Protocols to Determine Pollination Requirements and Optimal Pollinators for Plant Genetic Resource Regeneration

Transcription

1 Protocols to Determine Pollination Requirements and Optimal Pollinators for Plant Genetic Resource Regeneration Ken Richards & Mark Widrlechner Canadian Genetic Resources Program, Saskatoon, SK North Central Regional Plant Introduction Station, Ames, Iowa Agriculture and Agri-Food Canada Agriculture et Agroalimentaire Canada

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3 The Challenge / Needs Diversity of plant species 300,000 to 500,000 species of higher plants (250,000 described taxonomically) 30,000 edible; 7,000 cultivated or collected by humans at one time or another 30 crops feed the world providing 95% of dietary energy (calories) or protein When considering all animal/plant products, 1/3 of total human diet depends directly or indirectly on insect-pollinated crops

4 The Challenge / Needs Lack of information General patterns of pollen transfer understood But little known about pollination requirements for most cultivated plants Breeding systems are under genetic control; rarely fixed or static, often fluid and responsive to selection pressure Challenge: most seed plants have a range of reproductive options They arise intermittently through mutation and evolve in response to selective conditions

5 The Challenge / Needs Lack of information Although detailed pollination are requirements known for major cultivated crops, they are often based on modern, improved cultivars and may not reflect the full range of variation Other crop species (incl. wild relatives, underutilized or minor crops) are insufficiently understood

6 100 % Hand Selfing 50 alba % Natural Selfing in Melilotus Species Sano (1977) Ecol. Plant. 12: indica sulcata elegans messanensis italica macrocarpa suaveolens neapolitana suaveolens wolgica dentata dentata speciosa polonica infesta taurica hirsuta altissima officinalis segetalis alba officinalis Biennial - Eumelilotus Annual - Eumelilotus Annual - Micromelilotus

7 The Challenge / Needs Regeneration protocols Seed regeneration is a key part of ex situ germplasm conservation Even under optimal storage conditions, seed viability declines and leads to a loss of genetic diversity For unique material, such losses may be irreplaceable Therefore, monitoring of viability and timely seed regeneration must be a priority

8 The Challenge / Needs Factors influencing regeneration Loss of viability (seed longevity) Small original samples Number of requests for a given accession Scheduled morphological characterization Need to separate mixtures (for inbred crops or multiple-species collections)

9 The Challenge / Needs Regeneration Ideally conducted under neutral selection conditions (minimal competition, optimal growing environment, sufficient population size) To minimize genetic change during through selection But not always possible Certain degree of genetic change is inevitable Especially under conditions markedly different from those where the accession was best adapted

10 How to Proceed? A Basic Field Determination of Pollination Requirements Open pollinated Caged with insects - Optimal pollination achieved only when appropriate pollinator is used Pollinator excluded (control)

11 A More Thorough Determination of Pollination Requirements -- Detailed Greenhouse Protocol Flowers bagged to self-pollinate (SP) Shaken to stimulate movement by wind SP flowers with brush from same flower SP flowers with brush from same raceme SP flowers with brush from same plant Cross-pollinate with brush from different plant Flowers open pollinated (control)

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15 Important Metrics Measures of self incompatibility (Zapata & Arroya 1978) Self incompatibility = seed set from self-pollination seed set from cross-pollination - Caution: level may vary both among populations and among individuals within populations Estimate of cross pollination (Cruden 1977) Ratio between the number of pollen grains and ovules (the P:O ratio)

16 Important Metrics Rate of self-pollination (Charlesworth & Charlesworth 1987) Selfing rate = value from outcrossing value from open pollination value from outcrossing value from selfing - Caution: formula only valid when value from outcrossing > value from OP or selfing levels

17 Sainfoin (Onobrychis viciifolia) Case Study I Non-bloat forage legume for livestock production Highly out-crossing Alfalfa leaf cutter & honey bees

18 Sainfoin (Alberta Data) Flowers/ raceme Pods/ raceme % seed set Seed yield (kg/ha) Open 58.0a 29.7a 51.1a a Caged & 57.6a 26.7a 46.3b a Bees Exclusion 46.7b 0.9b 1.9c 9.6b

19 Diversity of pollinators (n=4974; Alberta) % Megachile rotundata 55.9 Apis mellifera 40.5 Bombus huntii 2.7 Bombus occidentalis 0.4 Bombus rufocinctus 0.4 Bombus fervidus 0.1 Much different array than reported in European literature

20 Probability of Floral Visitation Pv = 1 e m, where m = bees / area x visitation rate x pollination time flower density

21 Sainfoin Pollinator Efficiency (Visitation Rate) Bee N Seconds / flower Flowers / minute honey bee alfalfa LC bumble bees

22 Pollination Time Maximum 15 hr / d (determined by photoperiod) Optimum hr (varies by species also midday heat in field cages) Practical 12 hr / d? Actual?

23 Activity Curves by Species Vary by time of day & season

24 Stigma Receptivity (t = time stigma is receptive) Literature Values for t Tereschenko (1949): 1 day Dubbs (1967): 7-12 days Richards (unpublished): 1 day - Generally not known or recorded

25 Alfalfa (Medicago sativa) flowers are receptive longer than a day

26 Flower density Curvilinear over season

27 Constancy to Raceme (needs to be compared among pollinators -- indicator of outcrossing) flowers visited / raceme Apis mellifera Megachile rotundata Bombus spp >

28 Probability of Sainfoin Flower Visitation Predicts flower visits for studied pollinators 1 Bombus is as effective as 1.5 Apis or Megachile This approach is most valuable for planning field isolations

29 Probability of Visitation in Relation to Flower Density and Bee Density Bombus requires lower bee density for the same probability of visitation

30 Cicer Milkvetch (Astragalus cicer) Case Study II Non-bloating forage legume for livestock production Cross pollinated Bumblebee, alfalfa leafcutter, honey bees

31 Pollination Requirements for Cicer Milkvetch open pollinated pollinator excluded flowers / raceme seed set % seeds / raceme seeds / pod

32 Rate of Flower Visitation Sec. / fl. fl. / min. Bombus nevadensis B. huntii B. rufocinctus Apis mellifera Megachile rotundata

33 Pollinator Effectiveness Caged Seed Yield (seeds / pod) Bombus nevadensis 7.92a 6.83a 7.18a B. fervidus 7.22a B. appositus 5.97b 6.10b 6.40b B. huntii 5.87b 6.05b B. rufocinctus 5.80b B. californicus 5.80b Apis mellifera 3.27c 3.94c 4.19c Megachile rotundata 3.45c 3.48c 3.31c

34 Carrot Case Study III (Daucus carota) (Wilson et al. 1991) Widely cultivated root vegetable Mixed mating system Many insect visitors, but which species are effective pollinators?

35 Carrot Case Study Tested pollination by hand, honey bees, flies, and a combination of bees and flies, all in field cages Three years of data on seed weight per cage, also collected relative time measures for insect management

36 Carrot Case Study Total Seed Weight per Cage (g) Method Honeybees a 46.9 a 80.2 ab Flies b 30.9 a 44.8 b Both 67.3 a a Hand 26.2 b

37 Carrot Case Study Combination of bees and flies worked best, without a major increase in labor investment Daucus and other umbels vary not only in seed production by pollinator, but also can vary widely in quality (% germination) - See Pimpinella poster

38 Potential Managed Pollinators for Genebank Use What pollinators are potentially available for genebank managers today?

39 Potential Managed Pollinators for Genebank Use Honey bee (Apis mellifera) Bumble bees (Bombus spp.)

40 Potential Managed Pollinators for Genebank Use Mason bees (Osmia spp.) Alfalfa leafcutter bee (Megachile rotundata) Other solitary bees

41 Potential Managed Pollinators for Genebank Use Blow flies (Calliphora spp.) House fly (Musca domestica) Syrphid flies

42 Avoiding Pollen Contamination through Isolation Achieving adequate isolation depends on: - Possible pollen vectors (wind, insect, birds, bats, etc.) - Floral morphology and breeding system Isolation mechanisms: - Spatial or temporal - Natural or artificial barriers, trap crops - Bagging with hand crossing (if needed) Assumes knowing adequate isolation distance, how far? - Pollen and / or pollinator movement - Determine via morphological and / or molecular markers

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44 Positives Pollination Cages Pros and Cons - Effective isolation barriers - Excludes certain pests, which can vector diseases or otherwise reduce seed yield / vigor - Can manipulate pollinators and control pollinator density

45 Negatives Pollination Cages Pros and Cons - Expensive, laborious to construct - May shade plants / modify ambient temperature / humidity affecting plant growth, seed production, & pollinator foraging behavior - Favorable environment for certain insect pests / pathogens - May result in negative pesticide-pollinator interactions

46 Pollination Cages Pros and Cons Unknowns - Pollen longevity (heat and humidity) - Pollen movement (especially with multiple crops in a cage)

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49 Pollinator Choice and Management Optimal crop pollination can only be achieved if an appropriate pollen vector is available to visit flowers Challenges: Identify primary, secondary & tertiary pollinators Combinations of pollinators Efficiency, effectiveness, abundance Differentiate between visitors and pollinators Develop standard methods to ID pollinators Limited palette of managed pollinators at present

50 Pollinator Choice Determine general surface/volume relationships Tongue length of pollinators vs. Floral morphology (corolla tube length)

51 Pollinator Choice and Management More Challenges: Number of pollinators needed on small isolation plots - Integrate bee behavior, plant biology, agronomy - Bee drift from small plots and other plant competition Management techniques - Need handbook for pollinator management for genebanks Staff training and specialized facilities Working in cages with bees (sting / allergy hazard) Introducing new pollinators to regions and risks

52 Conclusions Pollination requirements for major crops are known in part; minor crops inadequate Optimal pollinator needs to be determined Compare to available managed pollinators Need to integrate agronomy, plant pollination requirements and biology, and pollinator behavior

53 Many Thanks to Sharon McClurg and Jeff Carstens for assistance with images and carrot data Larry Deack and Beatriz Moisset for fly images from the Internet John Virosteck, Tim Myers and Peggy Edwards for assistance with obtaining plant seed set and pollinator foraging data