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Review

Benefits of Insect Pollination in Brassicaceae: A Meta-Analysis of Self-Compatible and Self-Incompatible Crop Species

by
Francisco Rubén Badenes-Pérez
Instituto de Ciencias Agrarias, Consejo Superior de Investigaciones Científicas, 28006 Madrid, Spain
Agriculture 2022, 12(4), 446; https://doi.org/10.3390/agriculture12040446
Submission received: 2 February 2022 / Revised: 16 March 2022 / Accepted: 19 March 2022 / Published: 23 March 2022
(This article belongs to the Topic Insects in Sustainable Agroecosystems)

Abstract

:
This paper reviewed the effects of insect pollination on the yield parameters of plants from the family Brassicaceae presenting different breeding systems. Meta-analysis indicates that in both self-compatible and self-incompatible crop species, meta-analysis indicates that seed yield (Y), silique set (SQS), number of siliquae/plant (NSQ), and the number of seeds/silique (NSSQ) increase when plants are insect-pollinated compared to when there is no insect pollination. The weight of seeds (WS), however, increased in self-incompatible species but not in self-compatible ones as a result of insect pollination. Overall, the percentage of studies showing a positive effect of insect pollination on yield parameters was higher in self-incompatible than in self-compatible species. It was shown that the ability of self-compatible species to reproduce does not fully compensate for the loss of yield benefits in the absence of insect pollination. Cultivated Brassicaceae attract a wide variety of pollinators, with honeybees (Apis spp.) such as A. mellifera L., A. cerana F., A. dorsata F., and A. florea F. (Hymenoptera: Apidae); other Apidae, such as bumblebees (Bombus spp.) (Hymenoptera: Apidae); mining bees (Hymenoptera: Andrenidae); sweat bees (Hymenoptera: Halictidae); and hoverflies (Diptera: Syrphidae) constituting the most common ones. The benefits of insect pollination imply that pollinator conservation programs play a key role in maximizing yield in cruciferous crops.

1. Introduction

Pollinators are essential in food production and plant biodiversity conservation [1,2,3]. More than 78% of angiosperm species are pollinator-dependent [4]. This obligatory and facultative cross-pollination makes insect pollination essential, or at least a positive factor, in maximizing fertilization. Brassicaceae, as most angiosperms, are xenogamous and either require cross-pollination or can be facultatively cross-pollinated [5,6,7,8]. With a few exceptions, flowers in the family Brassicaceae have four sepals, four petals diagonally disposed as a cruciform corolla, two carpels, and six stamens arranged in a tetradynamous pattern (four longer inner ones and two shorter outer ones) [9,10,11]. Except for one species in the genus Lepidium [12], plants in the family Brassicaceae have hermaphrodite flowers [13].
Plants in the family Brassicaceae attract a broad diversity of pollinators, including honeybees such as Apis mellifera L. (Hymenoptera: Apidae), solitary bees, such as Andrena spp. (Hymenoptera: Andrenidae), and hoverflies, such as Eristalis tenax L. (Diptera: Syrphidae) [8,14,15]. The family Brassicaceae includes many economically important species, some of which are widely used as vegetables, oils, condiments, or ornamental plants [16,17]. For example, oilseed rape Brassica napus L. subsp. napus, which is one of the most cultivated oilseed Brassicaceae, has seen the price of its seeds rise by more than 30% in the last three years [18]. To increase crop yield and gross margins in B. napus, bee pollination can be more beneficial than pesticide applications [19]. In Ireland, the benefit of insect pollination to B. napus yield has been estimated at EUR 3.9 million per year [20]. In Brazil, the benefit of honeybees to B. napus yield is above USD 8 million [21]. The potential benefit of pollination is most important in cruciferous crops in which the harvest consists of seeds and fruits (i.e., siliquae). Among these are all oilseed Brassicaceae, the most important of which is rapeseed, also known as canola, B. napus [22]. Other cruciferous oilseed crops include field mustard Brassica rapa L. subsp. oleifera, synonymous with Brassica campestris; Indian mustard Brassica juncea (L.) Czern.; Ethiopian mustard Brassica carinata A. Braun; camelina Camelina sativa L. (Crantz); radish Raphanus sativus (L.) Domin; and white mustard Sinapis alba L. These oilseed crops can be used for oil, biofuel, and/or lubricant production [23,24,25,26,27,28,29,30]. The seeds of S. alba are used for mustard elaboration, and the siliquae of R. sativus can be used as a vegetable (Table 1). Yield parameters in the family Brassicacae are often measured by seed yield, but other yield parameters such as the number of siliquae/plant and seed oil content are also used [31,32,33].
A recent meta-analysis conducted with B. napus, a self-compatible species, showed that pollinator abundance is consistently important in predicting yield in this crop [34]. To date, no meta-analyses have been conducted to examine the effect of insect pollination in yield parameters across the broad spectrum of cruciferous crops, nor have there been meta-analyses examining the effects of insect pollination on yield parameters separately for self-compatible and self-incompatible species. Self-incompatible Brassicaceae species typically have larger flowers than self-compatible ones in order to attract pollinators, with a significantly reduced seed set in the absence of pollinating agents [35,36]. Given the evolutionary advantage of selfing as a reproductive assurance when there is a paucity of pollinators [37], insect pollination is likely to have more marked positive effects on yield parameters in self-incompatible Brassicaceae species than in self-compatible ones.
The purpose of this paper was to synthesize all the available literature regarding the effects of insect pollination on the main yield parameters of crops of the family Brassicaceae and to identify the main taxon groups of pollinators attracted to these crops. Furthermore, a meta-analysis was conducted in order to compare the effects of insect pollination on yield parameters in self-compatible and self-incompatible cruciferous crops. It was hypothesized that the effect of insect pollination on yield parameters will be more significant in self-incompatible species than in self-compatible ones.

2. Methods

The references included in this review were sourced from the Web of ScienceTM and Scopus databases. Additional publications on the topic were found in the social networking site for scientists and researchers ResearchGate. The species found were 10, including Brassssica oleracea L., B. carinata, B. juncea, B. napus, B. rapa, C. sativa, Eruca sativa Mill., R. sativus, S. alba, and Thlaspi arvense L. (Brassicaceae). Thlaspi arvense was, however, not included in the analysis because the only study available [38] did not include all the necessary statistical data for its inclusion. References were not limited by year of publication, with the exception of B. napus. In this crop, given the large amount of studies conducted, only studies published from the year 2000 onwards were included in the analysis. As an exception, one publication from 1986 [31] was used for B. napus because it also included studies on several crop species included in this review. The studies included in the meta-analysis were published between the years 1986 and 2019 and had been conducted in Brazil, Chile, Finland, Germany, India, Nepal, Pakistan, Serbia, and the UK. Studies on insect pollination and yield parameters from other countries were either unavailable or did not include the necessary statistical data. The latest retrieval date of the reviewed papers was January 2021. The corresponding authors of the 78 publications assessed for eligibility (Figure 1) were in some cases contacted by e-mail to ask for clarifications regarding the type of cultivars used and the statistical analysis presented. The yield parameters examined were: seed yield measured as seed weight (per plant, area, or open flower) (Y); unitary/group weight of seeds (WS, 1, 100, or 1000 seeds) (henceforth when mentioning seed weight alone, the reference will be to this unitary/group measurement of seed weight); number of seeds (per area, plant, or branch) (NSP); number of seeds (per either silique or open flower) (NSSQ); number of siliquae (per either plant or area) (NSQ); silique set (SQS); silique length (SQL); seed germination (G); and oil content (O). When one publication included research conducted with several cultivars, the study was considered as one, unless the cultivars had for some reason been studied separately (see publications listed in Table 2). Although there can be varying degrees of self-compatibility and self-incompatibility among the species and varieties of Brassicaceae, B. napus, B. juncea, B. carinata, C. sativa, and S. alba are considered mostly self-compatible [35,38,39,40,41], while B. oleracea, B. rapa, E. sativa, and R. sativus are considered mostly self-incompatible and thus require cross-pollination [31,35,41]. To identify the main taxon groups of pollinators attracted to crops of the family Brassicaceae, for each study found on the topic, the insect families named among the five top most abundant pollinators were selected for each crop species and country.
Table 1. Most common use and breeding system in the cultivated crops of the family Brassicaceae included in this study. In self-compatible plants, both outcrossing and selfing occurs, while in self-incompatible ones, the main breeding system is outcrossing.
Table 1. Most common use and breeding system in the cultivated crops of the family Brassicaceae included in this study. In self-compatible plants, both outcrossing and selfing occurs, while in self-incompatible ones, the main breeding system is outcrossing.
PlantMost Common NamesMost Common UseMain Breeding SystemReferences on Breeding System
Brassica carinata A. BraunEthiopian mustardLeaves, seeds for oilOutcrossing and selfing[35,40]
Brassica juncea (L.) Czern.Brown mustard, Indian mustardLeaves, seeds for oilOutcrossing and selfing[35,41]
Brassica napus L.Rapeseed, canolaSeeds for oilOutcrossing and selfing[35,39]
Brassica oleracea L.Cabbage, broccoli, cauliflowerLeaves, inflorescencesOutcrossing, self-incompatible[40]
Brassica rapa L.Turnip, field mustardLeaves, root, seeds for oilOutcrossing, self-incompatible[35,41]
Camelina sativa L. (Crantz)Camelina, German sesameSeeds for oil, leavesOutcrossing and selfing[35,38]
Eruca sativa Mill.Arugula, rucolaLeavesOutcrossing, self-incompatible[31]
Raphanus sativus (L.) Domin RadishRoots, seeds oilOutcrossing, self-incompatible[40]
Sinapis alba L.White mustardSeeds for table mustard, oilOutcrossing and selfing[35,41]

Meta-Analysis

A meta-analysis study was conducted with the main yield parameters reported in the literature separately for self-compatible and self-incompatible species. Since the family Brassicaceae includes both self-compatible and self-incompatible species [35], this allows the possibility of conducting separate meta-analyses for these two groups of crops. As some publications reported, several experiments comparing caged plants without insect pollination versus more than one insect pollination treatment, which were treated as separate studies. Therefore, some publications appeared in a meta-analysis more than once. For this reason, separate entries in the meta-analysis are not necessarily independent. In one of the publications included in the meta-analysis [42], which reported yield data for the lower, middle, and top part of the plant, the data used in the meta-analysis were only those from the middle part of the plant. A random effects model was fitted to the data. All statistical analyses and graphical displays were conducted using Jamovi version 1.6.23 [43]. Forest plots show standardized mean differences (95% confidence intervals, CI), square sizes representing the sample size of each study, and a diamond at the bottom indicating the overall effect size of the meta-analysis. Jamovi uses the R package “metafor”, estimating standardized mean differences by Hedges’ g [44,45]. The amount of heterogeneity was estimated using the restricted maximum-likelihood estimator, providing Cochran’s Q statistic (significant at p ≤ 0.05) and the I2 statistic (with values below 25%, between 25% and 50%, and above 75%, considered to indicate low, moderate, and high heterogeneity, respectively) [44,46]. Studies with a Cook’s distance larger than the median plus six times the interquartile range of the Cook’s distances were considered to be overly influential and were removed from the analysis the first time the meta-analysis was run. This happened in the meta-analyses conducted for seed yield in self-compatible and self-incompatible species (two studies removed in each case), the weights of seeds in self-incompatible species (two studies removed), silique set in self-compatible species (two studies removed), and number of seeds/silique in self-incompatible species (one study removed). Funnel plot asymmetry was used to measure differences in effects between smaller and larger studies, for example, because of publication bias [47], and this was assessed by means of the Begg and Mazumdar rank correlation test [48]. A PRISMA flow diagram [49] of the studies included in the meta-analysis is shown below (Figure 1).

3. Insect Pollination Effect on Yield Parameters in Cultivated Brassicaceae

Table 2 shows the crops for which the effect (increase, decrease, non-significant) of insect pollination on seed yield parameters was studied in the family Brassicaceae (reports from at least seven studies). Of these yield parameters, NSP, SQL, G, and O were subsequently not included in the meta-analysis because, for each of them, there were less than seven publications that reported the statistical parameters necessary to conduct the meta-analysis. Other yield parameters reported in a lesser number of studies (six or fewer studies) included seed weight/plant dry weight, seed weight/silique, number of seeds/plant dry weight, number of siliquae/raceme, silique mass, seed vigor, seed size, percentage of healthy seeds, percentage of filled seeds, oil yield (mg/silique), protein content, flowers/plant, flower abscission, racemes/plant, plant weight and plant dry weight, aboveground biomass, yield/biomass ratio, harvest index (seed weight/aboveground biomass), plant height, and market value (Tables S1–S6).
Table 2. Publications were consulted in this review for the main yield parameters (a total of seven or more studies found) which were: seed yield measured as seed weight/(plant, area, or open flower) (Y); weight of seeds (1, 100, or 1000 seeds) (WS); number of siliquae/(plant or area) (NSQ); number of seeds/(silique or open flower) (NSSQ); silique set (SQS); silique length (SQL); number of seeds/(area, plant, or branch) (NSP); seed germination (G); and oil content of seeds (O). An increase, decrease, or neutral effect of insect pollination on yield parameters is shown in red, blue, or green, respectively. Studies included in the meta-analysis for at least one yield parameter are marked with two asterisks (**) in the Note column.
Table 2. Publications were consulted in this review for the main yield parameters (a total of seven or more studies found) which were: seed yield measured as seed weight/(plant, area, or open flower) (Y); weight of seeds (1, 100, or 1000 seeds) (WS); number of siliquae/(plant or area) (NSQ); number of seeds/(silique or open flower) (NSSQ); silique set (SQS); silique length (SQL); number of seeds/(area, plant, or branch) (NSP); seed germination (G); and oil content of seeds (O). An increase, decrease, or neutral effect of insect pollination on yield parameters is shown in red, blue, or green, respectively. Studies included in the meta-analysis for at least one yield parameter are marked with two asterisks (**) in the Note column.
Plant SpeciesYield ParameterReferencesNote
YWSSQSNSQNSSQSQLNSPGO
B. carinata [31]**
[50]
B. juncea [31]**
[42]**
[51]
[52]
[53]**
[54]
[55]**
[56]
[57]
[58]
[59]
B. napus [31]**
[60]
[61]Male-fertile line
[61]Male-sterile line
[62]
[63]
[64]
[65]**
[66]**
[67]**
[68]
[33]
[20]
[69]**
[70]**
[71]Hybrid
[71]Non-hybrid
[72]**
** [73]**
* [74]
[75]
* [76]**
[77]Hybrid
[77]Non-hybrid
[78]
[79]
[80]
[81]Hybrid
[81]Non-hybrid
[82]
[83]
[84]**
[85]
[86]
[87]
[88]
B. oleracea [89]
[90]
[31]**
[91]
[92]Cabbage **
[92]Cauliflower **
[93]
B. rapa [31]**
[94]**
[95]**
[96]
[97]
[98]
[99]
[100]
[101]
[102]**
[103]**
[104]
C. sativa [38]**
E. sativa [31]**
R. sativus [31]**
[105]**
[106]
[107]**
[108]**
[109]
[110]
S. alba [31]
[111]
* Most common response when several cultivars, planting dates, or experimental locations were used.
The percentage of publications showing an increase, decrease, and neutral effect of insect pollination on the main yield parameters is shown in Figure 2. In this figure, the O yield parameter is not shown for self-incompatible species because only two publications reported on the effect that insect pollination had on this yield parameter in self-incompatible Brassicaceae crops.

3.1. Effect of Insect Pollination on Yield Parameters in Self-Compatible and Self-Incompatible Species

In terms of insect pollination and crop yield, B. napus and B. rapa were the most studied crops among the self-compatible and self-incompatible Brassicaceae crops, respectively (Table 2, Tables S4 and S5). The meta-analysis evaluation of the effect of insect pollination on the main yield parameters is shown below.

3.1.1. Effect of Insect Pollination on Y

For self-compatible species, a total of seven studies were included in the analysis (Figure 3A). The observed standardized mean differences ranged from 0.93 to 2.99, with all estimates being positive. The estimated average standardized mean difference was 1.95 (95% CI: 1.40–2.49). The average outcome differed significantly from zero (z = 7.02, p ≤ 0.001). According to the Q-test, there was no significant amount of heterogeneity in the true outcomes (Table 3). A 95% prediction interval for the true outcomes was given by 1.02–2.87. The rank correlation test indicated that there was no significant funnel plot asymmetry (Table 3, Figure S1A).
For self-incompatible species, a total of 11 studies were included in the analysis (Figure 3B). The observed standardized mean differences ranged from 1.33 to 25.89, with all estimates being positive. The estimated average standardized mean difference was 6.62 (95% CI: 3.20–10.04). The average outcome differed significantly from zero (z = 3.79, p ≤ 0.001). According to the Q-test and the high I2 statistic, the true outcomes appear to be heterogeneous (Table 3). A 95% prediction interval for the true outcomes is given by −4.93–18.17. The rank correlation test indicated that there was no significant funnel plot asymmetry (Table 3, Figure S1B).

3.1.2. Effect of Insect Pollination on WS

For self-compatible species, a total of 11 studies were included in the analysis (Figure 4A). The observed standardized mean differences ranged from −1.31 to 12.45, with the majority of estimates being positive (64%). The estimated average standardized mean difference was 0.18 (95% CI: −0.44–0.80). The average outcome did not differ significantly from zero (z = 0.57, p = 0.571). According to the Q-test and the I2, the true outcomes appear to be heterogeneous (Table 3). A 95% prediction interval for the true outcomes was given by −1.53–1.89. The rank correlation test indicated that there was no significant funnel plot asymmetry (Table 3, Figure S2A).
For self-incompatible species, a total of 10 studies were included in the analysis (Figure 4B). The observed standardized mean differences ranged from −0.36 to 59.87 with the majority of the estimates being positive (90%). The estimated average standardized mean difference was 12.91 (95% CI: 2.89–22.93). The average outcome differed significantly from zero (z = 2.52, p = 0.012). According to the Q-test and the high I2 statistic, the true outcomes appear to be heterogeneous (Table 3). A 95% prediction interval for the true outcomes is given by −19.72–45.54. The rank correlation test indicated potential funnel plot asymmetry (Table 3, Figure S2B).

3.1.3. Effect of Insect Pollination on SQS

For self-compatible species, a total of 12 studies were included in the analysis (Figure 5A). The observed standardized mean differences ranged from 0.25 to 8.15, with all estimates being positive. The estimated average standardized mean difference was 2.19 (95% CI: 0.92–3.46). The average outcome differed significantly from zero (z = 3.38, p ≤ 0.001). According to the Q-test and the high I2 statistic, the true outcomes appear to be heterogeneous (Table 3). A 95% prediction interval for the true outcomes is given by −2.19–6.58. The rank correlation test indicated that there was no significant funnel plot asymmetry (Table 3, Figure S3A).
For self-incompatible species, a total of eight studies were included in the analysis (Figure 5B). The observed standardized mean differences ranged from 1.54–10.39, with all estimates being positive. The estimated average standardized mean difference was 5.46 (95% CI: 3.18–7.74). The average outcome differed significantly from zero (z = 4.69, p ≤ 0.001). According to the Q-test and the high I2 statistic, the true outcomes appeared to be heterogeneous (Table 3). A 95% prediction interval for the true outcomes is given by −1.12–12.04. The rank correlation test indicated potential funnel plot asymmetry (Table 3, Figure S3B).

3.1.4. Effect of Insect Pollination on NSQ

For self-compatible species, a total of 12 studies were included in the analysis (Figure 6A). The observed standardized mean differences ranged from 0.71 to 11.94, with all estimates being positive. The estimated average standardized mean difference was 4.00 (95% CI: 2.41–5.58). The average outcome significantly differed from zero (z = 4.95, p ≤ 0.001). According to the Q-test and the high I2 statistic, the true outcomes appear to be heterogeneous (Table 3). A 95% prediction interval for the true outcomes is given by −1.39–9.38. The rank correlation test indicated potential funnel plot asymmetry (Table 3, Figure S4A).
For self-incompatible species, a total of nine studies were included in the analysis (Figure 6B). The observed standardized mean differences ranged from 0.15 to 29.39, with all estimates being positive. The estimated average standardized mean difference was 14.76 (95% CI: 7.79–21.74). The average outcome differed significantly from zero (z = 4.15, p ≤ 0.001). According to the Q-test and the high I2 statistic, the true outcomes appear to be heterogeneous (Table 3). A 95% prediction interval for the true outcomes is given by −7.06–36.59. The rank correlation test indicated that there was no significant funnel plot asymmetry (Table 3, Figure S4B).

3.1.5. Effect of Insect Pollination on NSSQ

For self-compatible species, a total of 23 studies were included in the analysis (Figure 7A). The observed standardized mean differences ranged from −1.23 to 4.20, with the majority of the estimates being positive (87%). The estimated average standardized mean difference was 1.62 (95% CI: 0.99–2.24). The average outcome differed significantly from zero (z = 5.07, p ≤ 0.001). According to the Q-test and the high I2 statistic, the true outcomes appear to be heterogeneous (Table 3). A 95% prediction interval for the true outcomes is given by −1.32–4.56. The rank correlation test indicated that there was no significant funnel plot asymmetry (Table 3, Figure S5A).
For self-incompatible species, a total of 16 studies were included in the analysis (Figure 7B). The observed standardized mean differences ranged from 1.54 to 81.26, with all estimates being positive. The relatively high standardized mean difference value and 95% CI of 81.26 [56.06, 106.46] in the study conducted with cabbage by Verma and Partap [92] was probably due to the large difference in the number of seeds per silique between open-pollinated plants and caged plants not exposed to insect pollination, as there was no silique set and the number of seeds per silique was zero in caged plants. The estimated average standardized mean difference was 5.07 (95% CI: 3.60–6.54). The average outcome differed significantly from zero (z = 6.75, p ≤ 0.001). According to the Q-test and the high I2 statistic, the true outcomes appear to be heterogeneous (Table 3). A 95% prediction interval for the true outcomes is given by −0.65–10.78. The rank correlation test indicated the potential funnel plot asymmetry (Table 3, Figure S5B).

4. Insect Pollinators of Crops of the Family Brassicaceae

The main pollinators reported for these crops are shown in Table 4, with the top pollinators for all of them being honeybees (Apis spp.), such as A. mellifera, A. cerana., A. dorsata, and A. florea, and mining bees (Andrenidae). Additional pollinators often reported for these crops are other Apidae (other than Apis spp.), such as bumblebees (Bombus spp.), sweat bees (Halictidae), and hoverflies (Syrphidae) for B. juncea; other Apidae and Syrphidae for B. napus; Halictidae and Syrphidae for B. oleracea; Syrphidae, Halictidae, and other Apidae for B. rapa; Syrphidae and Halictidae for C. sativa; other Apidae and Syrphidae for E. sativa; and Halictidae and Syrphidae for R. sativus. In the case of B. napus, single visit pollen deposition has been shown to be the highest for Bombus spp., Andrenidae, and A. mellifera (with median pollen grain depositions of 341, 335, and 202, respectively) [112], while single visit efficiency in terms of the number of seeds/silique produced was highest for Halictus and Apis spp. [66]. In B. napus, there were no differences in honeybee and bumblebee visits between open-pollinated and hybrid varieties [113], but bee abundance was higher and pollination deficit was lower in conventional compared to genetically modified Roundup Ready plants [114]. In the case of B. rapa, efficiency, given by stigmatic pollen grain deposition by a single visit of an insect to a flower, was highest for Bombus terrestris L. [15,115]. In addition to efficiency, the abundance and number of insect visits makes some insects more effective pollinators than others. Because of this, A. mellifera, often the most common floral visitor, can be considered a more effective pollinator than more efficient pollinators that visit flowers less often [15]. However, one or two bee flower visits may be sufficient to achieve a full seed set in B. rapa flowers [116,117].

5. Discussion and Main Conclusions

Approximately 75% of crop species benefit from pollinators, contributing to an estimated 9.5% of the value of the world agriculture production devoted to human food [1,147]. Other studies conducting meta-analysis have also shown the benefits of insect pollination for plant reproduction and yield in crops in general [148,149,150], in the plant species of particular natural habitats [151], and in particular crops, such as fava bean [152], oilseed rape [34], and tomato [153]. This review and meta-analysis shows that, overall, the yield parameters of crops in the family Brassicaceae benefit from insect pollination. Insect pollination has a positive effect on Y, SQS, NSQ, and NSSQ in both self-compatible and self-incompatible cruciferous crops. WS, however, increased as a result of insect pollination only in self-incompatible species. Even though the meta-analysis was conducted with crop species grouped into self-compatible and self-incompatible ones, it indicates that significant yield benefits of insect pollination also occur at the level of individual cruciferous crops.
Plants have evolved to have self-compatibility as a reproductive assurance that gives them a fitness advantage when ovules are outcross-pollen-limited [37]. However, this review shows that in self-compatible species, most yield parameters continue to benefit from insect pollination. Because of this, in some self-compatible crop species such as B. napus, the placement of honeybee colonies next to fields has been recommended [62,154]. Regarding the overall neutral effect of insect pollination on WS in self-compatible species, it is known that plants can compensate for variation among some yield parameters [62,63,85]. For example, WS is negatively correlated with NSP and NSSQ in B. napus [62,63,85]. This negative correlation indicates that B. napus can produce heavier seeds when the seed set is low [62,65,155]. For this reason, even if insect pollination does not increase WS, an increase in NSP can result in a positive effect on Y [62,86]. Another benefit of insect pollination shown for B. napus is the shortening of the flowering period and, therefore, of the growing season [87,156,157]. On the other hand, delayed maturity can also increase Y [158].
Except in the case of Y in self-compatible species, a significant amount of heterogeneity (given by the significance of the Q-test and the moderate to high I2 statistic) was found in the meta-analyses. Furthermore, for NSQ in self-compatible species, and for WS, SQS, and NSSQ in self-incompatible ones, significant asymmetry in the funnel plots (given by the significance of the Begg and Mazumdar rank correlation test) was found. Among the possible reasons explaining this significant heterogeneity and funnel plot asymmetry could be differences in sample size among studies and the high variability of results in yield parameters shown in some studies in the presence and absence of insect pollination. This high variability was more marked in the case of self-incompatible species. This could be an explanation of why funnel plot asymmetry occurred more often in self-incompatible species (occurring for WS, SQS, and NSSQ, i.e., in three out of the six yield parameters examined in the meta-analysis) than in self-compatible ones (occurring only for NSQ, i.e., in one out of six yield parameters examined). Some studies conducted with self-incompatible species and included in the meta-analyses reported SQS values of zero in the absence of insect pollination [92,105]. Low SQS in the absence of insect pollination has been shown for self-incompatible species in other studies [35]. For example, in the absence of insect pollination, the maximum SQS was 17% in self-incompatible species, and in some cases the few siliques produced had either very few or no seeds [35]. On the other hand, in the absence of insect pollination, self-compatible species had at least 43–90% of the silique set [35]. Although this review and meta-analysis only includes crops, given the closeness of the species within the family, the positive effects of insect pollination on yield parameters are also likely to occur in wild Brassicaceae, most of which are considered self-incompatible [159]. The positive effects of insect pollination on seed yield parameters have been found even in self-compatible wild Brassicaceae such as Lobularia maritima (L.) Desv. [160,161].
Both honeybees and wild bees are considered important pollinators of crops [148,162,163,164]. Among the variety of pollinators attracted to flowers of cultivated Brassicaceae, honeybees, A. mellifera and other Apis spp., seem to be the dominant reported species. However, other Apidae, such as bumblebees, mining bees (Andrenidae), sweat bees (Halictidae), and hoverflies (Syrphidae) are also commonly reported as pollinators of these crops. Since A. mellifera is often the most common floral visitor, the higher frequency of visits can make it a more effective pollinator than other more efficient pollinators that visit flowers less often [15,135,136,137]. Other pollinator families, such as Lepidoptera, were not among the most abundant pollinators found in the studies reviewed. However, lepidopterans such as Pieris spp. (Lepidoptera: Pieridae) were sometimes reported among less common pollinators [58,132,140]. Pollinator diversity can also enhance crop pollination and yield [34].
The importance of pollinators for yield in Brassicaceae crops makes it paramount to ensure that agricultural practices are compatible with pollinator conservation. Pest management and other agricultural practices can affect the effect of pollination on yield, and this has been shown for B. napus [75,79,85,165,166] and B. rapa [102,114]. In general, the application of pesticides, if unavoidable, should be performed following practices that minimize the risk of pollinator poisoning, such as using pesticides of low toxicity and not spraying when bees are foraging [14,101,167,168]. Unfortunately, some farmers growing cruciferous crops are unaware of the harmful effects that pesticide applications can have on pollinators and other beneficial insects [169,170]. Pollinator conservation practices, such as setting pollinator reservoirs [171,172,173], could also be implemented in the vicinity of Brassicaceae crops to ensure that pollinators can be sustained throughout the year. Pollinator reservoirs can also help in conservation biological control [174,175]. Some of the crops included in this review, such as B. rapa and S. alba, have also been used as insectary plants [176]. Proximity to natural habitats with natural vegetation and where wild bees can locate their nests can also enhance the abundance of wild bees [104,115,128]. The flowers of crucifer crops can also temporarily benefit wild bees because of the food resource boost [129].
In conclusion, a meta-analysis shows that insect pollination has a positive effect on Y, SQS, NSQ, and NSSQ in both self-compatible and self-incompatible cruciferous crops. WS increased as a result of insect pollination only in self-incompatible species. Given the reproductive advantage of self-compatibility in the absence of pollinators, insect pollination could have more positive effects on yield parameters in self-incompatible species than in self-compatible ones. However, among the yield parameters investigated, WS was the only one that did not improve in self-compatible species as a result of insect pollination. In Brassicaceae crops, the insect families most reported as pollinators are Apidae, Andrenidae, Syrphidae, and Halictidae.

Supplementary Materials

The following are available online at https://www.mdpi.com/article/10.3390/agriculture12040446/s1, Table S1: Studies reporting on insect pollination and yield parameters in Brassica carinata, Camelina sativa, Eruca sativa, and Sinapis alba; n/a = information not available; Table S2: Studies reporting on insect pollination and yield parameters in Brassica juncea; n/a = information not available; Table S3: Studies reporting on insect pollination and yield parameters in Brassica napus. Except for Sihag et al., the references are from the year 2000 onwards; n/a = information not available; Table S4: Studies reporting on insect pollination and yield parameters in Brassica oleracea; n/a = information not available; Table S5: Studies reporting on insect pollination and yield parameters in Brassica rapa (synonymous of Brassica campestris); n/a = information not available; Table S6: Studies reporting on insect pollination and yield parameters in Raphanus sativus; n/a = information not available; Figure S1: Funnel plots corresponding to the meta-analyses of the effect of insect pollination on seed yield in self-compatible (A) and self-incompatible (B) Brassicaceae crops; Figure S2: Funnel plots corresponding to the meta-analyses of the effect of insect pollination on the weight of seeds in self-compatible (A) and self-incompatible (B) Brassicaceae crops; Figure S3: Funnel plots corresponding to the meta-analyses of the effect of insect pollination on the silique set in self-compatible (A) and self-incompatible (B) Brassicaceae crops; Figure S4: Funnel plots corresponding to the meta-analyses of the effect of insect pollination on the number of siliques/plant or area in self-compatible (A) and self-incompatible (B) Brassicaceae crops; Figure S5: Funnel plots corresponding to the meta-analyses of the effect of insect pollination on the number of seeds per silique or area in self-compatible (A) and self-incompatible (B) Brassicaceae crops.

Funding

Fees for the publication of this review were paid by funding from the Spanish Ministry of Science, Innovation, and Universities, grant RTI2018-096591-B-I00.

Acknowledgments

I thank the anonymous reviewers of this manuscript for their helpful comments and suggestions and Laura Barrios for advice on statistical analysis.

Conflicts of Interest

The author declares no conflict of interest.

References

  1. Klein, A.M.; Vaissière, B.E.; Cane, J.H.; Steffan-Dewenter, I.; Cunningham, S.A.; Kremen, C.; Tscharntke, T. Importance of Pollinators in Changing Landscapes for World Crops. Proc. R. Soc. B Biol. Sci. 2007, 274, 303–313. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  2. Aizen, M.A.; Garibaldi, L.A.; Cunningham, S.A.; Klein, A.M. Long-Term Global Trends in Crop Yield and Production Reveal No Current Pollination Shortage but Increasing Pollinator Dependency. Curr. Biol. 2008, 18, 1572–1575. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  3. Senapathi, D.; Biesmeijer, J.C.; Breeze, T.D.; Kleijn, D.; Potts, S.G.; Carvalheiro, L.G. Pollinator Conservation—the Difference between Managing for Pollination Services and Preserving Pollinator Diversity. Curr. Opin. Insect Sci. 2015, 12, 93–101. [Google Scholar] [CrossRef] [Green Version]
  4. Ollerton, J.; Winfree, R.; Tarrant, S. How Many Flowering Plants Are Pollinated by Animals? Oikos 2011, 120, 321–326. [Google Scholar] [CrossRef]
  5. Crepet, W.L. Advanced (Constant) Insect Pollination Mechanisms: Pattern of Evolution and Implications Vis-a-Vis Angiosperm Diversity. Ann. Mo. Bot. Gard. 1984, 71, 607–630. [Google Scholar] [CrossRef]
  6. Preston, R.E. Pollen-Ovule Ratios in the Cruciferae. Am. J. Bot. 1986, 73, 1732–1740. [Google Scholar] [CrossRef]
  7. Goodwillie, C.; Kalisz, S.; Eckert, C.G. The Evolutionary Enigma of Mixed Mating Systems in Plants: Occurrence, Theoretical Explanations, and Empirical Evidence. Annu. Rev. Ecol. Evol. Syst. 2005, 36, 47–79. [Google Scholar] [CrossRef] [Green Version]
  8. Abrol, D.P. Pollination Biology: Biodiversity Conservation and Agricultural Production; Springer: Dordrecht, The Netherlands, 2012; ISBN 978-94-007-1941-5. [Google Scholar]
  9. Hall, J.C.; Sytsma, K.J.; Iltis, H.H. Phylogeny of Capparaceae and Brassicaceae Based on Chloroplast Sequence Data. Am. J. Bot. 2002, 89, 1826–1842. [Google Scholar] [CrossRef]
  10. Méndez, M.; Gómez, J.M. Phenotypic Gender in Hormathophylla Spinosa (Brassicaceae), a Perfect Hermaphrodite with Tetradynamous Flowers, Is Variable. Plant Syst. Evol. 2006, 262, 225–237. [Google Scholar] [CrossRef] [Green Version]
  11. Matsuhashi, S.; Sakai, S.; Kudoh, H. Temperature-Dependent Fluctuation of Stamen Number in Cardamine Hirsuta (Brassicaceae). Int. J. Plant Sci. 2012, 173, 391–398. [Google Scholar] [CrossRef]
  12. Soza, V.L.; Le Huynh, V.; Di Stilio, V.S. Pattern and Process in the Evolution of the Sole Dioecious Member of Brassicaceae. Evodevo 2014, 5, 42. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  13. Rea, A.C.; Nasrallah, J.B. Self-Incompatibility Systems: Barriers to Self-Fertilization in Flowering Plants. Int. J. Dev. Biol. 2008, 52, 627–636. [Google Scholar] [CrossRef] [PubMed]
  14. Badenes-Pérez, F.R.; Bhardwaj, T.; Thakur, R.K. Integrated Pest Management and Pollination Services in Brassica Oilseed Crops. In Integrated Management of Insect Pests on Canola and Other Brassica Oilseed Crops; Reddy, G.V.P., Ed.; CABI: Wallingford, UK, 2017; pp. 341–349. ISBN 978-1-78064-820-0. [Google Scholar]
  15. Rader, R.; Howlett, B.G.; Cunningham, S.A.; Westcott, D.A.; Newstrom-Lloyd, L.E.; Walker, M.K.; Teulon, D.A.J.; Edwards, W. Alternative Pollinator Taxa Are Equally Efficient but Not as Effective as the Honeybee in a Mass Flowering Crop. J. Appl. Ecol. 2009, 46, 1080–1087. [Google Scholar] [CrossRef]
  16. Al-Shehbaz, I.A. Brassicaceae (Mustard Family). In eLS; Wiley: Hoboken, NJ, USA, 2011; pp. 482–486. [Google Scholar]
  17. Warwick, S.I. Brassicaceae in Agriculture. In Genetics and Genomics of the Brassicaceae; Schmidt, R., Bancroft, I., Eds.; Springer: New York, NY, USA, 2011; pp. 33–65. ISBN 978-1-4419-7118-0. [Google Scholar]
  18. Wilson, C.; Golden, D.; Hubbs, T. Oil Crops Outlook: March 2021. 2021. Available online: https://downloads.usda.library.cornell.edu/usda-esmis/files/j098zb08p/t722j539s/g445d881s/OCS21e.pdf (accessed on 1 March 2022).
  19. Catarino, R.; Bretagnolle, V.; Perrot, T.; Vialloux, F.; Gaba, S. Bee Pollination Outperforms Pesticides for Oilseed Crop Production and Profitability. Proc. R. Soc. B Biol. Sci. 2019, 286, 20191550. [Google Scholar] [CrossRef]
  20. Stanley, D.; Gunning, D.; Stout, J. Pollinators and Pollination of Oilseed Rape Crops (Brassica Napus L.) in Ireland: Ecological and Economic Incentives for Pollinator Conservation. J. Insect. Conserv. 2013, 17, 1181–1189. [Google Scholar] [CrossRef]
  21. Chambó, E.D.; Camargo, S.C.; Garcia, R.C.; Carvalho, C.A.L.; Ruvolo-Takasusuki, M.C.C.; Ronqui, L.; Júnior, C.S.; Santos, P.R.; de Alencar Arnaut de Toledo, V. Benefits of Entomophile Pollination in Crops of Brassica Napus and Aspects of Plant Floral Biology. Brassica Germplasm-Charact. Breed. Util. 2018, 95–106. [Google Scholar] [CrossRef] [Green Version]
  22. Wittkop, B.; Snowdon, R.J.; Friedt, W. Status and Perspectives of Breeding for Enhanced Yield and Quality of Oilseed Crops for Europe. Euphytica 2009, 170, 131. [Google Scholar] [CrossRef]
  23. Moser, B.R.; Winkler-Moser, J.K.; Shah, S.N.; Vaughn, S.F. Composition and Physical Properties of Arugula, Shepherd’s Purse, and Upland Cress Oils. Eur. J. Lipid Sci. Technol. 2010, 112, 734–740. [Google Scholar] [CrossRef]
  24. Shonnard, D.R.; Williams, L.; Kalnes, T.N. Camelina-Derived Jet Fuel and Diesel: Sustainable Advanced Biofuels. Environ. Prog. Sustain. Energy 2010, 29, 382–392. [Google Scholar] [CrossRef]
  25. Chammoun, N.; Geller, D.P.; Das, K.C. Fuel Properties, Performance Testing and Economic Feasibility of Raphanus Sativus (Oilseed Radish) Biodiesel. Ind. Crops Prod. 2013, 45, 155–159. [Google Scholar] [CrossRef]
  26. Del Gatto, A.; Melilli, M.G.; Raccuia, S.A.; Pieri, S.; Mangoni, L.; Pacifico, D.; Signor, M.; Duca, D.; Pedretti, E.F.; Mengarelli, C. A Comparative Study of Oilseed Crops (Brassica Napus L. Subsp. Oleifera and Brassica Carinata A. Braun) in the Biodiesel Production Chain and Their Adaptability to Different Italian Areas. Ind. Crops Prod. 2015, 75, 98–107. [Google Scholar] [CrossRef]
  27. McVetty, P.B.E.; Duncan, R.W. Canola, Rapeseed, and Mustard: For Biofuels and Bioproducts. In Industrial Crops: Breeding for BioEnergy and Bioproducts; Cruz, V.M.V., Dierig, D.A., Eds.; Springer: New York, NY, USA, 2015; pp. 133–156. ISBN 978-1-4939-1447-0. [Google Scholar]
  28. Hossain, Z.; Johnson, E.N.; Wang, L.; Blackshaw, R.E.; Gan, Y. Comparative Analysis of Oil and Protein Content and Seed Yield of Five Brassicaceae Oilseeds on the Canadian Prairie. Ind. Crops Prod. 2019, 136, 77–86. [Google Scholar] [CrossRef]
  29. Gesch, R.W.; Long, D.S.; Palmquist, D.; Allen, B.L.; Archer, D.W.; Brown, J.; Davis, J.B.; Hatfield, J.L.; Jabro, J.D.; Kiniry, J.R.; et al. Agronomic Performance of Brassicaceae Oilseeds in Multiple Environments across the Western USA. Bioenerg. Res. 2019, 12, 509–523. [Google Scholar] [CrossRef]
  30. Mitrović, P.M.; Stamenković, O.S.; Banković-Ilić, I.; Djalović, I.G.; Nježić, Z.B.; Farooq, M.; Siddique, K.H.M.; Veljković, V.B. White Mustard (Sinapis Alba L.) Oil in Biodiesel Production: A Review. Front. Plant Sci. 2020, 11, 299. [Google Scholar] [CrossRef] [PubMed]
  31. Sihag, R.C. Insect Pollination Increases Seed Production in Cruciferous and Umbelliferous Crops. J. Apic. Res. 1986, 25, 121–126. [Google Scholar] [CrossRef]
  32. Abrol, D.P. Honeybees and Rapeseed: A Pollinator–Plant Interaction. In Advances in Botanical Research; Academic Press: Cambridge, MA, USA, 2007; Volume 45, pp. 337–367. ISBN 0065-2296. [Google Scholar]
  33. Bommarco, R.; Marini, L.; Vaissière, B.E. Insect Pollination Enhances Seed Yield, Quality, and Market Value in Oilseed Rape. Oecologia 2012, 169, 1025–1032. [Google Scholar] [CrossRef]
  34. Woodcock, B.A.; Garratt, M.P.D.; Powney, G.D.; Shaw, R.F.; Osborne, J.L.; Soroka, J.; Lindström, S.A.M.; Stanley, D.; Ouvrard, P.; Edwards, M.E.; et al. Meta-Analysis Reveals That Pollinator Functional Diversity and Abundance Enhance Crop Pollination and Yield. Nat. Commun. 2019, 10, 1481. [Google Scholar] [CrossRef] [Green Version]
  35. Salisbury, P.A.; Fripp, Y.J.; Gurung, A.M.; Williams, W.M. Is Floral Structure a Reliable Indicator of Breeding System in the Brassicaceae? PLoS ONE 2017, 12, e0174176. [Google Scholar] [CrossRef]
  36. Bateman, A.J. Self-Incompatibility Systems in Angiosperms. 3. Cruciferae. Heredity 1955, 9, 53–68. [Google Scholar] [CrossRef] [Green Version]
  37. Holsinger, K.E.; Steinbachs, J.E. Mating Systems and Evolution in Flowering Plants. In Evolution and Diversification of Land Plants; Iwatsuki, K., Raven, P.H., Eds.; Springer: Tokyo, Japan, 1997; pp. 223–248. ISBN 978-4-431-65918-1. [Google Scholar]
  38. Groeneveld, J.H.; Klein, A.-M. Pollination of Two Oil-Producing Plant Species: Camelina (Camelina Sativa L. Crantz) and Pennycress (Thlaspi Arvense L.) Double-Cropping in Germany. GCB Bioenergy 2014, 6, 242–251. [Google Scholar] [CrossRef] [Green Version]
  39. Williams, I.H.; Martin, A.P.; White, R.P. The Pollination Requirements of Oil-Seed Rape (Brassica Napus L.). J. Agric. Sci. 1986, 106, 27–30. [Google Scholar] [CrossRef]
  40. Sihag, R.C. Characterization of the Pollinators of Cultivated Cruciferous and Leguminous Crops of Sub-Tropical Hissar, India. Bee World 1988, 69, 153–158. [Google Scholar] [CrossRef]
  41. Snell, R.; Aarssen, L.W. Life History Traits in Selfing versus Outcrossing Annuals: Exploring the “time-Limitation” Hypothesis for the Fitness Benefit of Self-Pollination. BMC Ecol. 2005, 5, 2. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  42. Prasad, D.; Hameed, S.F.; Singh, R.; Yazdani, S.S.; Singh, B. Effect of Bee Pollination on the Quantity and Quality of Rai Crop (Brassica Juncea Coss). Indian Bee J. 1989, 51, 45–47. [Google Scholar]
  43. The Jamovi Project Jamovi, Version 1.6; Jamovi: Sydney, Australia, 2021.
  44. Viechtbauer, W. Conducting Meta-Analyses in R with the Metafor Package. J. Stat. Softw. 2010, 36, 1–48. [Google Scholar] [CrossRef] [Green Version]
  45. Hedges, L.V. Distribution Theory for Glass’s Estimator of Effect Size and Related Estimators. J. Educ. Stat. 1981, 6, 107–128. [Google Scholar] [CrossRef]
  46. Higgins, J.P.T.; Thompson, S.G.; Deeks, J.J.; Altman, D.G. Measuring Inconsistency in Meta-Analyses. BMJ 2003, 327, 557–560. [Google Scholar] [CrossRef] [Green Version]
  47. Sterne, J.A.C.; Egger, M.; Smith, G.D. Investigating and Dealing with Publication and Other Biases in Meta-Analysis. BMJ 2001, 323, 101–105. [Google Scholar] [CrossRef]
  48. Begg, C.B.; Mazumdar, M. Operating Characteristics of a Rank Correlation Test for Publication Bias. Biometrics 1994, 50, 1088–1101. [Google Scholar] [CrossRef]
  49. Page, M.J.; McKenzie, J.E.; Bossuyt, P.M.; Boutron, I.; Hoffmann, T.C.; Mulrow, C.D.; Shamseer, L.; Tetzlaff, J.M.; Akl, E.A.; Brennan, S.E.; et al. The PRISMA 2020 Statement: An Updated Guideline for Reporting Systematic Reviews. BMJ 2021, 372, n71. [Google Scholar] [CrossRef]
  50. Stiles, S.; Lundgren, J.G.; Fenster, C.B.; Nottebrock, H. Maximizing Ecosystem Services to the Oil Crop Brassica Carinata through Landscape Heterogeneity and Arthropod Diversity. Ecosphere 2021, 12, e03624. [Google Scholar] [CrossRef]
  51. Chand, H.; Singh, B. Effect of Pollination by Apis Cerana Fabr. on Yield of Mustard, Brassica Juncea. Indian Bee J. 1995, 57, 173–174. [Google Scholar]
  52. Mahindru, N.; Singh, G.; Grewal, G.S. Comparative Abundance and Foraging Behaviour of Insect Pollinators of Raya, Brassica Juncea L. and Role of Apis Mellifera L. in Crop Pollination. J. Insect Sci. 1998, 11, 34–37. [Google Scholar]
  53. Goswami, V.; Khan, M.S. Impacto of Honey Bee Pollination on Pod Set of Mustard (Brassica Juncea L.: Cruciferae) at Pantnagar. Bioscan 2014, 9, 75–78. [Google Scholar]
  54. Maity, A.; Chakrabarty, S.K.; Yadav, J.B. Foraging Behaviour of Honeybees (Apis Spp.) (Hymenoptera: Apidae) in Hybrid Seed Production of Indian Mustard (Brassica Juncea). Indian J. Agric. Sci. 2014, 84, 1389–1394. [Google Scholar]
  55. Nagpal, K.; Yadav, S.; Kumar, Y.; Singh, R. Effect of Pollination Modes on Yield Components in Indian Mustard (Brassica Juncea L.). J. Oilseed Brassica 2017, 8, 187–194. [Google Scholar]
  56. Devi, M.; Sharma, H.; Thakur, R.K.; Bhardwaj, S.; Rana, K.; Thakur, M.; Ram, B. Diversity of Insect Pollinators in Reference to Seed Set of Mustard (Brassica Juncea L.). Int. J. Curr. Microbiol. Appl. Sci. 2017, 6, 2131–2144. [Google Scholar] [CrossRef]
  57. Devi, M.; Sharma, H.K. Effect of Different Modes of Pollination on Seed Set of Mustard (Brassica Juncea L.) Sown on Different Sowing Dates. J. Entomol. Zool. Stud. 2018, 6, 1889–1893. [Google Scholar]
  58. Mandal, E.; Amin, M.R.; Rahman, H.; Akanda, A.M. Abundance and Foraging Behavior of Native Insect Pollinators and Their Effect on Mustard (Brassica Juncea L.). Bangladesh J. Zool. 2018, 46, 117–123. [Google Scholar] [CrossRef] [Green Version]
  59. Mahadik, P.B.; Kulkarni, S.R.; Manchare, R.R. Impact of Honey Bees as a Pollinators on Seed Production of Mustard (Brassica Juncea L.). J. Entomol. Zool. Stud. 2019, 7, 1380–1383. [Google Scholar]
  60. Mussury, R.M.; Fernandes, W.D. Studies of the Floral Biology and Reproductive System of Brassica Napus L. (Cruciferae). Braz. Arch. Biol. Technol. 2000, 43, 111–117. [Google Scholar] [CrossRef] [Green Version]
  61. Steffan-Dewenter, I. Seed Set of Male-Sterile and Male-Fertile Oilseed Rape (Brassica Napus) in Relation to Pollinator Density. Apidologie 2003, 34, 227–235. [Google Scholar] [CrossRef] [Green Version]
  62. Manning, R.; Wallis, I.R. Seed Yields in Canola (Brassica Napus Cv. Karoo) Depend on the Distance of Plants from Honeybee Apiaries. Aust. J. Exp. Agric. 2005, 45, 1307–1313. [Google Scholar] [CrossRef]
  63. Sabbahi, R.; De Oliveira, D.; Marceau, J. Influence of Honey Bee (Hymenoptera: Apidae) Density on the Production of Canola (Crucifera: Brassicacae). J. Econ. Entomol. 2005, 98, 367–372. [Google Scholar] [CrossRef]
  64. Jauker, F.; Wolters, V. Hover Flies Are Efficient Pollinators of Oilseed Rape. Oecologia 2008, 156, 819–823. [Google Scholar] [CrossRef]
  65. Araneda Durán, X.; Breve Ulloa, R.; Aguilera Carrillo, J.; Lavín Contreras, J.; Toneatti Bastidas, M. Evaluation of Yield Component Traits of Honeybee-Pollinated (Apis Mellifera L.) Rapeseed Canola (Brassica Napus L.). Chil. J. Agric. Res. 2010, 70, 309–314. [Google Scholar] [CrossRef]
  66. Ali, M.; Saeed, S.; Sajjad, A.; Whittington, A. In Search of the Best Pollinators for Canola (Brassica Napus L.) Production in Pakistan. Appl. Entomol. Zool. 2011, 46, 353–361. [Google Scholar] [CrossRef]
  67. De Souza Rosa, A.; Blochtein, B.; Lima, D.K. Honey Bee Contribution to Canola Pollination in Southern Brazil. Sci. Agric. 2011, 68, 255–259. [Google Scholar] [CrossRef] [Green Version]
  68. Jauker, F.; Bondarenko, B.; Becker, H.C.; Steffan-Dewenter, I. Pollination Efficiency of Wild Bees and Hoverflies Provided to Oilseed Rape. Agric. For. Entomol. 2012, 14, 81–87. [Google Scholar] [CrossRef]
  69. Shakeel, M.; Inayatullah, M. Impact of Insect Pollinators on the Yield of Canola (Brassica Napus) in Peshawar, Pakistan. J. Agric. Urban Entomol. 2013, 29, 1–5. [Google Scholar] [CrossRef]
  70. Nedić, N.; Mačukanović-Jocić, M.; Rančić, D.; Rørslett, B.; Šoštarić, I.; Stevanović, Z.D.; Mladenović, M. Melliferous Potential of Brassica Napus L. Subsp. Napus (Cruciferae). Arthropod-Plant Interact. 2013, 7, 323–333. [Google Scholar] [CrossRef]
  71. Hudewenz, A.; Pufal, G.; Bogeholz, A.L.; Klein, A.M. Cross-Pollination Benefits Differ among Oilseed Rape Varieties. J. Agric. Sci. 2014, 152, 770–778. [Google Scholar] [CrossRef]
  72. Garratt, M.P.D.; Coston, D.J.; Truslove, C.L.; Lappage, M.G.; Polce, C.; Dean, R.; Biesmeijer, J.C.; Potts, S.G. The Identity of Crop Pollinators Helps Target Conservation for Improved Ecosystem Services. Biol. Conserv. 2014, 169, 128–135. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  73. Chambó, E.D.; De Oliveira, N.T.E.; Garcia, R.C.; Duarte-Júnior, J.B.; Ruvolo-Takasusuki, M.C.C.; Toledo, V.A. Pollination of Rapeseed (Brassica Napus) by Africanized Honeybees (Hymenoptera: Apidae) on Two Sowing Dates. An. Da Acad. Bras. De Cienc. 2014, 86, 2087–2100. [Google Scholar] [CrossRef] [PubMed]
  74. Blochtein, B.; Nunes-Silva, P.; Halinski, R.; Lopes, L.; Witter, S. Comparative Study of the Floral Biology and of the Response of Productivity to Insect Visitation in Two Rapeseed Cultivars (Brassica Napus L.) in Rio Grande Do Sul. Braz. J. Biol. 2014, 74, 787–794. [Google Scholar] [CrossRef] [Green Version]
  75. Bartomeus, I.; Gagic, V.; Bommarco, R. Pollinators, Pests and Soil Properties Interactively Shape Oilseed Rape Yield. Basic Appl. Ecol. 2015, 16, 737–745. [Google Scholar] [CrossRef] [Green Version]
  76. Witter, S.; Nunes-Silva, P.; Lisboa, B.B.; Tirelli, F.P.; Sattler, A.; Hilgert-Moreira, S.B.; Blochtein, B. Stingless Bees as Alternative Pollinators of Canola. J. Econ. Entomol. 2015, 108, 880–886. [Google Scholar] [CrossRef]
  77. Marini, L.; Tamburini, G.; Petrucco-Toffolo, E.; Lindström, S.A.M.; Zanetti, F.; Mosca, G.; Bommarco, R. Crop Management Modifies the Benefits of Insect Pollination in Oilseed Rape. Agric. Ecosyst. Environ. 2015, 207, 61–66. [Google Scholar] [CrossRef]
  78. Kamel, S.M.; Mahfouz, H.M.; Blal, A.E.-F.H.; Said, M.; Mahmoud, M.F. Diversity of Insect Pollinators with Reference to Their Impact on Yield Production of Canola (Brassica Napus L.) in Ismailia, Egypt. Pestic. I Fitomedicina 2015, 30, 161–168. [Google Scholar] [CrossRef]
  79. Sutter, L.; Albrecht, M. Synergistic Interactions of Ecosystem Services: Florivorous Pest Control Boosts Crop Yield Increase through Insect Pollination. Proc. R. Soc. B Biol. Sci. 2016, 283, 1–8. [Google Scholar] [CrossRef] [Green Version]
  80. Samnegård, U.; Hambäck, P.A.; Lemessa, D.; Nemomissa, S.; Hylander, K. A Heterogeneous Landscape Does Not Guarantee High Crop Pollination. Proc. R. Soc. B Biol. Sci. 2016, 283, 20161472. [Google Scholar] [CrossRef] [PubMed]
  81. Lindström, S.A.M.; Herbertsson, L.; Rundlöf, M.; Smith, H.G.; Bommarco, R. Large-Scale Pollination Experiment Demonstrates the Importance of Insect Pollination in Winter Oilseed Rape. Oecologia 2016, 180, 759–769. [Google Scholar] [CrossRef] [PubMed]
  82. van Gils, S.; van der Putten, W.H.; Kleijn, D. Can Above-Ground Ecosystem Services Compensate for Reduced Fertilizer Input and Soil Organic Matter in Annual Crops? J. Appl. Ecol. 2016, 53, 1186–1194. [Google Scholar] [CrossRef] [Green Version]
  83. Zou, Y.; Xiao, H.; Bianchi, F.J.J.A.; Jauker, F.; Luo, S.; van der Werf, W. Wild Pollinators Enhance Oilseed Rape Yield in Small-Holder Farming Systems in China. BMC Ecol. 2017, 17, 6. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  84. Fuzaro, L.; Xavier, N.L.; Carvalho, F.J.; Silva, F.A.N.; Carvalho, S.M.; Andaló, V. Influence of Pollination on Canola Seed Production in the Cerrado of Uberlândia, Minas Gerais State, Brazil. Acta Scientiarum. Agron. 2018, 40, e39315. [Google Scholar] [CrossRef] [Green Version]
  85. Garratt, M.P.D.; Bishop, J.; Degani, E.; Potts, S.G.; Shaw, R.F.; Shi, A.; Roy, S. Insect Pollination as an Agronomic Input: Strategies for Oilseed Rape Production. J. Appl. Ecol. 2018, 55, 2834–2842. [Google Scholar] [CrossRef] [Green Version]
  86. Perrot, T.; Gaba, S.; Roncoroni, M.; Gautier, J.-L.; Bretagnolle, V. Bees Increase Oilseed Rape Yield under Real Field Conditions. Agric. Ecosyst. Environ. 2018, 266, 39–48. [Google Scholar] [CrossRef]
  87. Adamidis, G.C.; Cartar, R.V.; Melathopoulos, A.P.; Pernal, S.F.; Hoover, S.E. Pollinators Enhance Crop Yield and Shorten the Growing Season by Modulating Plant Functional Characteristics: A Comparison of 23 Canola Varieties. Sci. Rep. 2019, 9, 14208. [Google Scholar] [CrossRef]
  88. Mazzilli, S.R.; Abbate, S.; Silva, H.; Mendoza, Y. Apis Mellifera Visitation Enhances Productivity in Rapeseed. J. Apic. Res. 2020, 1–9. [Google Scholar] [CrossRef]
  89. Varma, S.K.; Joshi, N.K. Studies on the Role of Honey Bees in the Pollination of Cauliflower (Brassica Oleracea Var. Botrytis). Indian Bee J. 1983, 45, 52–53. [Google Scholar]
  90. Tewari, G.N.; Singh, K. Studies on Insect Pollinators in Relation to Seed Production in Cauliflower (Brassica Oleracea Var. Botrytis L.). Indian Bee J. 1983, 54–55. [Google Scholar]
  91. Kumar, J.; Gupta, J.K.; Mishra, R.C.; Dogra, G.S. Pollination Studies in Some Cultivars of Cauliflower (Brassica Oleracea Var. Botrytis L.). Indian Bee J. 1988, 50, 93–95. [Google Scholar]
  92. Verma, L.R.; Partap, U. Foraging Behaviour of Apis Cerana on Cauliflower and Cabbage and Its Impact on Seed Production. J. Apic. Res. 1994, 33, 231–236. [Google Scholar] [CrossRef]
  93. Sharma, D.; Abrol, D.P.; Kumar, M.; Singh, S.K.; Singh, P.K. Pollinator Diversity and Its Impact on Cauliflower (Brassica Campestris Var. Botrytis) Pollination. Ann. Agri Bio Res. 2013, 18, 383–385. [Google Scholar]
  94. Mishra, R.C.; Kumar, J.; Gupta, J.K. The Effect of Mode of Pollination on Yield and Oil Potential of Brassica Campestris L. Var. Sarson with Observations on Insect Pollinators. J. Apic. Res. 1988, 27, 186–189. [Google Scholar] [CrossRef]
  95. Singh, R.P.; Singh, P.N. Impact of Bee Pollination on Seed Yield, Carbohydrate Composition and Lipid Composition of Mustard Seed. J. Apic. Res. 1992, 31, 128–133. [Google Scholar] [CrossRef]
  96. Khan, B.M.; Chaudhry, M.I. Comparative Assessment of Honeybees and Other Insects with Self-Pollination of Sarson (Brassica Campestris) in Peshawar. In The Asiatic Hive Bee: Apiculture, Biology and Role in Sustainable Development in Tropical and Subtropical Asia; Kevan, P.G., Ed.; Enviroquest Ltd.: Dresden, ON, Canada, 1995; pp. 147–150. [Google Scholar]
  97. Atmowidi, T.; Buchori, D.; Manuwoto, S.; Suryobroto, B.; Hidayat, P. Diversity of Pollinator Insects in Relation to Seed Set of Mustard (Brassica Rapa L.: Cruciferae). HAYATI J. Biosci. 2007, 14, 155–161. [Google Scholar] [CrossRef] [Green Version]
  98. Tara, J.S.; Sharma, P. Role of Honeybees and Other Insects in Enhancing the Yield of Brassica Campestris Var. Sarson. Halteres 2010, 1, 35–37. [Google Scholar]
  99. Pudasaini, R.; Thapa, R.; Poudel, P. Effect of Pollination on Qualitative Characteristics of Rapeseed (Brassica Campestris L. Var. Toria) Seed in Chitwan, Nepal. Int. J. Biol. Food Vet. Agric. Eng. 2014, 8, 1278–1281. [Google Scholar]
  100. Pudasaini, R.; Thapa, R.B. Effect of Pollination on Rapeseed (Brassica Campestris L. Var. Toria) Production in Chitwan, Nepal. J. Agric. Environ. 2014, 15, 41–45. [Google Scholar] [CrossRef] [Green Version]
  101. Sharma, D.; Abrol, D.P. Effect of Insecticides on Foraging Behaviour and Pollination Role of Apis Mellifera L. (Hymenoptera: Apidae) on Toria (Brassica Campestris Var. Toria) Crop. Egypt. J. Biol. 2014, 16, 79–86. [Google Scholar] [CrossRef]
  102. Toivonen, M.; Herzon, I.; Rajanen, H.; Toikkanen, J.; Kuussaari, M. Late Flowering Time Enhances Insect Pollination of Turnip Rape. J. Appl. Ecol. 2019, 56, 1164–1175. [Google Scholar] [CrossRef] [Green Version]
  103. Subedi, N.; Subedi, I.P. Pollinator Insects and Their Impact on Crop Yield of Mustard in Kusma, Parbat, Nepal. J. Inst. Sci. Technol. 2019, 24, 68–75. [Google Scholar] [CrossRef] [Green Version]
  104. Devkota, K.; dos Santos, C.F.; Blochtein, B. Higher Richness and Abundance of Flower-Visiting Insects Close to Natural Vegetation Provide Contrasting Effects on Mustard Yields. J. Insect. Conserv. 2021, 25, 1–11. [Google Scholar] [CrossRef]
  105. Partap, U.; Verma, L.R. Pollination of Radish by Apis Cerana. J. Apic. Res. 1994, 33, 237–241. [Google Scholar] [CrossRef]
  106. Verma, S.K.; Phogat, K.P.S. Impact of Pollination by Honeybee (Apis Cerana Indica) on the Yield Gain of Radish under Valley Conditions of Himalayan Hills of U. P. (India). Indian Bee J. 1994, 56, 183–186. [Google Scholar]
  107. Priti; Mishra, R.C.; Sihag, R.C. Role of Insect Pollination in Seed Production of Radish (Raphanus Sativus L.). Seed Res. 2001, 29, 231–234. [Google Scholar]
  108. Kapila, R.K.; Singh, H.B.; Sharma, J.K.; Lata, S.; Thakur, S.P. Effect of Insect Pollinators on Seed Yield and Its Quality in Radish (Raphanus Sativus L.). Seed Res. 2002, 30, 142–145. [Google Scholar]
  109. Chandrashekhar, G.S.; Sattigi, H.N. Influence of Bee Attractants on Bee Pollination on Seed Quality and Yield in Radish. Karnataka J. Agric. Sci. 2009, 22, 777–780. [Google Scholar]
  110. Jakhar, P.; Kumar, Y.; Ombir; Janu, A.; Kaushik, P. Effect of Different Modes of Pollination on Quantitative and Qualitative Parameters of Radish Seed Crop. Trends Biosci. 2014, 7, 4041–4044. [Google Scholar]
  111. Gibson-Forty, E.V.J.; Tielbörger, K.; Seifan, M. Equivocal Evidence for a Change in Balance between Selfing and Pollinator-Mediated Reproduction in Annual Brassicaceae Growing along a Rainfall Gradient. J. Syst. Evol. 2022, 60, 196–207. [Google Scholar] [CrossRef]
  112. Phillips, B.B.; Williams, A.; Osborne, J.L.; Shaw, R.F. Shared Traits Make Flies and Bees Effective Pollinators of Oilseed Rape (Brassica Napus L.). Basic Appl. Ecol. 2018, 32, 66–76. [Google Scholar] [CrossRef]
  113. Kazda, J.; Bokšová, A.; Stejskalová, M.; Šubrt, T.; Bartoška, J.; Vlažný, P. The Factors Influencing the Pollinators Visitation of the Oilseed Rape Cultivars. Plant Soil Environ. 2019, 65, 574–580. [Google Scholar] [CrossRef]
  114. Morandin, L.A.; Winston, M.L. Wild Bee Abundance and Seed Production in Conventional, Organic, and Genetically Modified Canola. Ecol. Appl. 2005, 15, 871–881. [Google Scholar] [CrossRef] [Green Version]
  115. Chatterjee, A.; Chatterjee, S.; Smith, B.; Cresswell, J.E.; Basu, P. Predicted Thresholds for Natural Vegetation Cover to Safeguard Pollinator Services in Agricultural Landscapes. Agric. Ecosyst. Environ. 2020, 290, 106785. [Google Scholar] [CrossRef]
  116. Stanley, J.; Sah, K.; Subbanna, A.R.N.S. How Efficient Is the Asian Honey Bee, Apis Cerana in Pollinating Mustard, Brassica Campestris Var. Toria? Pollination Behavior, Pollinator Efficiency, Pollinator Requirements and Impact of Pollination. J. Apic. Res. 2017, 56, 439–451. [Google Scholar] [CrossRef]
  117. Sihag, R.C. Some Unresolved Issues of Measuring the Efficiency of Pollinators: Experimental Testing and Assessing the Predictive Power of Different Methods. Int. J. Ecol. 2018, 2018, 3904973. [Google Scholar] [CrossRef]
  118. Prasad, D.; Hameed, S.P.; Singh, R.; Singh, B. Foraging Behaviour of Insect Pollinators on Brown Mustard, Brassica Juncea in Bihar, India. Indian Bee J. 1989, 51, 131–133. [Google Scholar]
  119. Chand, H.; Singh, R.; Hameed, S.F. Population Dynamics of Honeybees and Insect Pollinators on Indian Mustard, Brassica Juncea L. J. Entomol. Res. 1994, 18, 233–239. [Google Scholar]
  120. Chaudhary, O.P. Abundance of Wild Pollinators on Rapeseed and Mustard. Insect Environ. 2001, 7, 141–142. [Google Scholar]
  121. Bhowmik, K.B.; Mitra, B.; Bhadra, K. Diversity of Insect Pollinators and Their Effect on the Crop Yield of Brassica Juncea L., NPJ-93, from Southern West Bengal. Int. J. Recent Sci. Res. 2014, 5, 1207–1213. [Google Scholar]
  122. Goswami, V.; Khan, M.S.; Srivastava, P. Association of Different Insect Pollinators and Their Relative Abundance on Blossoms of Mustard (Brassica Juncea L.). Environ. Ecol. 2014, 32, 368–371. [Google Scholar]
  123. Kunjwal, N.; Kumar, Y.; Khan, M.S. Flower-Visiting Insect Pollinators of Brown Mustard, Brassica Juncea (L.) Czern and Coss and Their Foraging Behaviour under Caged and Open Pollination. Afr. J. Agric. Res. 2014, 9, 1278–1286. [Google Scholar]
  124. Kumari, S.; Chhuneja, P.K.; Singh, J.; Choudhary, A. Relative Abundance and Diversity of Insects on Brassica Juncea L. Czern under North-Western Plains of India. J. Exp. Zool. India 2015, 18, 165–171. [Google Scholar]
  125. Das, R.; Jha, S. Record of Insect Pollinators and Their Abundance on Indian Mustard (Brassica Juncea L.) in New Alluvial Zone of West Bengal. Int. J. Pure Appl. Biosci. 2018, 6, 848–853. [Google Scholar] [CrossRef]
  126. Giri, S.; Chandra, U.; Jaiswal, R.; Singh, G.; Gautam, M.P. Study the Abundance of Insect Pollinators/Visitors in Rapeseed-Mustard (Brassica Juncea L.). J. Entomol. Zool. Stud. 2018, 6, 2563–2567. [Google Scholar]
  127. Woodcock, B.A.; Edwards, M.; Redhead, J.; Meek, W.R.; Nuttall, P.; Falk, S.; Nowakowski, M.; Pywell, R.F. Crop Flower Visitation by Honeybees, Bumblebees and Solitary Bees: Behavioural Differences and Diversity Responses to Landscape. Agric. Ecosyst. Environ. 2013, 171, 1–8. [Google Scholar] [CrossRef] [Green Version]
  128. Bailey, S.; Requier, F.; Nusillard, B.; Roberts, S.P.M.; Potts, S.G.; Bouget, C. Distance from Forest Edge Affects Bee Pollinators in Oilseed Rape Fields. Ecol. Evol. 2014, 4, 370–380. [Google Scholar] [CrossRef]
  129. Riedinger, V.; Mitesser, O.; Hovestadt, T.; Steffan-Dewenter, I.; Holzschuh, A. Annual Dynamics of Wild Bee Densities: Attractiveness and Productivity Effects of Oilseed Rape. Ecology 2015, 96, 1351–1360. [Google Scholar] [CrossRef]
  130. Ouvrard, P.; Quinet, M.; Jacquemart, A.-L. Breeding System and Pollination Biology of Belgian Oilseed Rape Cultivars (Brassica Napus). Crop Sci. 2017, 57, 1455–1463. [Google Scholar] [CrossRef]
  131. Zou, Y.; Bianchi, F.; Jauker, F.; Xiao, H.J.; Chen, J.H.; Cresswell, J.; Luo, S.D.; Huang, J.K.; Deng, X.Z.; Hou, L.L.; et al. Landscape Effects on Pollinator Communities and Pollination Services in Small-Holder Agroecosystems. Agric. Ecosyst. Environ. 2017, 246, 109–116. [Google Scholar] [CrossRef]
  132. Akhtar, T.; Aziz, M.A.; Naeem, M.; Ahmed, M.S.; Bodlah, I. Diversity and Relative Abundance of Pollinator Fauna of Canola (Brassica Napus L. Var Chakwal Sarsoon) with Managed Apis Mellifera L. in Pothwar Region, Gujar Khan, Pakistan. Pak. J. Zool. 2018, 50, 567–573. [Google Scholar] [CrossRef]
  133. Fuzaro, L.; Andaló, V.; Carvalho, S.M.; Silva, F.A.N.; Carvalho, F.J.; Rabelo, L.S. Floral Visitors of Canola (Brassica Napus L.) Hybrids in Cerrado Mineiro Region, Brazil. Arq. Do Inst. Biológico 2019, 86, e1312018. [Google Scholar]
  134. Sinha, S.N.; Chakrabarty, A.K. Studies on Pollination by Honeybees on Early Cauliflower and Its Effects on Seed Yield and Quality. Seed Res. 1985, 13, 115–119. [Google Scholar]
  135. Priti; Sihag, R.C. Diversity, Visitation Frequency, Foraging Behaviour and Pollinating Efficiency of Insect Pollinators Visiting Cauliflower (Brassica Oleracea L. Var. Botrytis Cv. Hazipur Local) Blossoms. Indian Bee J. 1997, 59, 230–237. [Google Scholar]
  136. Rana, V.K.; Kapoor, K.S.; Raj, D. Comparative Pollinating Activities of Apis Cerana Indica F. and Apis Mellifera L. on Cauliflower (Brassica Oleracea Var. Botrytis). J. Entomol. Res. 1999, 23, 141–148. [Google Scholar]
  137. Selvakumar, P.; Sinha, S.N.; Pandita, V.K. Abundance and Diurnal Rhythm of Honeybees Visiting Hybrid Seed Production Plots of Cauliflower (Brassica Oleracea Var. Botrytis L.). J. Apic. Res. 2006, 45, 7–15. [Google Scholar] [CrossRef]
  138. Srivastava, K.; Sharma, D.; Singh, S.; Ahmad, H. Foraging Behaviour of Honeybees in Seed Production of Brassica Oleracea Var. Italica Plenck. Bangladesh J. Bot. 2017, 46, 675–681. [Google Scholar]
  139. Rader, R.; Howlett, B.G.; Cunningham, S.A.; Westcott, D.A.; Edwards, W. Spatial and Temporal Variation in Pollinator Effectiveness: Do Unmanaged Insects Provide Consistent Pollination Services to Mass Flowering Crops? J. Appl. Ecol. 2012, 49, 126–134. [Google Scholar] [CrossRef]
  140. Mesa, L.A.; Howlett, B.G.; Grant, J.E.; Didham, R.K. Changes in the Relative Abundance and Movement of Insect Pollinators during the Flowering Cycle of Brassica Rapa Crops: Implications for Gene Flow. J. Insect Sci. 2013, 13, 13. [Google Scholar] [CrossRef] [Green Version]
  141. Shakeel, M.; Ali, H.; Ahmad, S.; Said, F.; Khan, K.A.; Bashir, M.A.; Anjum, S.I.; Islam, W.; Ghramh, H.A.; Ansari, M.J.; et al. Insect Pollinators Diversity and Abundance in Eruca Sativa Mill. (Arugula) and Brassica Rapa L. (Field Mustard) Crops. Saudi J. Biol. Sci. 2019, 26, 1704–1709. [Google Scholar] [CrossRef] [PubMed]
  142. Tasker, P.; Reid, C.; Young, A.D.; Threlfall, C.G.; Latty, T. If You Plant It, They Will Come: Quantifying Attractiveness of Exotic Plants for Winter-Active Flower Visitors in Community Gardens. Urban Ecosyst. 2020, 23, 345–354. [Google Scholar] [CrossRef]
  143. Eberle, C.A.; Thom, M.D.; Nemec, K.T.; Forcella, F.; Lundgren, J.G.; Gesch, R.W.; Riedell, W.E.; Papiernik, S.K.; Wagner, A.; Peterson, D.H.; et al. Using Pennycress, Camelina, and Canola Cash Cover Crops to Provision Pollinators. Ind. Crops Prod. 2015, 75, 20–25. [Google Scholar] [CrossRef]
  144. Thom, M.D.; Eberle, C.A.; Forcella, F.; Gesch, R.; Weyers, S.; Lundgren, J.G. Nectar Production in Oilseeds: Food for Pollinators in an Agricultural Landscape. Crop Sci. 2016, 56, 727–739. [Google Scholar] [CrossRef]
  145. Thom, M.D.; Eberle, C.A.; Forcella, F.; Gesch, R.; Weyers, S. Specialty Oilseed Crops Provide an Abundant Source of Pollen for Pollinators and Beneficial Insects. J. Appl. Entomol. 2018, 142, 211–222. [Google Scholar] [CrossRef]
  146. Amy, C.; Noël, G.; Hatt, S.; Uyttenbroeck, R.; Van De Meutter, F.; Genoud, D.; Francis, F. Flower Strips in Wheat Intercropping System: Effect on Pollinator Abundance and Diversity in Belgium. Insects 2018, 9, 114. [Google Scholar] [CrossRef] [Green Version]
  147. Gallai, N.; Salles, J.-M.; Settele, J.; Vaissière, B.E. Economic Valuation of the Vulnerability of World Agriculture Confronted with Pollinator Decline. Ecol. Econ. 2009, 68, 810–821. [Google Scholar] [CrossRef]
  148. Junqueira, C.N.; Pereira, R.A.S.; da Silva, R.C.; Alves Cardoso Kobal, R.O.; Araújo, T.N.; Prato, A.; Pedrosa, J.; Martínez-Martínez, C.A.; Castrillon, K.P.; Felício, D.T.; et al. Do Apis and Non-Apis Bees Provide a Similar Contribution to Crop Production with Different Levels of Pollination Dependency? A Review Using Meta-Analysis. Ecol. Entomol. 2021, 47, 76–83. [Google Scholar] [CrossRef]
  149. Rollin, O.; Garibaldi, L.A. Impacts of Honeybee Density on Crop Yield: A Meta-Analysis. J. Appl. Ecol. 2019, 56, 1152–1163. [Google Scholar] [CrossRef]
  150. Page, M.L.; Nicholson, C.C.; Brennan, R.M.; Britzman, A.T.; Greer, J.; Hemberger, J.; Kahl, H.; Müller, U.; Peng, Y.; Rosenberger, N.M.; et al. A Meta-Analysis of Single Visit Pollination Effectiveness Comparing Honeybees and Other Floral Visitors. Am. J. Bot. 2021, 108, 2196–2207. [Google Scholar] [CrossRef]
  151. Wolowski, M.; Ashman, T.-L.; Freitas, L. Meta-Analysis of Pollen Limitation Reveals the Relevance of Pollination Generalization in the Atlantic Forest of Brazil. PLoS ONE 2014, 9, e89498. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  152. Bishop, J.; Nakagawa, S. Quantifying Crop Pollinator Dependence and Its Heterogeneity Using Multi-Level Meta-Analysis. J. Appl. Ecol. 2021, 58, 1030–1042. [Google Scholar] [CrossRef]
  153. Cooley, H.; Vallejo-Marín, M. Buzz-Pollinated Crops: A Global Review and Meta-Analysis of the Effects of Supplemental Bee Pollination in Tomato. J. Econ. Entomol. 2021, 114, 505–519. [Google Scholar] [CrossRef] [PubMed]
  154. Westcott, L.; Nelson, D. Canola Pollination: An Update. Bee World 2001, 82, 115–129. [Google Scholar] [CrossRef]
  155. Adegas, J.E.B.; Nogueira Couto, R.H. Entomophilous Pollination in Rape (Brassica Napus L Var Oleifera) in Brazil. Apidologie 1992, 23, 203–209. [Google Scholar] [CrossRef] [Green Version]
  156. Sabbahi, R.; de Oliveira, D.; Marceau, J. Does the Honeybee (Hymenoptera: Apidae) Reduce the Blooming Period of Canola? J. Agron. Crop Sci. 2006, 192, 233–237. [Google Scholar] [CrossRef]
  157. Mesquida, J.; Renard, M.; Pierre, J.-S. Rapeseed (Brassica Napus) Productivity: The Effect of Honeybees (Apis Mellifera L.) and Different Polination Conditions in Cage and Field Tests. Apidologie 1988, 19, 51–72. [Google Scholar] [CrossRef] [Green Version]
  158. Habekotté, B. Options for Increasing Seed Yield of Winter Oilseed Rape (Brassica Napus L.): A Simulation Study. Field Crops Res. 1997, 54, 109–126. [Google Scholar] [CrossRef]
  159. Kitashiba, H.; Nasrallah, J.B. Self-Incompatibility in Brassicaceae Crops: Lessons for Interspecific Incompatibility. Breed Sci. 2014, 64, 23–37. [Google Scholar] [CrossRef] [Green Version]
  160. Gómez, J.M. Effectiveness of Ants as Pollinators of Lobularia Maritima: Effects on Main Sequential Fitness Components of the Host Plant. Oecologia 2000, 122, 90–97. [Google Scholar] [CrossRef]
  161. Picó, F.X.; Retana, J. The Flowering Pattern of the Perennial Herb Lobularia Maritima: An Unusual Case in the Mediterranean Basin. Acta Oecologica 2001, 22, 209–217. [Google Scholar] [CrossRef]
  162. Garibaldi, L.A.; Steffan-Dewenter, I.; Winfree, R.; Aizen, M.A.; Bommarco, R.; Cunningham, S.A.; Kremen, C.; Carvalheiro, L.G.; Harder, L.D.; Afik, O.; et al. Wild Pollinators Enhance Fruit Set of Crops Regardless of Honey Bee Abundance. Science 2013, 339, 1608–1611. [Google Scholar] [CrossRef] [PubMed]
  163. Rader, R.; Bartomeus, I.; Garibaldi, L.A.; Garratt, M.P.D.; Howlett, B.G.; Winfree, R.; Cunningham, S.A.; Mayfield, M.M.; Arthur, A.D.; Andersson, G.K.S.; et al. Non-Bee Insects Are Important Contributors to Global Crop Pollination. Proc. Natl. Acad. Sci. USA 2016, 113, 146–151. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  164. Földesi, R.; Howlett, B.G.; Grass, I.; Batáry, P. Larger Pollinators Deposit More Pollen on Stigmas across Multiple Plant Species—A Meta-Analysis. J. Appl. Ecol. 2021, 58, 699–707. [Google Scholar] [CrossRef]
  165. Sutter, L.; Albrecht, M.; Jeanneret, P. Landscape Greening and Local Creation of Wildflower Strips and Hedgerows Promote Multiple Ecosystem Services. J. Appl. Ecol. 2018, 55, 612–620. [Google Scholar] [CrossRef]
  166. Ouvrard, P.; Jacquemart, A.-L. Review of Methods to Investigate Pollinator Dependency in Oilseed Rape (Brassica Napus). Field Crops Res. 2019, 231, 18–29. [Google Scholar] [CrossRef]
  167. Mänd, M.; Williams, I.H.; Viik, E.; Karise, R. Oilseed Rape, Bees and Integrated Pest Management. In Biocontrol-Based Integrated Management of Oilseed Rape Pests; Springer: Berlin/Heidelberg, Germany, 2010; pp. 357–379. [Google Scholar]
  168. Abrol, D.P.; Shankar, U. Pollination in Oil Crops: Recent Advances and Future Strategies. In Technological Innovations in Major World Oil Crops; Springer: Berlin/Heidelberg, Germany, 2012; Volume 2, pp. 221–267. [Google Scholar]
  169. Badenes-Pérez, F.R.; Shelton, A.M. Pest Management and Other Agricultural Practices among Farmers Growing Cruciferous Crops in the Central and Western Highlands of Kenya and the Western Himalayas of India. Int. J. Pest Manag. 2006, 52, 303–315. [Google Scholar] [CrossRef]
  170. Pudasaini, R.; Thapa, R.B.; Tiwari, S. Farmers Perception on Effect of Pesticide on Insect Pollinators at Padampur and Jutpani Vdcs, Chitwan, Nepal. Int. J. Appl. Sci. Biotechnol. 2016, 4, 64–66. [Google Scholar] [CrossRef]
  171. Venturini, E.M.; Drummond, F.A.; Hoshide, A.K.; Dibble, A.C.; Stack, L.B. Pollination Reservoirs for Wild Bee Habitat Enhancement in Cropping Systems: A Review. Agroecol. Sustain. Food Syst. 2017, 41, 101–142. [Google Scholar] [CrossRef]
  172. Phillips, B.B.; Wallace, C.; Roberts, B.R.; Whitehouse, A.T.; Gaston, K.J.; Bullock, J.M.; Dicks, L.V.; Osborne, J.L. Enhancing Road Verges to Aid Pollinator Conservation: A Review. Biol. Conserv. 2020, 250, 108687. [Google Scholar] [CrossRef]
  173. Williams, N.M.; Ward, K.L.; Pope, N.; Isaacs, R.; Wilson, J.; May, E.A.; Ellis, J.; Daniels, J.; Pence, A.; Ullmann, K.; et al. Native Wildflower Plantings Support Wild Bee Abundance and Diversity in Agricultural Landscapes across the United States. Ecol. Appl. 2015, 25, 2119–2131. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  174. Wratten, S.D.; Gillespie, M.; Decourtye, A.; Mader, E.; Desneux, N. Pollinator Habitat Enhancement: Benefits to Other Ecosystem Services. Agric. Ecosyst. Environ. 2012, 159, 112–122. [Google Scholar] [CrossRef]
  175. Martin, E.A.; Dainese, M.; Clough, Y.; Báldi, A.; Bommarco, R.; Gagic, V.; Garratt, M.P.D.; Holzschuh, A.; Kleijn, D.; Kovács-Hostyánszki, A.; et al. The Interplay of Landscape Composition and Configuration: New Pathways to Manage Functional Biodiversity and Agroecosystem Services across Europe. Ecol. Lett. 2019, 22, 1083–1094. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  176. Badenes-Pérez, F.R. Trap Crops and Insectary Plants in the Order Brassicales. Ann. Entomol. Soc. Am. 2019, 112, 318–329. [Google Scholar] [CrossRef]
Figure 1. PRISMA flow diagram.
Figure 1. PRISMA flow diagram.
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Figure 2. Percentage of publications showing an increased, decreased, and neutral effect of insect pollination on seed yield measured as seed weight/(plant, area, or open flower) (Y); weight of seeds (1, 100, or 1000 seeds) (WS); silique set (SQS); number of siliquae/(plant or area) (NSQ); number of seeds/(silique or open flower) (NSSQ); silique length (SQL); number of seeds/(area, plant, or branch) (NSP); seed germination (G), and oil content (O). An increased, decreased, or neutral effect is shown in red, blue, or green, respectively, in self-compatible (A) and self-incompatible Brassicaceae crops (B).
Figure 2. Percentage of publications showing an increased, decreased, and neutral effect of insect pollination on seed yield measured as seed weight/(plant, area, or open flower) (Y); weight of seeds (1, 100, or 1000 seeds) (WS); silique set (SQS); number of siliquae/(plant or area) (NSQ); number of seeds/(silique or open flower) (NSSQ); silique length (SQL); number of seeds/(area, plant, or branch) (NSP); seed germination (G), and oil content (O). An increased, decreased, or neutral effect is shown in red, blue, or green, respectively, in self-compatible (A) and self-incompatible Brassicaceae crops (B).
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Figure 3. Forest plot of meta-analysis for the effect of insect pollination on seed yield in self-compatible (A) and self-incompatible Brassicaceae crops (B).
Figure 3. Forest plot of meta-analysis for the effect of insect pollination on seed yield in self-compatible (A) and self-incompatible Brassicaceae crops (B).
Agriculture 12 00446 g003aAgriculture 12 00446 g003b
Figure 4. Forest plot of meta-analysis for the effect of insect pollination on the weight of seeds in self-compatible (A) and self-incompatible Brassicaceae crops (B). In some cases B. napus and B. oleracea have been abbreviated as B. na. and B. oler., respectively, to avoid overlapping with error bars and squares.
Figure 4. Forest plot of meta-analysis for the effect of insect pollination on the weight of seeds in self-compatible (A) and self-incompatible Brassicaceae crops (B). In some cases B. napus and B. oleracea have been abbreviated as B. na. and B. oler., respectively, to avoid overlapping with error bars and squares.
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Figure 5. Forest plot of the meta-analysis for the effect of insect pollination on the silique set in self-compatible (A) and self-incompatible Brassicaceae crops (B). In the plots, B. oleracea and C. sativa are abbreviated to B. oler. and C. sa., respectively, to prevent overlapping with error bars and squares.
Figure 5. Forest plot of the meta-analysis for the effect of insect pollination on the silique set in self-compatible (A) and self-incompatible Brassicaceae crops (B). In the plots, B. oleracea and C. sativa are abbreviated to B. oler. and C. sa., respectively, to prevent overlapping with error bars and squares.
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Figure 6. Forest plot of the meta-analysis for the effect of insect pollination on the number of siliquae/plant or area in self-compatible (A) and self-incompatible Brassicaceae crops (B). In some cases, B. juncea and B. napus were abbreviated to B. jun. and B. na., respectively, to avoid overlapping with error bars and squares.
Figure 6. Forest plot of the meta-analysis for the effect of insect pollination on the number of siliquae/plant or area in self-compatible (A) and self-incompatible Brassicaceae crops (B). In some cases, B. juncea and B. napus were abbreviated to B. jun. and B. na., respectively, to avoid overlapping with error bars and squares.
Agriculture 12 00446 g006aAgriculture 12 00446 g006b
Figure 7. Forest plot of the meta-analysis for the effect of insect pollination on the number of seeds per silique in self-compatible (A) and self-incompatible Brassicaceae crops (B). In some cases, B. oleracea has been abbreviated to B. oler. to prevent overlapping with error bars and squares.
Figure 7. Forest plot of the meta-analysis for the effect of insect pollination on the number of seeds per silique in self-compatible (A) and self-incompatible Brassicaceae crops (B). In some cases, B. oleracea has been abbreviated to B. oler. to prevent overlapping with error bars and squares.
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Table 3. Heterogeneity statistics and publication bias based on Begg and Mazumdar rank correlation for the meta-analyses conducted to test the effect of insect pollination on yield parameters in self-compatible (SC) and self-incompatible (SI) Brassicaceae. The yield parameters included in the meta-analysis were seed yield measured as seed weight/(plant, area, or open flower) (Y); weight of seeds (WS); silique set (SQS); number of siliquae/(plant or area) (NSQ); and number of seeds/(silique or open flower) (NSSQ).
Table 3. Heterogeneity statistics and publication bias based on Begg and Mazumdar rank correlation for the meta-analyses conducted to test the effect of insect pollination on yield parameters in self-compatible (SC) and self-incompatible (SI) Brassicaceae. The yield parameters included in the meta-analysis were seed yield measured as seed weight/(plant, area, or open flower) (Y); weight of seeds (WS); silique set (SQS); number of siliquae/(plant or area) (NSQ); and number of seeds/(silique or open flower) (NSSQ).
Yield Parameter and Breeding SystemHeterogeneity StatisticsBegg and Mazumdar Rank Correlation
Tau2SEdfI2Qp-ValueValuep-Value
Y SC0.1450.302627.36%7.2400.2990.0481.000
Y SI31.66014.9881097.75%153.147<0.0010.4180.087
WS SC0.6610.4761065.37%41.585<0.0010.0910.761
WS SI251.094122.948999.83%288.722<0.0010.6000.017
SQS SC4.5862.1401194.68%96.480<0.0010.4240.063
SQS SI9.9145.783794.98%127.520<0.0010.7140.014
NSQ SC6.8883.3191195.21%251.043<0.0010.4850.031
NSQ SI111.37656.969899.59%1197.316<0.0010.5000.075
NSSQ SC2.1490.7052298.03%778.747<0.0010.0990.530
NSSQ SI7.9283.1931598.53%294.886<0.0010.4670.011
Table 4. Insect pollinators of crops of the family Brassicaceae. Abbreviations for pollinators are as follows: Apidae of the genus Apis (A), other Apidae different than Apis spp. (OA), Andrenidae (An), Bibionidae (B), Calliphoridae (C), Coccinellidae (Co), Colletidae (Col), Empididae (E), Formicidae (F), Halictidae (H), Megachillidae (M), Muscidae (Mu), Pieridae (P), Scarabaeidae (S), Sepsidae (Se), Stratiomyidae (St), Syrphidae (Sy), Tabanidae (T), and Vespidae (V). Abbreviations for countries are as follows: Australia (A), Bangladesh (B), Belgium (Be), Brazil (Br), China (C), France (F), Germany (G), India (I), Ireland (Ir), Nepal (N), New Zealand (NZ), Pakistan (P), Sweden (S), United Kingdom (UK), and United States of America (US).
Table 4. Insect pollinators of crops of the family Brassicaceae. Abbreviations for pollinators are as follows: Apidae of the genus Apis (A), other Apidae different than Apis spp. (OA), Andrenidae (An), Bibionidae (B), Calliphoridae (C), Coccinellidae (Co), Colletidae (Col), Empididae (E), Formicidae (F), Halictidae (H), Megachillidae (M), Muscidae (Mu), Pieridae (P), Scarabaeidae (S), Sepsidae (Se), Stratiomyidae (St), Syrphidae (Sy), Tabanidae (T), and Vespidae (V). Abbreviations for countries are as follows: Australia (A), Bangladesh (B), Belgium (Be), Brazil (Br), China (C), France (F), Germany (G), India (I), Ireland (Ir), Nepal (N), New Zealand (NZ), Pakistan (P), Sweden (S), United Kingdom (UK), and United States of America (US).
Plant Number of studies reporting main pollinators in a given family CountriesReferences
AOAAnBCCoCollEFHMMuPSSeStSyTV
B. carinata3-2----------------I, US[31,40,50]
B. juncea1444--1--1312--1-3-1B, I[31,40,52,54,56,58,118,119,120,121,122,123,124,125,126]
B. napus1284-1--1-2112---4--Be, Br, C, F, G, I, Ir, UK, P, S[20,31,33,40,66,67,127,128,129,130,131,132,133]
B. oleracea812------2------2--I[31,91,93,134,135,136,137,138]
B. rapa1153--12--31--2-171-A, I, N, NZ, P[15,31,40,97,103,104,115,116,117,120,139,140,141,142]
C. sativa2-1------2------2--Be, G, US[38,143,144,145,146]
E. sativa312-------------1--I, P[31,40,141]
R. sativus4-2------1------1--I, P[31,40,107,108]
S. alba2-2----------------I[31,40]
Total 591922112211133322112011
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Badenes-Pérez, F.R. Benefits of Insect Pollination in Brassicaceae: A Meta-Analysis of Self-Compatible and Self-Incompatible Crop Species. Agriculture 2022, 12, 446. https://doi.org/10.3390/agriculture12040446

AMA Style

Badenes-Pérez FR. Benefits of Insect Pollination in Brassicaceae: A Meta-Analysis of Self-Compatible and Self-Incompatible Crop Species. Agriculture. 2022; 12(4):446. https://doi.org/10.3390/agriculture12040446

Chicago/Turabian Style

Badenes-Pérez, Francisco Rubén. 2022. "Benefits of Insect Pollination in Brassicaceae: A Meta-Analysis of Self-Compatible and Self-Incompatible Crop Species" Agriculture 12, no. 4: 446. https://doi.org/10.3390/agriculture12040446

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