If a species is not footnoted with a number (1-18), then the specific gravity for that species has not been verified by Wagner. In most cases, with unverified species, these species have the same botanical name as the verified version but just a different common name. Many species (botanical name) in the world have many different common names. The footnote descriptions are shown at the bottom of the page.*

Wood Species Types in Alphabetical Order

To obtain the most accurate moisture content measurements with your Wagner moisture meter, you must set the meter for the correct species settings value for the species you are going to measure. For our customers' convenience, we have calibrated our meter's species settings in terms of specific gravity.*

For those instances where you need to measure moisture in a wood species that is not shown in your User’s Manual, Wagner has compiled this extensive database of wood species with their associated specific gravity values.

The sources for our database include the United States Department of Agriculture, Forest Products Laboratory.

The published specific gravity values are the average for each species. There can and will be some variability of the specific gravity (density) within any species of wood, but the average specific gravity value (again, from the most valid published sources) will provide the best settings for your Wagner moisture meter.

Common NameBotanical NameSpecific GravityVerified
Hura crepitans0.40
Radiata PinePinus radiata0.452
RaguaAleurites moluccana0.14
Rain TreeTetramerista glabra0.73
RaisalCupressus torulosa0.47
RaisallaCupressus torulosa0.47
Raisinier MontagnePodocarpus guatemalensis0.54
Raja KayuKoompassia excelsa0.75
RajadoPeltogyne porphyrocardia0.69
RakMelanorrhoea spp.0.75
RakichCalophyllum inophyllum0.55
RakichCalophyllum tomentosum0.59
Hura crepitans0.40
Hura crepitans0.40
RamalaCampnosperma brevipetiolata0.33
RaminGonystylus bancanus
0.562
RaminGonystylus forbesii0.61
RaminGonystylus macrophyllum0.54
Ramin TelurGonystylus macrophyllum0.54
RamlluwCampnosperma brevipetiolata0.33
RamluwCampnosperma brevipetiolata0.33
RamuloCampnosperma brevipetiolata0.33
RangguKoordersiodendron pinnatum0.71
Tabebuia serratifolia0.99
RapaneaRapanea melanophleos0.74
RarningobcheySpathodea campanulata0.25
RasulaCupressus torulosa0.47
Rata-KekunaAleurites moluccana0.14
Re VangMachilus odoratissima0.59
Red AlderAlnus rubra0.411
Red Ash0.557
Fraxinus americana0.60
Fraxinus pennsylvanica0.56
Red AshFraxinus profunda0.512
Red BalataManilkara bidentata0.95
Red BalauShorea guiso0.75
Red BalauShorea plagata0.75
Fagus grandifolia0.64
Betula papyrifera0.55
Prioria copaifera0.42
Red CedarCedrela huberi0.404
Cedrela odorata0.39
Red CedarCedrela toona0.47
Libocedrus decurrens0.37
Swietenia macrophylla0.47
Thuja plicata0.32
Taxodium distichum0.46
Red DealPinus sylvestris0.4514
Red ElmUlmus campestris0.5213
Red ElmUlmus crassifolia0.62
Red ElmUlmus procera0.5313
Ulmus rubra0.53
Abies amabilis0.43
Abies magnifica0.38
Abies procera0.39
Pseudotsuga menziesii0.48
Red Forest GumEucalyptus tereticornis0.82
Red GumEucalyptus rostrata0.74
Red GumEucalyptus tereticornis0.82
Liquidambar styraciflua0.52
Red HaiawaballiTetragastris altissima0.74
Red IronwoodLophira alata0.94
Red IvoryPygeum africanum0.61
Red IvorywoodRhamnus zeyheri0.86
Juniperus virginiana0.47
Red KwarieVochysia ferruginea0.52
Red KwarieVochysia guianensis0.52
Red LancewoodManilkara bidentata0.95
Red LarchLarix leptolepis0.49
Red LauanShorea negrosensis0.594
Robinia pseudoacacia0.69
Khaya nyassica0.44
Red MapleAcer rubrum0.541
Red MoraMora excelsa0.89
Pterocarpus indicus0.57
Red OakLophira alata0.94
Quercus coccinea0.67
Quercus palustris0.63
Quercus rubra0.63
Quercus velutina0.61
Pinus radiata0.45
Red PinePinus resinosa0.461
Red PinePinus sylvestris0.4514
Red PlanchonellaPlanchonella euphlebia0.89
Red River GumEucalyptus rostrata0.74
Pterocarpus soyauxii0.64
Red SelanganShorea guiso0.75
Red Selangan BatuShorea guiso0.75
Red Selangan BatuShorea plagata0.75
Red SilionManilkara zapota0.71
Red SprucePicea rubens0.401
Red stinkwoodPygeum africanum0.61
Red tolaOxystigma oxyphyllum0.53
Red wattleAcacia crassicarpa0.50
Swietenia macrophylla0.47
RedaniCedrela toona0.47
Red-Arilled AfzeliaAfzelia quanzensis0.62
Juniperus virginiana0.47
Pinus sylvestris0.45
RedwoodPiptadeniastrum africanum0.63
Pterocarpus soyauxii0.64
Redwood Old-GrowthSequoia sempervirens0.401
Redwood Young-GrowthSequoia sempervirens0.351
Pinus radiata0.45
RengasMelanorrhoea spp.0.75
RengkongAnisoptera curtisii0.52
Swietenia macrophylla0.47
Nyssa sylvatica0.50
ResakTarrietia sylvatica0.82
Rhode KwariVochysia guianensis0.52
Rhodesian CopalwoodGuibourtia coleosperma0.66
Rhodesian MahoganyAfzelia quanzensis0.62
Rhodesian MahoganyGuibourtia coleosperma0.66
Rhodesian TeakGuibourtia coleosperma0.66
Pterocarpus angolensis0.59
RhuCasuarina equisetifolia0.87
RiemhoutMicropholis guianensis0.67
RikhanPopulus ciliata0.37
RimdaHopea odorata0.63
RimpumaraMesua ferrea0.92
RindaHopea odorata0.63
Pterocarpus indicus0.57
River GumEucalyptus rostrata0.74
River Red GumEucalyptus rostrata0.74
RoMusanga cecropioides0.23
Robinia pseudoacacia0.69
RobleAmburana cearensis0.584
Platymiscium pinnatum0.87
Quercus alba0.68
Quercus bicolor0.72
Quercus coccinea0.67
Quercus macrocarpa0.64
Quercus michauxii0.67
Quercus palustris0.63
Quercus stellata0.67
Quercus velutina0.61
RobleQuercus virginiana0.84
Tabebuia serratifolia0.99
RobleTabebuia spp.0.552
RobleTerminalia amazonia0.76
Quercus alba0.68
Quercus bicolor0.72
Quercus coccinea0.67
Quercus macrocarpa0.64
Quercus michauxii0.67
Quercus palustris0.63
Quercus stellata0.67
Quercus velutina0.61
Roble AmarilloQuercus virginiana0.84
Roble AmarilloTerminalia amazonia0.76
Platymiscium pinnatum0.87
Tabebuia serratifolia0.99
Roble ColoradoPlatymiscium pinnatum0.874
Quercus alba0.68
Quercus bicolor0.72
Quercus coccinea0.67
Quercus macrocarpa0.64
Quercus michauxii0.67
Quercus palustris0.63
Quercus stellata0.67
Quercus velutina0.61
Roble ColoradoQuercus virginiana0.84
Amburana cearensis0.58
Roble de EsmeraldasTerminalia amazonia0.76
Roble de PelotaGrevillea robusta0.54
Roble de SedaGrevillea robusta0.54
Amburana cearensis0.58
Roble del PaisAmburana cearensis0.584
Quercus alba0.68
Quercus bicolor0.72
Quercus coccinea0.67
Quercus macrocarpa0.64
Quercus michauxii0.67
Quercus palustris0.63
Quercus stellata0.67
Quercus velutina0.61
Roble EncinoQuercus virginiana0.84
Roble MacuelizoTerminalia amazonia0.76
Platymiscium pinnatum0.87
Platymiscium pinnatum0.87
Roble RedosoGrevillea robusta0.54
Quercus alba0.68
Quercus bicolor0.72
Quercus coccinea0.67
Quercus macrocarpa0.64
Quercus michauxii0.67
Quercus palustris0.63
RoblecitoQuercus petraea0.65
Quercus stellata0.67
Quercus velutina0.61
RoblecitoQuercus virginiana0.84
Rock ElmChlorophora excelsa0.70
Rock ElmUlmus alata0.65
Rock ElmUlmus crassifolia0.62
Rock ElmUlmus thomasii0.631
Acer nigrum0.57
Acer saccharum0.63
Pseudotsuga menziesii0.48
Abies lasiocarpa0.32
Picea engelmannii0.35
Abies concolor0.39
RocoChlorophora excelsa0.70
Fagus sylvatica0.67
Hymenaea courbaril0.83
Hymenaea courbaril0.83
Rode SalieTetragastris altissima0.74
Rode StinkhoutPygeum africanum0.61
Cedrela odorata0.39
RokkoChlorophora excelsa0.70
RokkoChlorophora regia0.59
Romanian BeechFagus sylvatica0.6713
Astronium graveolens0.89
Astronium graveolens0.80
RoneTestulea gabonensis0.76
RonkoTerminalia ivorensis0.54
Astronium graveolens0.89
Astronium graveolens0.80
RoodeMora excelsa0.89
Roode MoreMora excelsa0.89
Astronium graveolens0.89
Astronium graveolens0.80
RorumHeritiera javanica0.65
RosarosaHeritiera ornithocephala0.70
Cedrela odorata0.39
Rose KadambuMitragyna parvifolia0.59
RosenhoutAniba duckei0.56
RosewoodByrsonima coriacea0.68
RosewoodDalbergia stevensonii0.88
Pterocarpus indicus0.57
RositaHieronyma alchorneoides0.58
RostamarindeMarmaroxylon racemosum1.07
Rostrata GomEucalyptus rostrata0.74
Rostrata GumEucalyptus rostrata0.74
Rostrata-GomEucalyptus rostrata0.74
Rotes TolaOxystigma oxyphyllum0.53
Quercus robur0.57
RuCasuarina equisetifolia0.87
Ru LaitCasuarina equisetifolia0.87
Rubber TreeTieghemella heckelii0.60
RubberwoodHevea brasiliensis0.5116
RufaSyzygium buettnerianum0.73
Prunus serotina0.50
Fagus sylvatica0.67
RumuHeritiera javanica0.65
RungunHeritiera javanica0.65
Russian WhitewoodPicea abies0.43

Footnotes:

1Forest Products Laboratory Wood Handbook @ 12% MC values
2Forest Products Laboratory Wood Handbook Calculated from Green MC values by Wagner
3Forest Products Laboratory Techsheets Calculated from Green MC values by Wagner
4WoodWorkersSource Wood Library Calculated from Green MC values by Wagner
5We included Douglas-fir(Pseudotsuga menziesii) Coast (.48)*, Interior West (.50)*, Interior North (.48)*, Interior South (.46)* to come up with an average SG of (.48)* *“Coast type Douglas-fir is defined as Douglas-fir growing in the States of Oregon and Washington west of the summit of the Cascade Mountains. Interior West includes the State of California and all counties in Oregon and Washington east of but adjacent to the Cascade summit. Interior North includes the remainder of Oregon and Washington and the States of Idaho, Montana, and Wyoming.” Specific Gravity resources: * Wood Handbook page 5-7
6According to USDA Forest Service, Forest Product Laboratory, Wood Handbook 2-8, Hard maple includes sugar maple (Acer saccharum) (.63)* and black maple (A. nigrum) (.57)*.
7According to USDA Forest Service, Forest Product Laboratory, Techsheets, Red Ash includes these three subspecies Fraxinus americana (.60)*, Fraxinus pennsylvanica (.56)*, Fraxinus profunda (.51)*
8According to USDA Forest Service, Forest Product Laboratory, Wood Handbook page 2-8, Soft maple includes silver maple (Acer saccharinum) (.47)*, red maple (A. rubrum) (.54)*, bigleaf maple (A.macrophyllum) (.48)*, and boxelder (A. negundo) (.45)** Specific Gravity resources:
* Wood Handbook page 5-5
** Forest Product Laboratory Techsheet
9According to the Southern Pine Inspection Bureau (SPIB) the four main subspecies that make up the SYP category are: Longleaf, Shortleaf, Loblolly and Slash pines. The SYP mix setting (.56) was determined by taking the average of Longleaf (.59)*, Shortleaf (.51)*, Loblolly (.51)* and Slash pines (.59)* Specific Gravity resources: * Wood Handbook page 5-7 & page 5-8
10 Forest Products Laboratory Techsheets Calculated from Green MC values by Wagner applying an acceptable volumetric shrinkage approximation per USDA GTR FPL-GTL-76
11 According to Forest Products Laboratory Techsheets Guatambu grown in *Brazil has a higher specific gravity then for **Argentinean material. *Guatambu (Brazil) (Balfourodendron riedelianum)(.79) Calculated from Green MC values by Wagner. **Guatambu (Argentinean) (Balfourodendron riedelianum)(.70) Calculated from Green MC values by Wagner.
12Forest Products Laboratory Techsheets Calculated from Dry (0%) MC values by Wagner applying an acceptable volumetric shrinkage approximation per USDA GTR FPL-GTL-76
13WoodWorkersSource Wood Library Calculated from Dry (0%) MC values by Wagner applying an acceptable volumetric shrinkage approximation per USDA GTR FPL-GTL-76
14WoodWorkersSource Wood Library Calculated from Green MC values by Wagner applying an acceptable volumetric shrinkage approximation per USDA GTR FPL-GTL-76
15WoodWorkersSource Wood Library Calculated from Dry (0%) MC values by Wagner
16The Wood Database Calculated from Green MC values by Wagner
17The Wood Database Calculated from Green MC values by Wagner applying an acceptable volumetric shrinkage approximation per USDA GTR FPL-GTL-76
18Tropicaltimber Calculated from Green MC values by Wagner applying an acceptable volumetric shrinkage approximation per USDA GTR FPL-GTL-76
19According to Forest Products Laboratory Techsheets Goncalo Alves grown in *Honduras and Venezuela has a higher specific gravity then for **Brazil and Colombia material. *Goncalo Alves (Honduras and Venezuela) (Astronium graveolens)(.89) Calculated from Green MC values by Wagner. **Goncalo Alves (Brazil and Colombian) (Astronium graveolens)(.80) Calculated from Green MC values by Wagner.
 
 
* Legal disclaimer:

Wagner has compiled species’ average specific gravity (SG) values (wood volume at 12% moisture content (MC) and oven-dry weight) from industry-accepted 3rd-party sources (USDA Forest Products Laboratory as an example) and provides this list for free with no implied warranty. Where an SG value listed in Wagner Meters’ manuals or website has been verified by Wagner, this is indicated as such, and not indicated as verified if a verification process has not been completed by Wagner for that species. Wagner is not responsible for any 3rd-party oversights or errors in their (the 3rd-parties) published SG values.

Where no published average SG value could be found for a species for the wood volume at 12% MC and oven-dry weight basis, Wagner has derived the proper SG value through a robust algorithm (see detailed explanation below under the heading ‘Specific Gravity (SG) Values of Wood and Their Referenced Moisture Content’).
 


 
Specific Gravity (SG) Values of Wood and Their Referenced Moisture Content

 

Wagner Meters’ moisture meters’ species settings are calibrated to wood samples that are at a nominal 12% moisture content (MC). It should also be recognized that the measurement accuracy of non-pin wood moisture meters is almost solely dependent on wood density; that is because wood species that have differing wood density but the same absolute amount of water will have different MC values because the definition of MC is the ratio of water weight to wood weight. Some online and other technical references that cite specific gravity (SG) values for different wood species list the SG when the wood is a different MC other than 12%. For example, some SG values listed are the values when the wood is dried all the way down to where the MC is actually zero. Other listed values are when the wood is “green” at perhaps 80% MC or even higher.

The reason that it matters what the MC was when the SG was determined is that the volume of a wood sample will shrink when it is dried down from high MC values to lower MC values. So as the volume of the wood sample shrinks, the density (SG) of the wood increases because the formula for the wood density is the weight of the wood sample divided by the volume of the wood sample, or more simply the ratio of the weight of the wood to its volume. As the weight stays the same during shrinkage, the volume decreases. Online and other references will not only provide SG values at some specific MC but also their “shrinkage ratio”. The shrinkage ratio is defined to be the percent of the volume of the wood that shrinks per decrease in MC value. For instance, one might see a 2% shrinkage ratio which means that for every 1% drop in MC the wood will shrink by 2% of its volume.

Wagner chose to calibrate its meters at a nominal 12% MC because this is close to where most wood will be in service and will be measured by our meters. Therefore we publish SG values for wood species to be used by our meters that correlate to a 12% MC value. Since online and other references publish SG values at sometimes 0% MC or “green” MC, you will often see different values online than what we publish. We correct these published values by applying correction factors based on MC at referenced SG values and shrinkage ratio published values. It should be noted that a wood sample will not begin shrinking significantly until the MC drops below fiber saturation point, which is generally between 28% and 32%, so we use 30% as the average fiber saturation point.

As an example, let’s say we have a published SG value of 0.50 referenced to 0% MC with a shrinkage ratio of 0.1% of volume per percent MC. We want to convert to an SG value referenced to 12% MC. A sample at 12 % MC will be 1.2% larger in volume (swells 12 * 0.1%). Since 0.50 equals the weight of the sample divided by volume, we now know the volume will actually be 1.2% larger, so the SG should be adjusted by a factor of 1 divided by (1 + 1.2%) or 1 divided by (1.012) = 0.50/1.012 = 0.49). So, in this specific case, the 12 % MC referenced SG value will be slightly less than the published value referenced at 0% MC.