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
WaHopea odorata0.63
WaciwaciSterculia vitiensis0.34
WadaraCouratari pulchra0.534
WahooUlmus alata0.65
Juglans cinerea0.38
Juglans nigra0.55
Juglans nigra0.55
Pinus glabra0.44
Pinus palustris0.59
Triplochiton scleroxylon0.32
WanakwarVochysia tomentosa0.52
WanakwariVochysia ferruginea0.52
WanakwariVochysia guianensis0.52
Wana-KwariVochysia guianensis0.52
WananiaMinquartia guianensis0.83
WanekwalieVochysia guianensis0.52
WangaStaudtia stipitata0.79
WanguCalophyllum inophyllum0.55
WanguCalophyllum tomentosum0.59
WaniniIrvingia gabonensis0.76
Turraeanthus africanus0.51
WantalIntsia bijuga0.65
WantonMorus mesozygia0.71
WarasarHeritiera javanica0.65
Pterocarpus indicus0.57
WaroeasiIntsia bijuga0.65
WaroesiVirola surinamensis0.51
Tabebuia serratifolia0.99
Tabebuia serratifolia0.99
Tabebuia serratifolia0.99
Tabebuia serratifolia0.99
Fraxinus nigra0.49
Fraxinus pennsylvanica0.56
Fraxinus pennsylvanica0.56
Water BeechCarpinus caroliniana0.64
Ulmus americana0.50
Nyssa aquatica0.50
Water GumSyzygium buettnerianum0.73
Water HickoryCarya aquatica0.621
Acer rubrum0.54
Water OakQuercus arkansana0.53
Water OakQuercus nigra0.631
Quercus palustris0.63
Water tupeloNyssa aquatica0.501
WathoBrachylaena hutchinsii0.85
Juglans nigra0.55
Triplochiton scleroxylon0.32
Triplochiton scleroxylon0.32
WeVirola surinamensis0.51
WeedeePodocarpus guatemalensis0.54
Weeping WillowCasuarina equisetifolia0.87
Tabebuia serratifolia0.99
WeideSalix alba0.38
Salix nigra0.39
Terminalia superba0.40
WeissbucheCarpinus betulus0.61
Pterocarpus soyauxii0.64
WengaPiptadeniastrum africanum0.63
WengeMillettia laurentii0.8114
WengeMillettia stuhlmannii0.8314
WensoneMusanga cecropioides0.23
WepaBerlinia acuminata0.64
WeruAnisoptera costata0.52
Pometia pinnata0.60
WeseleIntsia bijuga0.65
West African CordiaCordia platythyrsa0.39
Western HemlockTsuga heterophylla0.44
West Indian BoxwoodGossypiospermum praecox0.77
Cedrela odorata0.39
Hymenaea courbaril0.83
West Indian MahoganySwietenia mahagoni0.57
West Indian Maracaibo BoxwoodGossypiospermum praecox0.77
Albizia lebbeck0.543
West Indies MahoganySwietenia mahagoni0.57
Picea rubens0.40
WestaAlnus nepalensis0.26
Alnus rubra0.41
Thuja plicata0.32
Abies grandis0.37
Abies lasiocarpa0.32
Populus balsamifera0.34
Populus trichocarpa0.35
Western Black WillowSalix alba0.38
Salix nigra0.39
Western CatalpaCatalpa speciosa0.37
Western CatawbaCatalpa speciosa0.37
Thuja plicata0.32
Abies amabilis0.43
Abies concolor0.39
Abies grandis0.37
Abies lasiocarpa0.32
Abies magnifica0.38
Abies procera0.39
Western hackberryCeltis occidentalis0.53
Western HemlockTsuga heterophylla0.451
Tsuga heterophylla0.45
Tsuga heterophylla0.45
Pinus contorta0.41
Western LarchLarix occidentalis0.521
Acer macrophyllum0.48
Betula papyrifera0.55
Pinus ponderosa0.40
Alnus rubra0.41
Western Red CedarThuja plicata0.321
Thuja plicata0.32
Pinus ponderosa0.40
Picea engelmannii0.35
Picea sitchensis0.40
Larix occidentalis0.52
Betula papyrifera0.55
Abies grandis0.37
Western White PinePinus monticola0.351
Picea engelmannii0.35
Western White SprucePicea glauca0.363
Pinus ponderosa0.40
Hymenaea courbaril0.83
Westindisches BuchsGossypiospermum praecox0.77
Hymenaea courbaril0.83
WewokoMitragyna stipulosa0.53
Pinus strobus0.35
Prunus serotina0.50
Whistling PineCasuarina equisetifolia0.87
Terminalia superba0.40
White AfzeliaAfzelia pachyloba0.62
White AshFraxinus americana0.601
Fraxinus pennsylvanica0.56
Abies concolor0.39
Abies lasiocarpa0.32
White BalticPicea abies0.43
Tilia americana0.37
White BirchBetula papyrifera0.533
White BombayTerminalia procera0.54
White BombwayTerminalia procera0.54
White BombweTerminalia procera0.54
Prioria copaifera0.42
Chamaecyparis lawsoniana0.43
Chamaecyparis nootkatensis0.44
Chamaecyparis thyoides0.32
Libocedrus decurrens0.37
White CedarMelia azedarach0.51
Thuja occidentalis0.31
Taxodium distichum0.46
White Cypress-PineCallitris glauca0.591
White DealPicea abies0.43
Diospyros virginiana0.71
Ulmus americana0.50
Abies amabilis0.43
Abies balsamea0.35
White FirAbies concolor0.391
Abies grandis0.37
Abies lasiocarpa0.32
Abies magnifica0.38
Abies procera0.39
White FirPicea abies0.43
White HaiawaballiTetragastris altissima0.74
Tsuga canadensis0.40
Tsuga heterophylla0.45
Carya tomentosa0.72
Ilex opaca0.55
White LauanShorea contorta0.374
White LauanShorea leprosula0.504
White LauanShorea leptoclados0.384
White LauanShorea smithiana0.434
Terminalia superba0.40
Robinia pseudoacacia0.69
White MahoganyVochysia hondurensis0.52
Turraeanthus africanus0.51
Acer rubrum0.54
Acer saccharinum0.47
Acer saccharum0.63
White MerantiShorea assamica0.514
White MerantiShorea cochinchinensis0.504
White MerantiShorea hypochra0.584
White MoraMora excelsa0.89
White MulberryMorus alba0.60
White OakQuercus alba0.681
Quercus bicolor0.72
Quercus macrocarpa0.64
Quercus michauxii0.67
Quercus stellata0.67
White OakQuercus virginiana0.84
White OliveTerminalia amazonia0.76
White OliverTerminalia amazonia0.76
White OliverTerminalia amazonica0.76
White OlivierTerminalia guyanensis0.60
White PinePicea abies0.43
Pinus monticola0.35
White PlanchonellaPlanchonella euphlebia0.89
Liriodendron tulipifera0.42
Fraxinus americana0.60
Sassafras albidum0.46
Pinus sylvestris0.45
White SirisAlbizia procera0.55
Abies balsamea0.35
Picea engelmannii0.35
White SprucePicea glauca0.363
White StringybarkEucalyptus globoidea0.70
White ThinganHopea odorata0.63
White Tulip OakPterygota horsfieldii0.65
Juglans cinerea0.38
White WillowSalix alba0.38
White YemeriVochysia hondurensis0.52
Liriodendron tulipifera0.42
WhitewoodPicea abies0.43
Populus deltoides0.40
Tilia americana0.37
Tabebuia serratifolia0.99
WiathoBrachylaena hutchinsii0.85
Wild AlmondPygeum turnerianum0.44
Prunus serotina0.50
Wild CashewAnacardium excelsum0.33
Wild CherryPrunus avium0.5813
Prunus serotina0.50
Wild DateAleurites moluccana0.14
Wild MangoIrvingia gabonensis0.76
Wild NutmegVirola surinamensis0.51
Carya aquatica0.62
Wild PinePodocarpus guatemalensis0.54
Wild Pitch PinePodocarpus guatemalensis0.54
WilgSalix alba0.38
Salix nigra0.39
WillowSalix alba0.38
WillowSalix fragilis0.38
Salix nigra0.39
Tilia americana0.37
Willow OakQuercus phellos
0.691
Winged ElmUlmus alata0.65
WishmoreTarrietia utilis0.54
WiswiskwariVochysia ferruginea0.52
WiswiskwariVochysia guianensis0.52
Witte MoraMora excelsa0.89
Turraeanthus africanus0.51
Tabebuia serratifolia0.99
WontonMorus mesozygia0.71
Turraeanthus africanus0.51
WosimaTieghemella heckelii0.60
WosimeTieghemella heckelii0.60
WossieVochysia guianensis0.52
WowovokoMitragyna stipulosa0.53
Wych ElmUlmus glabra0.53

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.