Key descriptors for forage legumes

1.0

The Key descriptors for forage legumes consist of an initial minimum set of characterization and evaluation descriptors for herbaceous small tropical species. This general forage legume descriptor will be limited to herbaceous small tropical species with specific examples from species of Clitoria ternatea, Macroptilium atropurpureum, Stylosanthes guianensis, Stylosanthes hamata and Stylosanthes scabra.

This strategic set aims at facilitating access to and utilization of these species and it does not exclude the addition of other descriptors later. This work has been done jointly with the International Livestock Research Institute (ILRI) and the FAO International Treaty on Plant Genetic Resources for Food and Agriculture. The list was based on a preliminary list of descriptors developed by ILRI. In addition, internet searches were carried out looking for the most updated information on relevant characteristics and traits. The original list was subsequently integrated with evaluation traits.

Special attention was given to the inclusion of descriptors relevant to nutritional components and biotic stresses of particular importance in the context of emerging adverse weather events which are expected to intensify under current and future climate challenges. The descriptor list was compared and harmonised, where possible, with minimum descriptors listed for specific forage legumes in Australian Pastures Genebank database and Tropical Forages database.

The key set of access and utilization descriptors was defined through an online survey, in which 22 experts from 13 different organizations and universities from 11 countries participated. Survey results were subsequently validated in consultation with a Core Advisory Group (see “Contributors”) led by Alice Muchugi and Jean Hanson from ILRI.

The strategic set of data standards is designed to facilitate access to and utilization of plant genetic resources for food and agriculture information. Together with passport information (Alercia et al. 2015, 2018), descriptors are critical to the effective sharing of characterization and evaluation data and to the efficient use of plant genetic resources for food and agriculture.

Crop
Forages
Publisher
ILRI and FAO
Bibliographic citation

Muchugi A., Hanson J., Habte E., Sime Y., Alemayehu, A., Alercia A., Cerutti A.L. and Lopez F. 2023. Key descriptors for forage legumes. International Livestock Research Institute, Addis Ababa, Ethiopia and FAO on behalf of the International Treaty on Plant Genetic Resources for Food and Agriculture, Rome, Italy. https://doi.org/10.4060/cc4598en

Version
1.0

The way the main stem continues growth recorded at 50% flowering. Measure/count each descriptor on 10 randomly selected plants or plant parts and report as a mean, with standard deviation, if relevant, for the accession.

Classification
Characterization
Data type
Coded
CodeTermDescription
1Determinate
2Indeterminate

The shape of the plant recorded at 50% flowering. Measure/count each descriptor on 10 randomly selected plants or plant parts and report as a mean, with standard deviation, if relevant, for the accession.

Classification
Characterization
Data type
Coded
CodeTermDescription
1Creeping (procumbent)
2Prostrate
3Semi-erect
4Erect
5Twining

An assessment of the plant leafiness recorded at 50% flowering. Measure/count each descriptor on 10 randomly selected plants or plant parts and report as a mean, with standard deviation, if relevant, for the accession.

Classification
Characterization
Data type
Scale
3
4
5
6
7

Legend:

3

Poor (main stem easily visible)

5

Medium

7

Good (very leafy)

Measured from ground to the tip of the longest branch at maturity. This may be expressed as short to tall compared to a mean measurement for the species planted on the same date in the same site and season. Measure/count each descriptor on 10 randomly selected plants or plant parts and report as a mean, with standard deviation, if relevant, for the accession.

Classification
Characterization
Data type
Numeric
Unit of measure
cm

Record the number of leaflets making up one leaf recorded at 50% flowering. Measure/count each descriptor on 10 randomly selected plants or plant parts and report as a mean, with standard deviation, if relevant, for the accession.

Classification
Characterization
Data type
Numeric

Record the absence/presence of secondary colour on leaflets at pre-flowering stage. Measure/count each descriptor on 10 randomly selected plants or plant parts and report as a mean, with standard deviation, if relevant, for the accession.

Classification
Characterization
Data type
Coded
CodeTermDescription
0Absent
1Present

Record the predominant shape of a mature terminal leaflet, including the shape of the leaflet tip, at 50% flowering. Measure/count each descriptor on 10 randomly selected plants or plant parts and report as a mean, with standard deviation, if relevant, for the accession.

Classification
Characterization
Data type
Coded
CodeTermDescription
1Linear
2Lanceolate
3Ovate
4Oval
5Round
99Other (specify in the NOTES descriptor)

Record the maximum length of the axillary leaflet lamina from a leaflet located in the middle area of the main branch. Measure/count each descriptor on 10 randomly selected plants or plant parts and report as a mean, with standard deviation, if relevant, for the accession.

Classification
Characterization
Data type
Numeric
Unit of measure
mm

Record the maximum width of the axillary leaflet lamina from a leaflet located in the middle area of the main branch. Measure/count each descriptor on 10 randomly selected plants or plant parts and report as a mean, with standard deviation, if relevant, for the accession.

Classification
Characterization
Data type
Numeric
Unit of measure
mm

An assessment of the hairiness of the surface of a mature leaflet recorded at 50% flowering. Measure/count each descriptor on 10 randomly selected plants or plant parts and report as a mean, with standard deviation, if relevant, for the accession.

Classification
Characterization
Data type
Coded
CodeTermDescription
0Glabrous
1Hairy
2Bristled
3Ciliated (hairs around leaf margin)
99Other (specify in the NOTES descriptor)

Record the length of the stipule measured on the leaf subtending the primary inflorescence (if applicable) or the first inflorescence, according to species, recorded at 50% flowering. Measure/count each descriptor on 10 randomly selected plants or plant parts and report as a mean, with standard deviation, if relevant, for the accession.

Classification
Characterization
Data type
Numeric
Unit of measure
mm

Record the predominant flower colour of the upper side of the standard petal on a fully newly opened flower. Flower colour of the wing petals and keel could be scored in a similar way as an additional descriptor if these differ in colour from the standard. Measure/count each descriptor on 10 randomly selected plants or plant parts and report as a mean, with standard deviation, if relevant, for the accession.

Classification
Characterization
Data type
Coded
CodeTermDescription
1White
2Pink
3Yellow
4Orange
5Red
6Purple
7Violet
8Blue
9Grey
99Other (specify in the NOTES descriptor)

Record the predominant flower colour on the lower side of the standard of a fully newly opened flower. Refer to adaxial side for relevant colours.

Classification
Characterization
Data type
Coded
CodeTermDescription
1White
2Pink
3Yellow
4Orange
5Red
6Purple
7Violet
8Blue
9Grey
99Other (specify in the NOTES descriptor)

Record the predominant colour of mature pods at harvest stage. Measure/count each descriptor on 10 randomly selected plants or plant parts and report as a mean, with standard deviation, if relevant, for the accession.

Classification
Characterization
Data type
Coded
CodeTermDescription
1Light brown
2Dark brown
3Dark green
4Dark grey
5Black or dark purple
99Other (specify in the NOTES descriptor)

Record the predominant pod shape. See Figure 3 in the source document. Measure/count each descriptor on 10 randomly selected plants or plant parts and report as a mean, with standard deviation, if relevant, for the accession.

Classification
Characterization
Data type
Coded
CodeTermDescription
1Linear
2Curved (twisted)
3Ovate
4Obovate
5Cup-shaped (half-oval)
99Other (specify in the NOTES descriptor)

Record the predominant texture of the seed pod. Measure/count each descriptor on 10 randomly selected plants or plant parts and report as a mean, with standard deviation, if relevant, for the accession.

Classification
Characterization
Data type
Coded
CodeTermDescription
1Glabrous
2Fine hairs
3Bristles
4Waxy
5Reticulate
99Other (specify in the NOTES descriptor)

Record the length at the longest point of mature pods. Measure/count each descriptor on 10 randomly selected plants or plant parts and report as a mean, with standard deviation, if relevant, for the accession.

Classification
Characterization
Data type
Numeric
Unit of measure
mm

Record the number of seeds in a mature pod. Measure/count each descriptor on 10 randomly selected plants or plant parts and report as a mean, with standard deviation, if relevant, for the accession.

Classification
Characterization
Data type
Numeric

Record the predominant primary colour of mature seeds. Measure/count each descriptor on 10 randomly selected plants or plant parts and report as a mean, with standard deviation, if relevant, for the accession.

Classification
Characterization
Data type
Coded
CodeTermDescription
1White
2Green
3Cream
4Yellow
5Purple
6Light brown
7Dark brown
8Black
99Other (specify in the NOTES descriptor)

Record the percentage of secondary seed colour as bicolour, spots and mottling on mature seeds. Measure/count each descriptor on 10 randomly selected plants or plant parts and report as a mean, with standard deviation, if relevant, for the accession.

Classification
Characterization
Data type
Numeric
Unit of measure
%

Record the predominant shape of mature seeds. See Figure 4 in the source document. Measure/count each descriptor on 10 randomly selected plants or plant parts and report as a mean, with standard deviation, if relevant, for the accession.

Classification
Characterization
Data type
Coded
CodeTermDescription
1Round
2Oval
3Ovate
4Oblong
5Obovate
6Obcordate
7Reniform
8Deltoid
9Rhomboid
99Other (specify in the NOTES descriptor)

Record the length of the longest axis of mature seeds. Measure/count each descriptor on 10 randomly selected plants or plant parts and report as a mean, with standard deviation, if relevant, for the accession.

Classification
Characterization
Data type
Numeric

Record the width of mature seeds at the widest point. Measure/count each descriptor on 10 randomly selected plants or plant parts and report as a mean, with standard deviation, if relevant, for the accession.

Classification
Characterization
Data type
Numeric

Record the thickness of mature seeds. Measure/count each descriptor on 10 randomly selected plants or plant parts and report as a mean, with standard deviation, if relevant, for the accession.

Classification
Characterization
Data type
Numeric

Record the weight of 100 randomly selected mature seeds taking replicates to obtain a mean. This can be expressed as 100 or 1000 seed weight for smaller seeds. Measure/count each descriptor on 10 randomly selected plants or plant parts and report as a mean, with standard deviation, if relevant, for the accession.

Classification
Characterization
Data type
Numeric

Number of days from sowing until 50% of the plants have begun to flower. Recorded for plants with the same sowing date at the same location in the same year. Measure/count each descriptor on 10 randomly selected plants or plant parts and report as a mean, with standard deviation, if relevant, for the accession.

Classification
Characterization
Data type
Numeric

Record the dry matter weight of quadrats cut at 10% flowering at 5-10 cm above ground (as relevant for the species) using representative samples that are dried and converted to kg dry matter/ha. Indicate season, plant age and physiological stage (e.g. vegetative/ flowering) at harvesting as results will change as the plant ages. Data are reported as means with standard deviation, for the accession.

Classification
Evaluation
Data type
Numeric

Weight of pure seeds after threshing and cleaning recorded from representative samples taken from quadrats and converted to kg/ha. Data are reported as means with standard deviation, for the accession.

Classification
Evaluation
Data type
Numeric

Recorded from representative samples taken from quadrats. Analytical assessment determined on a dried ground sub-sample of the whole plant. All nutritional traits reported should be from comparable samples using analyses done according to standard accredited methods from the same laboratory. Data are reported as means with standard deviation, for the accession.

Classification
Evaluation
Data type
Numeric

Recorded from representative samples taken from quadrats. Analytical assessment determined on a dried ground sub-sample of the whole plant. Indicate plant age and physiological stage (e.g. vegetative/ flowering) at harvesting as results will change as the plant ages. All nutritional traits reported should be from comparable samples using analyses done according to standard accredited methods from the same laboratory. Data are reported as means with standard deviation, for the accession.

Classification
Evaluation
Data type
Numeric

Recorded from representative samples taken from quadrats. Analytical assessment determined on a dried ground sub-sample of the whole plant. Indicate plant age and physiological stage (e.g. vegetative/ flowering) at harvesting as results will change as the plant ages. All nutritional traits reported should be from comparable samples using analyses done according to standard accredited methods from the same laboratory. Data are reported as means with standard deviation, for the accession.

Classification
Evaluation
Data type
Numeric

Record the percentage of plants showing the trait under stress conditions. Abiotic Stress Susceptibility scored as percentage survival from a specific trial to induce drought stress, under conditions which are clearly specified. Drought trials are often performed under greenhouse conditions or rain-out shelters.

Classification
Evaluation
Data type
Numeric