Oxygen Measurements in Seed Testing Kent J. Bradford, Pedro Bello, Jing-Chen Fu and Margarita Barros Department of Plant Sciences, Seed Biotechnology Center University of California, Davis, USA [email protected]

Respiration Rates and Seed Quality Respiration is known to be associated with seed vigor and viability, as is shown through tetrazolium tests.

VIABLE

NONVIABLE UCDAVIS

Respiration As A Seed Quality Parameter • Respiration is essential for germination. • Respiration is related to seed quality. • Individual seeds vary in their respiration rates and capacity. • Single-seed assays are labor-intensive, but bulk samples give only an average value for the seed population. • It is difficult to relate respiration directly to components of seed quality in bulk samples. • A convenient method to assay respiration of many individual seeds would be useful. UCDAVIS

Astec Q2 for Measuring Seed Respiration

www.astecglobal.net UCDAVIS

Single-seed Respiration Measurements

Individual seeds are sealed into the wells of a microtiter plate or in screwcap vials. The sealing membrane or screwcap has dye dots on the inner side whose fluorescence is proportional to the oxygen concentration in the well. As the seeds imbibe and respire, the oxygen content of the air space of the well decreases. This increases the fluorescence of the dye in the dot inside the well when illuminated with light. UCDAVIS

Single-Seed Respiration Measurements A light source/fluorescence sensor unit moves over the plates at user-specified intervals and records the oxygen content of each well.

The instrument records the oxygen level in each well over time as it is depleted due to seed respiration.

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Air Volume Can Be Varied and Germination Observed

Using agar, the air volume in the wells can be varied to match the size and respiration rates of the seeds.

Agar also allows radicle emergence to be observed through the bottom of the plate at desired intervals.

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Q2 Temperature Controller

We developed a custom temperature controller that can maintain constant and different temperatures in groups of four plates. UCDAVIS

ASTEC Analysis Software for Q2 Data Raw data

Categorized and modeled data UCDAVIS

Respiration Patterns and ASTEC Values SMR = Starting Metabolism Rate

100 SMR

SMR

Oxygen (% of initial)

80

60

40

20

0 0

10

20

30

40

50

60

70

Time (h)

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Respiration Patterns and ASTEC Values SMR = Starting Metabolism Rate IMT = Increased Metabolism Time

100 SMR

SMR

Oxygen (% of initial)

80 IMT

60

40

20

0 0

10

20

30

40

50

60

70

Time (h)

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Respiration Patterns and ASTEC Values SMR = Starting Metabolism Rate IMT = Increased Metabolism Time OMR = Oxygen Metabolism Rate

100 SMR

SMR

Oxygen (% of initial)

80 IMT

60

OMR OMR

40

20

0 0

10

20

30

40

50

60

70

Time (h)

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Respiration Patterns and ASTEC Values SMR = Starting Metabolism Rate IMT = Increased Metabolism Time OMR = Oxygen Metabolism Rate RGT = Relative Germination Time

100 SMR

SMR

Oxygen (% of initial)

80 IMT

60

OMR OMR

40

20 RGT

RGT

0 0

10

20

30

40

50

60

70

Time (h)

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Respiration Patterns and ASTEC Values SMR = Starting Metabolism Rate IMT = Increased Metabolism Time OMR = Oxygen Metabolism Rate RGT = Relative Germination Time COP = Critical Oxygen Pressure

100 SMR

SMR

Oxygen (% of initial)

80 IMT

60

OMR OMR

40 COP

COP

20 RGT

RGT

0 0

10

20

30

40

50

60

70

Time (h)

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Respiration Patterns and ASTEC Values SMR = Starting Metabolism Rate IMT = Increased Metabolism Time OMR = Oxygen Metabolism Rate RGT = Relative Germination Time COP = Critical Oxygen Pressure QT50 = Time to 50% Oxygen

100 SMR

SMR

Oxygen (% of initial)

80 IMT

60

OMR OMR

40 COP

COP

20 RGT

QT50

RGT

QT50

0 0

10

20

30

40

50

60

70

Time (h)

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Respiration Patterns and ASTEC Values SMR = Starting Metabolism Rate IMT = Increased Metabolism Time OMR = Oxygen Metabolism Rate RGT = Relative Germination Time COP = Critical Oxygen Pressure QT50 = Time to 50% Oxygen AUC50 = Area Under Curve to QT50

100 SMR

SMR

Oxygen (% of initial)

80 IMT

60

OMR OMR

40 AUC50 COP

COP

20 RGT

QT50

RGT

QT50

0 0

10

20

30

40

50

60

70

Time (h)

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Q2 Experience with Diverse Species

17 Species Tested Alfalfa Cabbage Chinese cabbage Cauliflower Cantaloupe Coreopsis Cornflower Lettuce

Marigold Onion Pansy Radish Sugar beet Tomato Turnip Vinca Viola UCDAVIS

Vigor Correlation with ASTEC Values -- Brassica 35

A IMT

30

y = -0.3194x + 43.629 R² = 0.2133**

IMT (h)

25 20 15 10 5

IMT and OMR correlated significantly with a common vigour index (early count in a standard germination test) across 17 cabbage, 6 Chinese cabbage, 5 turnip and 5 cauliflower seed lots.

0 70

8

80

85 90 First count (%)

95

100

y = 0.0708x - 3.374 R² = 0.1858*

C OMR

7

OMR (% Oxygen/h)

75

6 5 4

Turnip Chinese cabbage Cauliflower Cabbage

3 2 1 0 70

75

80

85

90

First count (%)

95

100

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Vigor Correlation with ASTEC Values -- Brassica 160

y = -1.1324x + 151.66 R² = 0.2315**

E RGT

140 120

RGT (h)

100 80 60 40 20 0 70

75

80

85 90 First count (%)

100

y = -0.6892x + 76.92 R² = 0.2967**

F HOM

50

95

40

HOM (h2)

RGT and HOM also correlated significantly with a common vigour index (early count in a standard germination test) across 17 cabbage, 6 Chinese cabbage, 5 turnip and 5 cauliflower seed lots. SMR and COP did not have significant correlations with vigor index.

30 20 10 0 70

75

80

85

90

95

100

Turnip Chinese cabbage Cauliflower Cabbage

First count (%)

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Priming Treatments -- Tomato Screening priming treatments by comparing times to 50% germination (T50) with QT50 respiration values.

The times to germination of individual seeds and the T50 of the population were highly correlated with QT50 respiration rates. The IMT was also highly correlated with QT50 and with T50. UCDAVIS

Temperature and Respiration -- Tomato Temperature has predictable effects on germination rates. Similar effects are observed on respiration rates measured by the Q2.

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Water Potential and Respiration -- Tomato Reduced water potential also has consistent effects on germination rates. 0 MPa -0.2 MPa -0.4 MPa

Similar effects are observed on respiration rates measured by the Q2.

0 MPa -0.2 MPa -0.4 MPa

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Priming and Aging Treatments -- Lettuce Priming advanced and aging (75% RH and 40ºC) delayed both germination and respiration relative to the control (untreated) seeds.

Note the wide variation in the shapes of the oxygen consumption curves, and the trend for more seeds to have linear patterns as they aged.

Color scale at bottom of each panel indicates the time of radicle emergence for the seeds whose respiration curves are the same color. UCDAVIS

Priming and Aging Treatments -- Lettuce Some ASTEC values were highly correlated with T50 for germination in response to priming or aging, particularly SMR and RGT.

The QT50 and AUC50 values were highly correlated with T50 for germination, and are not dependent upon the shapes of the respiration curves. UCDAVIS

Alternative Data Analysis Method for Q2 Data

75%

25%

We developed an alternative analysis method based upon the time required for each seed to reduce the oxygen level to a specified percentage, e.g., 50% of the initial value. When plotted versus time, this results in a curve resembling a germination time course. UCDAVIS

Germination versus QT Time Courses Priming and aging effects on germination time courses were similar to their effects on respiration time courses. This representation takes advantage of the singleseed measurements and can reveal differences in behavior among subpopulations of the seed lot. This analysis method also allows the application of threshold-based population models to the respiration data, such as for temperature, water potential or aging.*

*Alvarado and Bradford (2002) Plant Cell Environ. 25: 1061-1069. Bradford et al. (1993) J. Exp. Bot. 44: 1225-1234. UCDAVIS

Application of Q2 to CD Tests -- Radish

CD at 33% RH and 50 C

Controlled deterioration viability tests at lower storage MC take a long time to conduct if final viability is scored. Germination rates are more sensitive to aging.

Respiration rates are sensitive to aging, and show large differences before significant viability has been lost. Respiration rates can be assessed after shorter aging periods to estimate potential longevity.

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Conclusions • The Q2 instrument can measure respiration time courses of individual seeds. • There is wide variation among respiration rates of individual seeds, but overall patterns are correlated with seed vigour and germination rates. • Various components of oxygen depletion time courses can be quantified to assess respiratory patterns. • Respiratory time courses of seed populations, analogous to germination time courses, can be generated. • Q2 assays can semi-automate collection of time course data and enable greater use of germination rates in seed quality evaluation.

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Financial Support

Astec Global: technical and in-kind support

American Seed Trade Association Vegetable & Flower Seed Permanent Research Fund

Western Regional Seed Physiology Research Group WRSPRG Pedro Bello

Q2 Users’ Group

Q2 Users’ Group and multiple companies who provided seeds. UCDAVIS