, Volume 49, Issue 1, pp 101–111 | Cite as

Contribution of honeybees to soybean yield

  • Diego Cesar BlettlerEmail author
  • Guillermina Andrea FAGÚNDEZ
  • Octavio Pedro CAVIGLIA
Original article


Despite the economic importance of soybean [Glycine max (L.) Merr.], knowledge on the contribution of entomological pollination on seed yield is scarce. This study estimates the production of soybean resulting from pollination by honeybees (Apis mellifera L.) in two consecutive growing seasons in Paraná (Argentina). Experiments had two treatments: excluded flower-visiting insects (EV) and non-excluded flower-visiting insects (NEV). The abundance of honeybees was similar in both years, although soybean production differed significantly (P < 0.05) between years. The NEV treatment out-yielded (P < 0.001) the EV treatment by 18% (5224 vs. 4415 kg ha−1) in year 1, which was associated with an increase in the seeds per unit area but not with individual seed weight. In contrast, seed yield (on average 3830 kg ha−1) and seeds per unit area did not differ between treatments in year 2. Individual seed weight was 3–5% (P < 0.05) higher in EV than in NEV in both years. The mechanisms involved in the seed yield increase could be related with pollen sterility in relegated flowers in secondary racemes or in distal locations of primary racemes under favorable conditions, as recorded in year 1. Thus, the action of honeybees carrying pollen from fertile flowers to relegated flowers may have increased the pod and seed set in treatment NEV in year 1.


pollination foraging hours seed yield soybean honeybees 

1 Introduction

Although soybean is essentially an autogamous species (McGregor 1976; Carlson and Lersten 1987; Ahrent and Caviness 1994), it is also cross-pollinated mainly by flower-visitor insects (Erickson et al. 1978). Insect pollination, under certain conditions, has contributed to increasing seed yield (Juliano 1976; Moreti et al. 1993; Chiari et al. 2005, Chiari et al. 2008; Milfont et al. 2013; Santos et al. 2013). The increases in soybean seed yield were associated with genotypes that are attractive to bees and with respect to distance from colonies (Erickson et al. 1978). It is, however, still unclear why insect pollination sometimes results in higher seed yields. The movements of the insect for promoting the auto pollination, i.e., self-pollination mediated by insects, or carrying pollen to improve the cross-pollination have been proposed as possible mechanisms involved in the seed yield improvements (Free 1993). Moreover, a study has shown that the action of insects visiting flowers to maximize the auto pollination seems to increase seed or fruit production, even in obligatory autogamous species (Aizen 2008). Likewise, the action of insects carrying pollen from fertile to androsterile plants, which can be in a variable proportion within a crop, has been proposed as an additional mechanism involved in the increase in the number of reproductive structures in autogamous plants (Ortiz-Pérez et al. 2006).

Honeybees are the most abundant and frequent flower-visiting insects of soybean (Delaplane and Mayer 2000), although other hymenoptera (Milfont et al. 2013; Fujita et al. 1997; Monasterolo et al. 2015; Santos et al. 2013), as well as diptera and coleoptera are also regular flower-visiting insects (Santos et al. 2013; Fagúndez et al. 2016). Accordingly, several palynological studies have demonstrated that soybean is an important nectariferous resource for production of honey by honeybees (Fagúndez and Caccavari 2003; Fagúndez et al. 2016; Gallez et al. 2005; Fagúndez 2016), even resulting in a monofloral honey of soybean in some cases (Fagúndez 2016). Moreover, soybean has been reported as the most important source of pollen for honeybee colonies during peak flowering (Fagúndez and Caccavari 2003). These results suggest that soybean is an important resource for the nutrition of honeybees and for honey production, which is especially true in the agriculture of Argentina, where ca. 70% of the cultivated area is planted with soybean (SIIA 2015). Some soybean genotypes, however, are not attractive enough to honeybees, possibly due to low sugar concentration in their nectar, among other factors (Alves et al. 2010).

Despite the economic importance of soybean, knowledge is scarce on the effect of entomological pollination on seed yield. This could be critical, since the density and diversity of wild pollinators has declined (Garibaldi et al. 2013), with the reduction of habitats providing nesting and foraging resources outside the crop flowering period (Aizen et al. 2009; Garibaldi et al. 2011). In this context, managed honeybees may be a valuable alternative to the replacement of wild pollinators and to improve soybean yields.

We hypothesized that (i) honeybee pollination improves soybean seed production, and (ii) increased honeybee flower visitation rate improves soybean seed production. The objective of this study was to estimate the impact of pollination by honeybees on soybean seed yield.

2 Materials and methods

2.1 Experiment and husbandry conditions

The study was carried out during two consecutive growing seasons (2010–2011 and 2011–2012, hereafter year 1 and year 2, respectively) on soybean fields in Paraná, Argentina (31° 50 ′S and 60° 31 ′W, 91 m above sea level). The fields, which are 1000 m apart, had 23 ha in year 1 and 20 ha in year 2 and both had oat (Avena sativa L.) as the previous crop. Soybean crops were sown in rows, 0.53 m apart, on 5 November in year 1 and on 2 November in year 2. Seeding rate was 27 seeds per meter and the genotype used was Nidera A 4990 RG (maturity group IV, glyphosate resistant, indeterminate growing habit). This genotype is one of the most widely used in the region.

The population of phytophagous insects was monitored weekly, and it was always below the economic injury threshold (Baigorri 2004) during the flowering and seed set period, i.e., from R1 (beginning bloom) to R6 (full seed) (Fehr and Caviness 1977). Insects were collected and counted each week from 15 samples of 0.5 m2 of crop canopy.

The experiment had a completely randomized design and included two treatments with ten replicates each. One treatment excluded visitor insects, hereafter EV (excluded flower-visiting insects), by using a net (brand Claril, mesh 4 × 1 mm with shading < 15%) assembled on a metallic structure (see Fig. 1a). In the other treatment, although flower-visiting insects had free access to the crop (non-excluded flower-visiting insects (NEV)), plots were also covered with the net but only at the top of the structure, in order to account for the shading effect, but not at the side of plots in order to allow the freedom of action of the honeybees (see Fig. 1b). Each plot, defined by the metallic structure, was 2 m long and three rows wide (1.58 m). Plots were established on 21 December in year 1 and 14 December in year 2.
Fig. 1.

Metallic structures supporting the net in: a excluded flower-visiting insects (EV) and b non-excluded flower-visiting insects (NEV) plots c shows the location of several plots location at Paraná, Argentina. NEV plots allow insect visits while maintaining identical shading conditions to EV plots.

To ensure an adequate population of honeybees (Apis mellifera ligustica), 36 colonies were placed in the middle line of each field at R2 (full bloom) stage. Plots were established in regular alternance along the sides of the line of colonies (see Fig. 1c), in order to increase the action of honeybees and to reduce the influence of competitive sources of flowers, i.e., a dilution effect.

Colonies were standardized in their size and management. Young queens of Apis mellifera ligustica (Italian bees) were used and sanitary treatments were performed to prevent varroasis (Varroa destructor), American (Paenibacillus larvae) and European foulbrood disease (Melissococcus pluton) in the colonies. Each colony had six frames in the deep super and all hives were new each year. The estimated population was 20,000 bees per hive.

2.2 Measurements

Crop phenology, from planting to physiological maturity, was recorded weekly within the plots using the scale of Fehr and Caviness (1977) on ten consecutive plants. Seed yield was determined after physiological maturity (R8) by cutting all plants at the ground level on an area of 1.6 m2, and then manually threshing. Individual seed weight was determined from a sample of the threshed seeds by counting 1000 seeds. Soybean yield was expressed as seed yield per ha at 0.135 kg−1 moisture.

During the flowering period, i.e., from R2 (full bloom) to R4 (full pod), the activity of honeybees was monitored every 4 days at 09h30, 12h30, and 16h00 around each plot by sweeping 50 times an entomological net of 0.11 m2. The time for the monitoring was chosen in following several authors who agree that the period for bee foraging in soybean is 6 h before or after noon (Erickson et al. 1978; Mahfouz et al. 2012; Blettler et al. 2016). The captured honeybees were bagged until counting. Only the number of honeybees (Apis mellifera L.) was recorded and other flower-visiting insects were neither identified nor quantified. Meteorological data were obtained from the agrometeorological station of INTA EEA Paraná located at ca. 1.000 m.

2.3 Estimation of seed yield

As is usual in studies of soybean seed yield determination (Egli 1998; Sadras and Calviño 2001), we studied the two main seed yield components, i.e., the seed number per unit area (seed m−2) and the individual seed weight (mg seed−1) (Egli 2004; Egli and Zhen-wen 1991). This approach allows to infer the role of honeybees in the set of seed number per unit area, which is more related with the number of flowers converted in pods than with the seed yield itself. Moreover, the seed yield in soybean may be strongly affected by the individual seed weight, irrespective of the seed number (Borrás et al. 2004).

Seed number per unit area, i.e., m2, was calculated as the quotient between seed yield and individual seed weight. The abundance of honeybees was expressed as the average number of insects captured in a sweep.

2.4 Estimation of flower visitation rate

We estimated the flower visitation rate following Goodwin et al. (2011) for white sweet clover (Trifolium repens L.). Firstly, we estimated the number of flowers per unit area based on the seed number per unit area. Based on our field observations, we assumed that each pod, i.e., a fertilized flower converted into a fruit, had 2.5 seeds. Thus, the number of fertile flowers per unit area in each year was estimated as the quotient between the seed number per unit area and 2.5. Then, we assumed a flower abortion rate of 60% (van Schaik and Probst 1958; Hansen and Shibles 1978; Jiang and Egli 1993) to estimate the number of flowers per unit area, i.e., the quotient between the number of fertile flowers per unit area and 0.6. Taking into account the duration of the flowering period, i.e., 31 days in year 1 and 28 days in year 2, we estimated the daily flowering average as the quotient of the total number of flowers per unit area and the duration of the flowering period. This estimation yielded 110 flowers per m−2 d−1 in year 1 and 102 flowers per m−2 d−1, which are consistent with previous reports (McGregor 1976). Considering the size of the used entomological sweep net, we estimated 25 m3 of total volume of interception in the crop canopy, which was considered equivalent to 50 m2 because flowers were displayed in only ca. 0.5 m plant height (from 0.15 to 0.65 m height). The number of honeybees per unit area was calculated from the ratio between the total number of captured honeybees and the area swept with the net.

Honeybee flower visitation rate for soybean has been reported at 12 flowers per min (Chiari et al. 2005); therefore, the estimated flower visitation rate was 130 visits m−2 d−1. This rate was higher than the estimated flowering rate for the considered period, which suggests that the number of honeybees in our experiment was enough to ensure the visitation of the available flowers.

2.5 Environmental conditions

A water balance was performed for each year, at a daily step, from crop evapotranspiration (ET), rainfall, and plant available water (PAW). The ET was calculated as the product between reference ET and phenology-dependent crop coefficients (Allen et al. 1998). Actual evapotranspiration was assumed to be equal to ET when PAW > 0.5, and to decline linearly with PAW between 0 and 0.5 (Sadras and Milroy 1996). Further details of water budget calculations can be found in Sadras and Calviño (2001). The initial PAW was assumed to be 0.5 as a fraction for each year.

Mean temperature during the critical period for seed set, i.e., from R3 (beginning pod) to R6 (full seed), was similar in both years. However, it was higher during seed filling, i.e., the period between R6 and physiological maturity, in year 1 (Fig. 2a). Likewise, global solar radiation was similar between years during the critical period but it was higher during seed filling in year 1 (Fig. 2b).
Fig. 2.

Mean temperature (a), global radiation (b) and plant available water (c) during growing seasons 2010/2011 (year 1) and 2011/2012 (year 2) at Paraná, Argentina. Arrows indicate R3 (onset of pod formation) and R5 (onset of seed filling period), two key phenological stages of the soybean crop. Horizontal broken line in (c) indicates the threshold of 30% plant available water.

Despite the higher total rainfall during the growing seasons in year 2 (563 mm) than in year 1 (441 mm), the fraction of plant available water was below the threshold of 30% during the critical period for seed set, i.e., from R3 to R6, during year 2 (Fig. 2c), which was associated to the higher rainfall during this period (193 mm for year 1 vs. 100 mm for year 2).

2.6 Statistical analyses

We used a general linear mixed-model (GLMM-ANOVA) to evaluate the effects of treatments and years on soybean seed yield, seed number per unit area, and individual seed weight. The linear model included year and replicates as random effects, whereas treatment was included as a fixed effect. We compared flower visitation rate and activity of honeybees between years using a one-tailed Student’s t test. Statistical analysis of this study was performed by INFOSTAT (Di Rienzo et al. 2011). When the ANOVA indicated significant differences (P < 0.05), we compared the treatment means using the Tukey test (α = 0.05).

3 Results

3.1 Activity of honeybees and flower visitation rate

The activity of honeybees at different hours of the day did not differed between years (P > 0.05). The most intense activity was recorded at 12h30 (Fig. 3). The amount of captured individuals at 12h30 was, on average, 2.4-fold higher than at 09h30 and 13.7-fold higher than at 16h00 (Fig. 3). We estimated 0.03 honeybees m−2 and an average daily visitation rate of 130 visits m−2 d−1; both variables did not differ significantly between years (P > 0.05).
Fig. 3.

Average number of honeybees captured per sweep, over soybean flowering period of each year. Vertical segments over bars indicate the standard deviation of the mean for the flowering period.

3.2 Soybean seed yield

There were significant effects of treatment (P = 0.003), year (P < 0.0001), and the interaction treatment ×year (P < 0.0001) on seed yield (Table I). In year 1, treatment non-excluded flower-visiting insects (NEV) out-yielded treatment (EV) by 18% (Table II) in contrast with year 2, where the seed yield was similar between both treatments. On average, seed yield was 26% higher in year 1 than in year 2. Similarly, seed number per unit area was 12% higher in NEV than in EV in year 1 (Table II), without significant differences in year 2. Seed weight was significantly increased by EV treatment in both years (Table I). Irrespective of year, seed weight was 3.5% higher (P < 0.0001) when flower-visiting insects were excluded in comparison with NEV treatment. Seed weight was 14% higher in year 1 than in year 2 (Table II).
Table I

Analysis of variance of year, treatment, and the interaction year × treatment for soybean seed yield, seed number per unit area and individual seed weight in an experiment carried out in Paraná, Argentina during two consecutive growing seasons.


P value

Source of variation

Seed yield

Seed number

Seed weight


< 0.0001

< 0.0001

< 0.0001


< 0.0001

< 0.0001

< 0.0001



< 0.0001


Year × treatment

< 0.0001

< 0.0001


Table II

Average seed yield, seed number per unit area and individual seed weight in treatments having excluding (EV) and non-excluding flower-visiting insects (NEV) during two consecutive growing seasons in Paraná, Argentina


Seed yield (g m−2)


Seed number (Seeds m−2)


Seed weight (mg seed−1)


Year 1


522.4 ± 41


3407 ± 144


153 ± 6



441.5 ± 30


2795 ± 188


158 ± 5


Year 2


377.6 ± 41


2842 ± 318


133 ± 6



388.4 ± 24


2769 ± 152


140 ± 5


Bracketed values beside means indicate the standard deviation. Different letters besides means within a year indicate significant differences according to the Tukey test (α = 0.05)

4 Discussion

In agreement with our first hypothesis, seed yield increase in NEV treatment as compared with EV treatment in year 1, which is coincident with what was reported by several previous studies (Table III). However, the results of the year 2 did not show the same effect of NEV on seed yield (Table I), i.e., seed yield was unaffected by treatments.
Table III

Documented changes in soybean seed yield attributed to the effect of honeybees and/or others flower-visiting insects


Seed yield change (%)


Erickson et al. (1978)

+ 15


Chiari et al. (2005)

+ 57

Honeybees and others visitors

Chiari et al. (2008)

+ 38


Milfont et al. (2013)

+ 18


Santos et al. (2013)

+ 25

Honeybees and others visitors

Kengni et al. (2015)

+ 36


A wide range of the impact of honeybees on soybean seed yield has been reported (Table III) in the related body of literature, for instance, Erickson (1975, 1984) reported an increase from 5 to 20% depending on the year, whereas Chiari et al. (2005) reported a seed yield increase as high as 57%.

Although the fixed effects of our treatments were identical in both years, the meteorological conditions during the critical period for seed set differed between years (Fig. 2). Therefore, seed yield was higher in year 2 than in year 1 due to the more favorable environmental conditions, particularly regarding PAW (Fig. 2c). Our results, in consequence, suggest a more important impact of pollination by honeybees when environmental conditions promote higher yields.

The most critical period for seed set in soybean spans from R3 to R6, where flowering, pod, and seed formation are overlapping (Board and Tan 1995; Egli and Zhen-wen 1991; Jiang and Egli 1995; Egli 1997). As a consequence, formation and abortion of flowers and pods and seeds set occurs simultaneously during this critical period, the duration of which varies depending on temperature, photoperiod, and genotype sensibility to these factors. Although the flower, pod and seed abortion processes are still not completely understood, distal flowers of primary racemes as well as secondary racemes are more likely to abort, than those which are located close to the node (Egli and Bruening 2006). The position of distal flowers of primary racemes or secondary racemes, in terms of assimilate (supply of nutrients) partitioning in the plant, determine a lower assimilate flux to the formation of flower parts (Egli 1998, 1999, 2004; Borrás et al. 2004; Egli and Bruening 2006), which can be derived in a deficient pollen formation. Thus, the action of honeybees carrying pollen from fertile flowers to relegated flowers in secondary racemes or in distal locations of primary racemes may have increased the pod and seed set in treatment NEV in year 1. Such a mechanism was not effective in year 2 (Table I) due to the low PAW-affected crop growth, which reduced the assimilate availability to seed set, i.e., even when pollen transfer could be effective in year 2, there were not enough plant assimilates to sustain the seed growth. This mechanism, however, needs to be more deeply addressed in further research, since to the best of our knowledge there are no previous studies available to confirm both: (i) the pollen sterility in relegated locations in racemes and (ii) the feasibility to fertilize these flower with fertile pollen in order to induce pod and seed formation.

Also, another possible mechanism to explain the contrasting response of our treatments could be related with the proportion of androsterile individuals within the population. In fact, some spontaneous mutations may result in some androsterile individuals in soybean, as reported by Graybosch and Palmer (1988) and Palmer et al. (2004), which has been suggested as having a higher probability of being frequent when a genotype is successively replicated after its release. These mutations may be favored by several environmental factors such as extreme temperatures, drought, and nutrient deficiency (Davis 2000), which suggest a differential proportion of individuals among years. These androsterile individuals will only set seeds when available pollen reach the stigmas, which becomes feasible only with the action of flower-visiting insects (Ortiz-Pérez et al. 2006).

Another mechanism, although less plausible than the previous mechanisms, has been suggested to be important in seed yield improvement as affected by the action of flower-visiting insects in soybean. It is stated that with this mechanism, the action of honeybees in increases the seed set which is related with a better pollen distribution on the stigmatic surface, due to the intimate contact between the abdominal portion of the insect with the receptive structure of the flower (Milfont et al. 2013). This mechanism does not include the androsterility as a factor, but is focused on hypothetical failures of fertile pollen in reaching the stigma surface.

The increase of seed number per unit area promoted by honeybees’ pollination was similar to the increase in seed yield (Table II), which is consistent with examples in the body of literature (Erickson 1975; Juliano 1976; Erickson et al. 1978; Chiari et al. 2005), where seed yield is always related to seed and pod number per unit yield. However, the seed weight decreased in the NEV treatments as compared with the EV treatments (Table II). Similarly, a negative influence of flower-visiting insects has been reported by other authors (Delaplane and Mayer 2000; Alencar Arnaut de Toledo et al. 2011).

Although seed weight is frequently reported as being less variable than seed number per unit area, an important variation in seed weight may be anticipated when important changes in the source/sink (assimilate availability per seed) relationship occurs (Borrás et al. 2004). In fact, when the assimilate availability per seed is reduced by a higher seed number per unit area under a similar environment for seed fill a reduction of seed weight may be anticipated. Thus, in NEV treatments an important (year 1) or a negligible (year 2) change in seed number per unit area may have reduced the assimilate availability per seed leading to the reported seed weight reduction (Table II).

Notwithstanding, flower visitation rate was similar between years, and seed yield was not increased by NEV treatment in year 2 (Table II). Thus, honeybee activity had not necessarily improved soybean seed production, which is in contrast with our second hypothesis. The more restrictive environmental conditions for crop growth during the critical period of seed set in year 2 surely underlie this result as discussed above. Although, to the best of our knowledge, there are no previous reports on the attractiveness for honeybees of the used cultivar, our estimated flower visitation rate was higher than the flowering rate (see Materials and methods section), provided a rough indication of this genotype feature. This could be a valuable consideration for further research, since variability in attractiveness for honeybees has been reported (Chiari et al. 2005).

5 Conclusions

Soybean production in plots where flower-visiting insects were not excluded was higher than in plots where flower-visiting insects were excluded in year 1, when favorable environmental conditions occurred. The yield increase associated to honeybee visitation was positively related with seed number per unit area and negatively related with individual seed weight. Collectively, our results suggest an important role of honeybees in increasing the seed number per unit area of soybean under high yielding conditions.

The mechanisms involved in the seed yield increase were not revealed, but we suggested a possible way, related with pollen sterility in relegated flowers within the racemes under favorable conditions, for a high seed set.



This work was funded by UADER, CONICET, and COFECyT. GAF and OPC are members of CONICET, the Research Council of Argentina. We acknowledge the valuable comments of the reviewers and editors, particularly comments made by reviewer #3, which contribute remarkably to improving this work.


DB, GF, and OC conceived this research and designed experiments, participated in the design and interpretation of the data. All authors read and approved the final manuscript.


  1. Ahrent, D. K., Caviness, C. E. (1994) Natural cross-pollination of twelve soybean cultivars in Arkansas. Crop Sci. 34: 376–378.CrossRefGoogle Scholar
  2. Aizen, M. A. (2008) Long-term global trends in crop yield and production reveal no current pollination shortage but increasing pollinator dependency. Curr. Biol. 18: 1572–1575.CrossRefPubMedGoogle Scholar
  3. Aizen, M. A., Garibaldi, L. A., Dondo, M. (2009) Expansión de la soja y diversidad de la agricultura argentina. Ecol. Austral. 19: 45–54.Google Scholar
  4. Alencar Arnaut de Toledo, V., Malerbo-Souza, D. C., Selegatto, J. C., Sene Pinto, A., Colla Ruvolo-Takasusuki, M.C., Dechechi Tambó, E. (2011) Biodiversidade de agentes polinizadores e seu efeito na produção de grãos em soja Var. monsoy 3329. Revista Varia Scientia Agrarias 02(01): 123–130.Google Scholar
  5. Allen, R. G., Pereira, L. S., Raes, D., Smith, M. (1998). Crop evapotranspiration: guidelines for computing crop water requirements. FAO Irrigation and drainage paper No. 56, Rome.Google Scholar
  6. Alves, E. M., Toledo, V. A., Oliveira, A. J., Sereia, M. J., Neves, C. A., Ruvolo-Takasusuki, M.C. (2010) Influência de abelhas africanizadas na concentração de açúcares no néctar de soja (Glycine max L. Merrill) var. Codetec 207. Acta Scientiarum Animal Sciences, Maringá, 32 (2): 189–195.Google Scholar
  7. Baigorri, H. E. (2004) Reconocimiento de enfermedades, plagas, malezas y carencias nutricionales de la soja. Ediciones INTA, Buenos Aires, pp 160Google Scholar
  8. Blettler, D., Fagúndez, G., Chémez, M.D. (2016) A study of the foraging schedule of honeybees on soy crops as an agronomical tool to mitigate the effects of agrochemicals. Forensic Sci. Int. 7: 14–28.Google Scholar
  9. Board, J. E., Tan, Q. (1995) Assimilatory capacity effects on soybean yield components and pod number. Crop Sci. 35: 846–851.CrossRefGoogle Scholar
  10. Borrás, L., Slafer G. A., Otegui, M. (2004) Seed dry weight response to source-sink manipulations in wheat, maize and soybean: a quantitative reappraisal. Field Crop Res. 86: 161–146.CrossRefGoogle Scholar
  11. Carlson, J. B., Lersten, N. R. (1987) Reproductive morphology. In: Wilcox, J.R., ed. Soybeans: Improvement, Production and Uses, 2nd ed. Madison: American Soc. Agron.: 97–134.Google Scholar
  12. Chiari, W. C., Toledo, V., Takasusuki, M. C., Attencia, V. M., Martins, F., Kotaka, C., Sakaguti, E. Magalhães, H. R (2005) Pollination of soybean [Glycine max (L.) Merril] by honeybees (Apis mellifera L.). Braz. Arch. Biol. Technol., 48: 31–36.CrossRefGoogle Scholar
  13. Chiari, W. C., Alencar Arnaut de Toledo, V., Hoffmann-Campo C. B., Colla Rúvolo-Takasusuki M. C., Oliveira Arnaut de Toledo T. C., Sousa Lopes, T. (2008) Polinização por Apis mellifera em soja transgênica [Glycine max (L.) Merril] Roundup Ready cv. BRS 245 RR e convencional cv. BRS 133. Acta Sci. Agron, Maringá, 30: 267–271.Google Scholar
  14. Delaplane, K., Mayer, D. (2000) Crop Pollination by Bees. CABI Publishing. p. 344.Google Scholar
  15. Di Rienzo J. A., Casanoves F., Balzarini M. G., Gonzalez L., Tablada M., Robledo C. W. (2011). InfoStat versión 2011. Grupo InfoStat, FCA, Universidad Nacional de Córdoba, Argentina.Google Scholar
  16. Egli, D. B. (1997) Cultivar maturity and response of soybean to shade stress during seed filling. Field Crop Res. 52: 1–8.CrossRefGoogle Scholar
  17. Egli, D. B. (1998) Seed Biology and the Yield of Grain Crops. CAB International, Wallingford. pp. 178.Google Scholar
  18. Egli, D. B. (1999) Variation in leaf starch and sink limitations during seed filling in soybean. Crop Sci. 36: 1361–1368.CrossRefGoogle Scholar
  19. Egli, D. B. (2004) Seed-fill duration and yield of grain crops. Adv. Agron. 83: 243–279.CrossRefGoogle Scholar
  20. Egli D. B., Bruening, W. P. (2006) Fruit development and reproductive survival in soybean: position and age effects. Field Crop Res., 98:195–202.CrossRefGoogle Scholar
  21. Egli, D. B. Zhen-wen, Y.U. (1991) Crop growth rate and seeds per unit area in soybeans. Crop Sci. 31: 439–442.CrossRefGoogle Scholar
  22. Erickson, E. H. (1975) Honey bees and soybeans. Am. Bee J. 115: 351–353.Google Scholar
  23. Erickson, E. H. (1984) Soybean pollination and honey production a research progress report. Am. Bee J. 124: 775–779.Google Scholar
  24. Erickson, E. H., Berger, G. S., Shannon, J. G. (1978) Honey bee pollination increases soybean yields in the Mississippi Delta regions of Arkansas and Missouri. J. Econ. Entomol. 71: 601–603.CrossRefGoogle Scholar
  25. Fagúndez, G. (2016) Botanical and geographical characterisation of honeys in Diamante, Entre Ríos, Argentina. Palynology 40: 308–321.CrossRefGoogle Scholar
  26. Fagúndez, G. A. Caccavari, M. A. (2003) Primeros registros de mieles monofloras y cargas de polen de soja (Glycine max L.) en Argentina. Boletín Apícola Trimestral, SAGPyA 24: 3–6.Google Scholar
  27. Fagúndez, G. A., Blettler, D. C., Krumrick, C. G., Bertos, M. A., Trujillo, C. G. (2016) Do agrochemicals used during soybean flowering affect the visits of Apis mellifera L?. Span. J. Agric. Res., 14: e0301.CrossRefGoogle Scholar
  28. Fehr, W. R. Caviness, C. E. (1977) Stages of soybean development, Ames: Iowa State University, 80.Google Scholar
  29. Free, J. B. (1993) Insect pollination of crops. London. Academic Press, p. 684.Google Scholar
  30. Fujita, R., Ohara, M., Okazaki, K. Shimamoto, Y. (1997) The extent of natural cross-pollination in wild soybean (Glycine soja). J. Hered. 88: 124–128.CrossRefGoogle Scholar
  31. Gallez, L. M., Andrada, A. C., Valle, A. F. Gil, M. E. Continanza, F. G. (2005) Polen de soja (Glycine max L.) en mieles del centro-oeste pampeano. 28° congreso Argentino de Producción Animal. Rev. Argentina de Producción Animal 25: 398–399.Google Scholar
  32. Garibaldi, L. A., Steffan-Dewenter, I., Kremen, C., Morales, J. M., Bommarco, R., Cunningham, S. A., Holzschuh, A. (2011) Stability of pollination services decreases with isolation from natural areas despite honey bee visits. Ecol. Lett. 14: 1062–1072.CrossRefPubMedGoogle Scholar
  33. Garibaldi, L. A., Steffan-Dewenter, I., Winfree, R., Aizen, M. A., Bommarco, R., Cunningham, S. A., Bartomeus, I. (2013) Wild pollinators enhance fruit set of crops regardless of honey bee abundance. Science, 339: 1608–1611.CrossRefPubMedGoogle Scholar
  34. Goodwin, R. M., Cox, H. M., Taylor, M. A., Evans, L. J., McBrydie, H. M. (2011) Number of honey bee visits required to fully pollinate white clover (Trifolium repens) seed crops in Canterbury, New Zealand. N. Z. J. Crop Hortic. Sci.. 39: 7–19.CrossRefGoogle Scholar
  35. Graybosch, R., Palmer, R. (1988) Male sterility in soybean—an overview. Am. J. Bot. 75: 144–156.CrossRefGoogle Scholar
  36. Hansen, W.R., Shibles, R. (1978) Seasonal log of the flowering and podding activity of field-grown soybeans. Agron. J. 70: 47–50.CrossRefGoogle Scholar
  37. Jiang, H., Egli, D.B. (1993) Shade induced changes in flower and pod number and flower and fruit abscission in soybean. Agron. J. 85:221–225.CrossRefGoogle Scholar
  38. Jiang, H., Egli, D. B. (1995) Soybean seed number and crop growth rate during flowering. Agron. J. 87: 264–267.CrossRefGoogle Scholar
  39. Juliano, J. C. (1976) Polinização entomófila na soja. In: Congresso Brasileiro de Apicultura, Curitiba: Convênio Incra/ FAEP, 4: p. 235–239.Google Scholar
  40. Kengni, S.B., Fohouo, F.N.T., Ngakou, A. (2015) Impact of the foraging activity of Apis mellifera adansonii Latreille (Hymenoptera: Apidae) and Bradyrhizobium fertilizer on pollination and yield components of Glycine max L.(Fabaceae) Int. J. Biol. Res. 3: 64–71Google Scholar
  41. Mahfouz, H., Kamel, S., Belal, A., Said, M. (2012) Pollinators visiting sesame (Sesamum indicum L.) seed crop with reference to foraging activity of some bee species. Cercetari Agronomice in Moldova. 45: 49–55.Google Scholar
  42. McGregor, S. E. (1976) Insect pollination of cultivated crop plants. Washington: Agric. Res. Service United States Dept. of Agriculture, p. 411.Google Scholar
  43. Milfont, M. O., Rocha, E. E., Lima, A. O., Freitas, B. M. (2013) Higher soybean production using honeybee and wild pollinators, a sustainable alternative to pesticides and autopollination, Environ. Chem. Lett. 11: 335–341.CrossRefGoogle Scholar
  44. Monasterolo, M., Musicante M. L., Valladares, G. R., Salvo, A. (2015) Soybean crops may benefit from forest pollinators. Agric. Ecosyst. Environ. 202: 217–222.CrossRefGoogle Scholar
  45. Moreti, A. C., Silva, E. C., Alvez, M.L. (1993) Observações iniciais sobre a polinização do girassol (Helianthus annuus L.) efetuada por Apis mellifera L. B. Indústr. anim., Nova Odessa, 50: 31–34.Google Scholar
  46. Ortiz-Pérez, E., Horner, H., Hanlin, S., Palmer, R. (2006) Insect-mediated seed-set evaluation of 21 soybean lines segregating for male sterility at 10 different loci. Euphytica 152:351–360.CrossRefGoogle Scholar
  47. Palmer, R., Pfeifer, T., Buss, R., Killen, T. (2004) Fertility-sterility. Qualitative genetics. Soybeans: improvement, production, and uses. Third Edition. American Society of Agronomy. Madison, Wisconsin. pp. 171–173.Google Scholar
  48. Sadras, V. O., Calviño, P.A. (2001) Quantification of grain yield response to soil depth in soybean, maize, sunflower, and wheat. Agron. J. 93, 577–583.CrossRefGoogle Scholar
  49. Sadras, V. O., Milroy, S.P. (1996) Soil-water thresholds for the responses of leaf expansion and gas exchange: a review. Field Crop Res. 47: 253–266.CrossRefGoogle Scholar
  50. Santos, E., Mendoza, Y., Vera, M., Carrasco-Letelier, L., Díaz, S., Invernizzi, C. (2013) Aumento en la producción de semillas de soja (Glycine max) empleando abejas melíferas (Apis mellifera). Agrociencia 17: 215–224.Google Scholar
  51. SIIA (2015) Ministerio de Agroindustria, Argentina: Presidencia de La Nación. (with acces 10/08/2016).Google Scholar
  52. van Schaik, P.H., Probst, A.H (1958) Effects of some environmental factors on flower production and reproductive efficiency in soybeans. Agron. J. 50:192–197.CrossRefGoogle Scholar

Copyright information

© INRA, DIB and Springer-Verlag France SAS 2017

Authors and Affiliations

  • Diego Cesar Blettler
    • 1
    Email author
  • Guillermina Andrea FAGÚNDEZ
    • 1
  • Octavio Pedro CAVIGLIA
    • 2
    • 3
  1. 1.Laboratorio de Actuopalinología, Centro de Investigaciones Científicas y Transferencia de Tecnología a la Producción/ Facultad de Ciencia y Tecnología (CICyTTP-CONICET/FCyT-UADER)Universidad Autónoma de Entre RíosDiamanteArgentina
  2. 2.INTA–EEA Paraná – CONICETParanaArgentina
  3. 3.Facultad de Ciencias Agropecuarias (FCA-UNER)Universidad Nacional de Entre RíosParanaArgentina

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