) content and high levels of potassium (K) and magnesium (Mg). In both years of the study, winter wheat served as the forecrop for the sugar beets. The plots were fertilized with nitrogen at a rate of 120 kg N ha−1. Nitrogen was applied in two stages: 60 kg N ha−1 was administered before sowing, and an additional 60 kg N ha−1 was applied when the sugar beets reached the BBCH 14 developmental stage. One week prior to sowing, the soil was fertilized with 60 kg P2O5 ha−1 of phosphorus, in combination with potassium. Weed and disease management were conducted in accordance with the plant protection guidelines recommended by the Plant Protection Institute—NRI (Poland).
The sugar beet variety Marynia was utilized in the field experiment. The seeds were treated with the fungicide Tachigaren 70 WP, which contains hymexazol as the active ingredient (a.i.) at a concentration of 700 g kg−1 (70%), applied at a rate of 40 g per unit of seeds per hectare. Sowing occurred annually between April 1st and 10th, with a seeding density of 1.02 units per hectare.
Data Collection
Sugar beets were harvested annually during the second ten days of October. At the time of harvest, plants from the three central rows were manually topped, and the leaves were subsequently weighed. The roots were counted, extracted from the soil, and weighed according to the PN-R-74452 standard. Roots were manually collected from six rows, covering an area of 10.8 m2, with the three central rows of each plot being harvested. Both qualitative and quantitative analyses were conducted on 20 sugar beet roots. These analyses were performed at the Plant Breeding Station of the Kutno Sugar Beet Farm in Śmiłów, with further evaluations conducted in Straszków (Kutno Sugar Beet Farm in Kutno, Kłodawa) using an automated Venema processing line (Hassan and Mostafa 2018). Sugar content was measured using polarimetry (ICUMSA 2024), α‑amino nitrogen was quantified using a fluorometric technique (Burba and Georgi 1976), and potassium (K) and sodium (Na) contents were determined using a photoelectric method (ICUMSA 2024). The molasses content was expressed in milliequivalents per 1000 g of pulp. The white sugar yield (technological yield) was calculated using the formula proposed by Buchholz et al. (1995). The following parameters were analyzed: plant density (PD), sugar beet yield (SBY), biological sugar yield (BSY), pure sugar yield (PSY), sugar content (SC), refined sugar content (RSC), yield of preferential sugar (YPS), recoverable sugar (RS), potassium molasses (PM), sodium molasses (SM), α‑amino nitrogen (α-AN), alkalinity factor (AF), and standard molasses loss (SML).
Statistical Analysis
The normality of the distribution for all 13 observed traits was verified using the Shapiro-Wilk test (Shapiro and Wilk 1965). A three-way multivariate analysis of variance (MANOVA) was conducted to assess the effects of year, method, and chemical control. This was followed by a three-way analysis of variance (ANOVA) to determine the individual and interaction effects of year, method, chemical control, and their interactions (year × method, year × chemical control, method × chemical control, and year × method × chemical control) on the variation in all 13 traits. Mean values and standard deviations were calculated for each trait, and Fisher’s Least Significant Differences (LSDs) were computed to identify homogeneous groups. The relationships among the 13 traits were evaluated using Pearson’s linear correlation coefficients, which were visually represented in heatmaps. Additionally, multidimensional statistical methods were employed. Canonical variate analysis (CVA) was utilized to present a multi-trait assessment of similarity between the combinations of spraying methods and chemical controls across different years in a reduced dimensional space with minimal information loss. Mahalanobis distance was used as a measure of similarity between the combinations of “multi-trait” methods, chemical controls, and years (Bocianowski and Liersch 2022), with its significance verified using the critical value Dα, known as the “least significant distance” (Mahalanobis 1936). Mahalanobis distances were calculated for all combinations of years, methods, and chemical controls. Data processing was performed using the statistical software package Genstat v. 23.1 (VSN International Genstat 2023).
Results
The empirical distributions of all observed characteristics followed a normal distribution. Statistics of MANOVA revealed that years (λ = 0.0328; F13;60 = 136.04; p < 0.0001), methods (λ = 0.6544; F13;60 = 2.44; p = 0.01), year × method interaction (λ = 0.536; F13;60 = 4.00; p < 0.0001) and year × chemical control interaction effect (λ = 0.2747; F65;287 = 1.39; p = 0.036) were significantly different for all 13 traits. Chemical control (λ = 0.317; F65; 287 = 1.22; p = 0.142), method × chemical control interaction (λ = 0.3645; F65;287 = 1.05; p = 0.379) and years × method × chemical control interaction (λ = 0.323; F65;287 = 1.19; p = 0.166) did not differ significantly for all 13 traits. Analysis of variance revealed that the main effects of the year were significant for all investigated parameters, except for AF (Table 2). The main effects of the method were significant for SBY and BSY, but the main effects of chemical control were not significant for all 13 observed traits. The year × method interaction was significant for PD, SBY, YPS, RS, α‑AN and SML, while the year × chemical control interaction was significant for PD, SC, RSC and YPS (Table 3).
Table 3
F-statistics from two-way analysis of variance (ANOVA) of observed traits.
Source of variation
Year (Y)
Method (M)
Chemical control (Cc)
Y × M
Y × Cc
M × Cc
Y × M × Cc
The number of degrees of freedom
1
1
5
1
5
5
5
Plant density, PD
57.88***
3.88
1.81
10.31**
3.04*
0.71
2.24
Sugar beet yield, SBY
9.93**
5.76*
2.26
5.46*
1.05
1.07
0.18
Biological sugar yield, BSY
88.75***
4.31*
1.63
3.83
0.79
1.27
0.44
Pure sugar yield, PSY
103.11***
3.88
1.68
2.98
0.76
1.33
0.46
Sugar content, SC
1517.58***
0.1
0.61
0.3
3.08*
2.3
1.27
Refined sugar content, RSC
1400.82***
0
0.63
0.16
4.06**
2.09
0.9
Yield of preferential sugar, YPS
189.16***
1.03
1.11
6.86*
2.97*
0.49
0.47
Recoverable sugar, RS
5.66*
0.65
0.74
9.41**
1.09
0.34
0.88
Potassium molasses, PM
12.04***
3.33
0.38
1.99
0.28
0.54
0.88
Sodium molasses, SM
53.52***
0.05
0.47
0.47
0.22
0.66
1.44
α–amino nitrogen, α–ΑΝ
5.65*
0.06
0.73
10.36**
1.04
0.27
0.7
Alkalinity factor, AF
1.06
1.81
0.48
2.26
0.41
0.02
0.68
Standard molasses loss, SML
9.19**
0.49
0.51
10.58**
1.06
0.62
0.73
* p < 0.05, ** p < 0.01, *** p < 0.001
Statistically significant high mean values of all investigated traits (except MS and AF) were observed in 2021 (Table 4). The mean sodium molasses was 6621 in 2020, which was significantly higher than 5344 in 2021 (Table 4). The mean sugar beet yield for the traditional spraying method was higher (66.54 t ha−1) than that obtained for the variant with 3‑nozzle curved spray lances (61.54 t ha−1) (Fig. 2). The mean biological sugar yield for the traditional sprayer boom (11.46 t ha−1) was higher than for the 3‑nozzle curved spray lance (10.67 t ha−1) (Fig. 3).
Table 4
Mean values and standard deviations (SD) for observed traits in particular years of study.
Trait
Year
LSD0.05
2020
2021
Plant density, PD
74,000b ± 9239
85,750a ± 8196
3078.9
Sugar beet yield, SBY
60.75b ± 8.76
67.33a ± 12.62
4.16
Biological sugar yield, BSY
9.25b ± 1.364
12.88a ± 2.4
0.767
Pure sugar yield, PSY
7.794b ± 1.136
11.215a ± 2.123
0.672
Sugar content, SC
15.23b ± 0.5313
19.1a ± 0.5154
0.198
Refined sugar content, RSC
12.84b ± 0.5511
16.63a ± 0.5265
0.2022
Yield of preferential sugar, YPS
81.3b ± 1.799
85.14a ± 0.98
0.557
Recoverable sugar, RS
2.395b ± 0.1777
2.469a ± 0.1274
0.0618
Potassium molasses, PM
46.91b ± 5.178
51.14a ± 6.299
2.429
Sodium molasses, SM
6.621a ± 0.7024
5.344b ± 0.9237
0.3481
α–amino nitrogen, α–ΑΝ
28.02b ± 5.661
30.38a ± 4.053
1.982
Alkalinity factor, AF
1.967a ± 0.364
1.891a ± 0.3217
0.1478
Standard molasses loss, SML
0.1363b ± 0.01777
0.1455a ± 0.01203
0.00606
a, b—in row, means followed by the same letters are not significantly different, based on Fisher’s least significant differences
Fig. 2
Mean values of sugar beet yield for analyzed methods. LSD0.05 = 4.16
Mean values and standard deviations (SD) for traits with a significant year × method and year × chemical control interaction are presented in Tables 5 and 6, respectively.
Table 5
Mean values and standard deviations (SD) for traits with statistically significant year × method interaction.
Year
2020
2021
Method
Mean
SD
Mean
SD
Plant density [pcs ha−1]
Traditional
70000
7337
86708
7310
3‑nozzle curved lance
78000
9339
84792
9050
LSD0.05 for year × method interaction: 4354.2
Sugar beet yield [t ha−1]
Traditional
65.69
7.66
67.4
11.13
3‑nozzle curved lance
55.81
6.869
67.26
14.19
LSD0.05 for year × method interaction: 5.88
Yield of preferential sugar [t ha−1]
Traditional
80.79
2.164
85.36
1.09
3‑nozzle curved lance
81.8
1.179
84.92
0.818
LSD0.05 for year × method interaction: 0.788
Recoverable sugar [%]
Traditional
2.455
0.2171
2.434
0.1322
3‑nozzle curved lance
2.335
0.0993
2.504
0.1145
LSD0.05 for year × method interaction: 0.0874
α‑amino nitrogen
Traditional
29.5
6.91
28.66
3.146
3‑nozzle arc lance
26.54
3.632
32.1
4.181
LSD0.05 for year × method interaction: 2.802
Standard molasses loss [mmol (100 g)−1]
Traditional
0.1423
0.02171
0.1416
0.01197
3‑nozzle curved lance
0.1303
0.00993
0.1494
0.011
LSD0.05 for year × method interaction: 0.0086
Table 6
Mean values and standard deviations (SD) for traits with statistically significant year × chemical control interaction.
Year
Chemical control
C
E
NO
O
T
V
Mean
SD
Mean
SD
Mean
SD
Mean
SD
Mean
SD
Mean
SD
Plant density [plants ha−1]
2020
73250
8102
81125
6402
72250
6882
80125
6643
66875
3758
70375
13522
2021
85125
8202
87375
9149
85625
9102
82750
9588
88125
4518
85500
9196
LSD0.05 for year × chemical control interaction: 7541.6
Sugar content [%]
2020
15.07
0.4034
15.54
0.6155
15.58
0.7363
15.07
0.4055
15.12
0.4757
15.02
0.2228
2021
19.26
0.3719
18.85
0.4188
19.02
0.5577
19.23
0.455
18.9
0.6195
19.36
0.561
LSD0.05 for year × chemical control interaction: 0.4851
Refined sugar content
2020
12.61
0.4873
13.21
0.6288
13.25
0.6091
12.64
0.3934
12.76
0.4989
12.57
0.2868
2021
16.78
0.3468
16.35
0.4516
16.55
0.5702
16.72
0.4296
16.47
0.6292
16.95
0.5944
LSD0.05 for year × chemical control interaction: 0.4953
Yield of preferential sugar [t ha−1]
2020
80.39
2.085
82.34
1.11
82.41
0.483
80.77
2.512
81.44
1.109
80.43
1.892
2021
85.21
0.543
84.68
1.318
85.01
0.73
84.98
1.107
85.24
0.817
85.71
1.14
LSD0.05 for year × chemical control interaction: 1.365
Table 7 presents the correlation coefficients for all pairs of the 13 observed traits. Positive correlations were found for the following pairs of traits: PD-BSY, PD-PSY, PD-SC, PD-RSC, PD-YPS, SBY-BSY, SBY-PSY, SBY-SC, SBY-RSC, BSY-PSY, BSY-SC, BSY-RSC, BSY-YPS, BSY-α-AN, BSY-SML, PSY-SC, PSY-RSC, PSY-YPS, PSY-SML, SC-RSC, SC-YPS, SC-RS, SC-PM, SC-α-AN, SC-SML, RSC-YPS, RSC-PM, RSC-SML, RS-PM, RS-α-AN, RS-SML, PM-α-AN, PM-AF, PM-SML and α‑AN-SML (Fig. 4; Table 6). Significant negative correlations were found between the following pairs of traits: SM-PD, SM-BSY, SM-PSY, SM-SC, SM-RSC, YPS-RS, YPS-SM, YPS-α-AN, YPS-SML, PM-SM, AF-RS, AF-α-AN, and AF-SML (Fig. 4; Table 7).
Table 7
The correlation matrix for the 13 observed traits.
Trait
PD
SBY
BSY
PSY
SC
RSC
YPS
RS
PM
SM
α‑AN
AF
SBY
0.18
–
–
–
–
–
–
–
–
–
–
–
BSY
0.43***
0.88***
–
–
–
–
–
–
–
–
–
–
PSY
0.45***
0.86***
0.99***
–
–
–
–
–
–
–
–
–
SC
0.51***
0.28**
0.69***
0.72***
–
–
–
–
–
–
–
–
RSC
0.52***
0.27**
0.69***
0.72***
0.99***
–
–
–
–
–
–
–
YPS
0.52***
0.20
0.56***
0.61***
0.83***
0.87***
–
–
–
–
–
–
RS
−0.03
0.10
0.16
0.14
0.24*
0.16
−0.33***
–
–
–
–
–
PM
−0.02
0.04
0.18
0.16
0.35***
0.30**
−0.03
0.69***
–
–
–
–
SM
−0.27**
0.06
−0.26**
−0.28**
−0.64***
−0.64***
−0.54***
−0.17
−0.35***
–
–
–
α‑AN
0.04
0.15
0.22*
0.19
0.24*
0.17
−0.27**
0.87***
0.33**
−0.1
–
–
AF
−0.08
−0.09
−0.13
−0.12
−0.10
−0.07
0.15
−0.42***
0.28**
0.07
−0.77***
–
SML
0.01
0.14
0.23*
0.20*
0.30**
0.22*
−0.26**
0.97***
0.69***
−0.2
0.91***
−0.45***
PD plant density, SBY sugar beet yield, BSY biological sugar yield, PSY pure sugar yield, SC sugar content, RSC refined sugar content, YPS yield of preferential sugar, RS recoverable sugar, PM potassium molasses, SM sodium molasses, α-AN α-amino nitrogen, AF alkalinity factor, SML standard molasses loss
* p < 0.05, ** p < 0.01, *** p < 0.001
Fig. 4
Heatmaps for linear Pearson’s correlation coefficients between the 13 observed traits (rcr = 0.20). The heatmap provides a graphical representation of a correlation matrix between pairs of the observed traits. Each element of the correlation matrix is represented by a shaded rectangle indicating the value at that location, using a different colour or shading density. PD plant density, SBY sugar beet yield, BSY biological sugar yield, PSY pure sugar yield, SC sugar content, RSC refined sugar content, YPS yield of preferential sugar, RS recoverable sugar, PM potassium molasses, SM sodium molasses, α‑AN α-amino nitrogen, AF alkalinity factor, SML standard molasses loss
Individual traits had different significance and contributed differently to the joint multi-trait variation of the investigated combinations of years, methods and chemical controls. The analysis of the first two canonical variables for 24 combinations of 13 quantitative traits is presented in Fig. 5. In the graph, the coordinates of the point for a given combination are the values for the first and second canonical variables, respectively. The first two canonical variables explained 89.08% of the total variation between individual combinations (Fig. 5). The most significant positive, linear relationship with the first canonical variable was found for PD, SBY, BSY, PSY, SC, RSC, YPS, PM and SML, and a negative relationship for SM. The second canonical variable was significantly positively correlated with PD and negatively correlated with: SBY, BSY, RS, PM, α‑AN, and SML. The greatest variation in terms of all 13 traits measured jointly with Mahalanobis distances was found for V in 2020 for spraying with a traditional boom and V in 2021 for spraying with a traditional boom (the distance between them was 12.82). The greatest similarity was found between O in 2021 for the traditional method of spraying and V in 2021 for spraying with the 3‑nozzle curved lance (0.90) (Table 8).
Fig. 5
Distribution of 24 combinations of years, methods and chemical controls in the space of the first two canonical variables
Mahalanobis distances between combinations of methods, chemical controls and years.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
Traditional
2020
NO
1
0.00
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
C
2
4.59
0.00
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
V
3
4.29
2.46
0.00
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
E
4
2.36
3.98
4.26
0.00
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
O
5
3.42
3.03
3.41
2.34
0.00
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
T
6
3.18
3.47
2.55
2.32
2.42
0.00
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
2021
NO
7
8.06
10.72
10.84
9.23
10.00
10.34
0.00
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
C
8
8.38
10.95
11.16
9.56
10.32
10.73
1.76
0.00
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
V
9
10.17
12.55
12.82
11.28
11.85
12.47
3.88
3.74
0.00
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
E
10
8.08
10.82
11.02
9.31
10.10
10.51
2.86
2.38
5.28
0.00
–
–
–
–
–
–
–
–
–
–
–
–
–
–
O
11
7.57
10.26
10.42
8.64
9.51
9.81
1.51
1.63
4.68
2.56
0.00
–
–
–
–
–
–
–
–
–
–
–
–
–
T
12
7.30
9.85
10.09
8.50
9.30
9.67
2.60
1.94
3.99
2.96
2.05
0.00
–
–
–
–
–
–
–
–
–
–
–
–
3‑nozzle lance
2020
NO
13
2.96
5.33
5.40
1.83
3.23
3.34
9.86
10.16
11.74
9.84
9.34
9.20
0.00
–
–
–
–
–
–
–
–
–
–
–
C
14
2.93
3.87
3.83
1.56
1.51
2.03
9.88
10.17
11.77
9.89
9.33
9.11
2.23
0.00
–
–
–
–
–
–
–
–
–
–
V
15
3.12
4.79
5.00
1.83
2.46
3.13
9.88
10.10
11.64
9.77
9.31
9.06
1.50
1.34
0.00
–
–
–
–
–
–
–
–
–
E
16
3.02
6.04
6.27
2.56
3.89
4.42
7.94
8.31
10.01
7.93
7.34
7.37
2.64
3.09
2.61
0.00
–
–
–
–
–
–
–
–
O
17
3.80
5.84
6.12
2.38
3.33
4.03
9.81
10.11
11.62
9.74
9.24
9.16
1.61
2.37
1.43
2.09
0.00
–
–
–
–
–
–
–
T
18
2.43
3.42
3.36
2.03
2.58
2.20
10.08
10.37
11.98
10.16
9.62
9.31
2.48
2.32
2.74
4.16
3.71
0.00
–
–
–
–
–
–
2021
NO
19
7.84
10.44
10.76
9.04
9.82
10.29
2.29
1.59
4.32
2.18
1.67
1.49
9.70
9.66
9.56
7.72
9.58
9.93
0.00
–
–
–
–
–
C
20
8.12
10.75
10.95
9.31
10.08
10.46
1.54
1.42
4.51
2.27
1.05
2.23
9.99
9.97
9.94
8.02
9.91
10.19
1.37
0.00
–
–
–
–
V
21
7.60
10.39
10.47
8.76
9.58
9.87
1.34
1.62
4.59
2.74
0.90
2.42
9.36
9.42
9.41
7.47
9.33
9.63
2.16
1.25
0.00
–
–
–
E
22
7.31
9.94
10.12
8.42
9.26
9.52
2.18
2.61
5.46
2.84
1.32
2.65
9.20
9.15
9.18
7.22
9.13
9.38
2.11
1.41
1.70
0.00
–
–
O
23
8.25
10.67
10.93
9.61
10.21
10.66
2.79
2.39
4.75
2.95
2.78
2.92
10.25
10.26
10.24
8.63
10.35
10.19
2.50
2.05
2.55
2.59
0.00
–
T
24
10.02
12.18
12.55
11.21
11.78
12.32
5.21
5.68
4.30
6.02
6.05
5.42
11.77
11.74
11.63
10.21
11.74
11.80
5.38
5.72
6.20
6.07
5.50
0.00
Discussion
Acaricides for controlling the two-spotted spider mite (TSSM) are widely regarded as an effective method for rapidly eliminating a significant number of pests and halting their reproduction (Abou Jawdah et al. 2024; Zhang et al. 2023). In field plantations, systemic pesticides are typically applied once or twice per growing season to inhibit the development and reproduction of these pests (Sánchez-Bayo 2021). While chemical acaricides have historically been popular and somewhat effective for spider mite control, their use is associated with several drawbacks (Simma et al. 2020). These include adverse environmental impacts and the risk of contaminating food, particularly fresh fruits and vegetables. Furthermore, the continuous use of synthetic acaricides has led to the development of resistant spider mite strains (Adesanya et al. 2021). Spider mites have developed resistance to many commonly used acaricides, including organophosphates, pyrethroids, carbazinates, quinolines, carbamates, tetrazines, diphenyloxazolines, quinazolines, phenoxypyrazoles, thiazolidines, macrocyclic lactones, pyridazones, and pyrazole derivatives. In Poland, the range of acaricides approved for use in sugar beet cultivation is notably limited. Only one product, Ortus 05 SC, is registered for this purpose. However, Ortus 05 SC is a contact acaricide that targets adult spider mites but is ineffective against their eggs. For optimal efficacy, this acaricide must directly cover the body of the pest, which poses a challenge in practice, as the protective silk webbing created by the mites and the dense canopy formed by overlapping beet leaves hinder thorough coverage. The effectiveness of pest control, therefore, largely depends on the technical aspects of the application. According to the manufacturer’s recommendations, both the water volume (400 L ha−1) and the product dose (1.5–1.8 L ha−1) should not be reduced, as doing so would compromise the success of the treatment. These practices align with the EU strategy and the Integrated Pest Management (IPM) Directive. In our study, we employed products that are registered for controlling spider mites in orchards and ornamental plants but are not approved for use in field crops, specifically sugar beets.
The most critical factor in effective pest control is the proper adjustment of the sprayer (Hanif et al. 2022). It is essential to select the appropriate fan output and travel speed to ensure that the working solution adequately covers all parts of the plants while minimizing off-site drift beyond the sugar beet rows (Niu et al. 2020). Drift of droplets to adjacent inter-rows does not contribute to the efficacy of the chemical treatment (Zheng and Xu 2023). Additionally, the volume of the applied working solution plays a significant role. Spider mites are small pests that migrate across the uneven surfaces of beet leaves, and since most acaricides are contact-based, it is crucial to maximize the coverage of the leaf surface. Ensuring that droplets reach and cover difficult-to-access niches between the leaves, where spider mites often reside, is vital for effective control (Dara et al. 2018). To achieve this, it is recommended to use high volumes of working solution per hectare when targeting spider mites. Incorporating a full dose of a specialized adjuvant, such as a wetting agent, into the working solution is also advisable. Wetting agents reduce the surface tension of the water-based solution on the sprayed plants, thanks to their hydrophilic-lipophilic properties, which provide an affinity for both water and fats (Chen et al. 2022). These agents lower the spray water pressure, improve droplet adhesion, and enhance the wettability of the sprayed surfaces. These characteristics significantly increase the biological activity of the plant protection product, thereby improving the effectiveness of pest control (Miziniak et al. 2017).
Another valuable class of additives includes behavior-modifying biochemicals (BMBs). These substances contain pest alarm pheromones that increase the mobility of spider mites, thereby enhancing their exposure to the applied pesticide (Bartlett et al. 1988). In practice, BMBs significantly improve the efficacy of pest control treatments. Research by Maciesiak and Olszak (2006) demonstrated that a substantially reduced dose of acaricide, when combined with a BMB, achieved the same level of effectiveness as a full dose of acaricide used alone, without the addition of BMBs.
Climatic conditions during the two experimental years strongly influenced treatment outcomes. In 2020, irregular rainfall patterns, episodes of drought, and lower relative humidity created unfavorable conditions for sugar beet growth while favoring spider mite development, resulting in reduced yields and sugar content. In contrast, 2021 was characterized by more stable precipitation, higher temperatures, and greater relative humidity, which together supported improved plant growth and sugar accumulation while partially limiting mite population pressure. These environmental differences explain the significant year effects observed in nearly all measured parameters and highlight that weather variability was a stronger driver of yield and quality than acaricide treatment alone (Table 1).
The year effect was significant for almost all traits (MANOVA, ANOVA)—except the alkalinity factor (AF). Better climatic conditions in 2021 explain why yields, sugar content, and technological quality were higher across treatments, while spider mite pressure may have been mitigated by higher humidity. In 2020, drought spells plus lower humidity created stress that both reduced yields and made plants more vulnerable to mites, highlighting why acaricide effects seemed less pronounced than the climatic influence.
The effectiveness of treatment also significantly depends on the spraying method employed. In our experiment, we utilized two approaches: the traditional horizontal boom sprayer and the Fragaria boom equipped with 3‑nozzle curved spray lances designed specifically for spraying strawberries (Renal, Poland). The RENAL FRAGARIA boom is distinguished by its ability to deliver uniform, three-directional spraying, covering the top and both sides of the plant. This method is particularly effective in controlling a variety of strawberry diseases and molds, as it ensures thorough penetration of the spray into the interior of the bushes, thereby enhancing the efficacy of the applied agents and improving yield by preventing disease. The standard Fragaria boom is configured to spray eight rows simultaneously, with adjustable row spacing. Each guide with side nozzles is spring-loaded, ensuring that the spray consistently reaches inside the bushes. Additionally, the boom is equipped with a hydraulic vertical lift, and the maximum spacing between the guides with nozzles is 78 cm, with the option to extend coverage by 2 or 4 additional rows. We adapted this strawberry spraying system for use in sugar beet cultivation, applying it between the rows to combat spider mites. The innovative nozzle arrangement allows the working solution to precisely reach the interior of the plants, targeting the areas where mites are most concentrated and causing the greatest damage.
The results presented in this paper do not definitively demonstrate the superiority of either method for controlling spider mites. Technological yield of sugar beet was achieved in both years of the study using the horizontal boom sprayer (traditional method) (Table 5). The biological sugar yield was, on average, higher in 2020 when the Fragaria boom was employed, whereas in 2021, the horizontal boom sprayer yielded better results (Table 5). The recoverable sugar index was higher for plots treated with the traditional method in 2020, while in 2021, plots sprayed using the Fragaria boom showed a higher recoverable sugar index (Table 5).
Conclusions
1.
The application of acaricides significantly improved sugar beet yield and technological quality parameters compared with untreated control plots.
2.
Significant differences between years were observed for most traits, confirming the strong influence of environmental conditions on crop performance and treatment efficacy.
3.
The traditional horizontal boom sprayer generally provided higher root and biological sugar yields, although the effectiveness of both spraying methods depended on seasonal conditions.
4.
Differences among individual acaricide treatments were less pronounced, but overall results confirmed the effectiveness of chemical control against Tetranychus urticae in sugar beet.
5.
In practice, spider mite management should be based on regular monitoring, timely treatment decisions, appropriate selection and rotation of active ingredients, the use of adjuvants, and careful choice of spraying technique to ensure coverage of both leaf surfaces.
Conflict of interest
M. Jakubowska, J. Bocianowski and D. Zawada declare that they have no competing interests.
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