THE USDA ECONOMIC BOTANY LABORATORY’SDATA BASE ON MINOR ECONOMIC PLANT SPECIES

James DukeU.S. Department of Agriculture, Beltsville, Md.

The world is fed mainly by a dozen plant species,and most agricultural countries have specialists fortheir country’s major crops. The world also hasthousands of minor economic species, which po-tentially are as important ecologically and econom-ically as the big dozen, but there are not enoughspecialists to study them. There is an overwhelm-ing number of climatological, pedological, anthro-pological, latitudinal, and biological variablesassociated with these minor species. The EconomicBotany Laboratory (EBL) of the U.S. Departmentof Agriculture (USDA) is trying to gather data onthese potentially economically useful species.

In 1971, USDA asked me to develop an informa-tion system on potential alternative crops for nar-cotics. With no computers available, I set up a man-ual information retrieval system of transparenciesfor screening 1,000 economic plants as potentialsubstitutes. In 1972, I was encouraged to abandonthe transparencies for computers. Now, 10 yearslater, there are many data in the computer. How-ever, the computer bill for 1981 was over $50,000,and with the loss of our support from the NationalCancer Institute, we can no longer afford to keepthe data bases online.

Data Base Files and Subsets

Some of our files and their subsets are listedbelow, subjectively ranked in decreasing order ofimportance to USDA’s Beltsville Agricultural Re-search Center.1. ECOSYSTEMATICS

Germ Plasm Donor Subset (mailing list)Monthly TemperatureMonthly PrecipitationSoil pHSoil Type [limited)Salinity (more limited)Tolerances (not computerized)

2. YIELDPhytomass SubsetCultural Subsets

3. CLIMATEWernstedtQuestionnairesPublishing Experiment Stations

4. NUTRITIONFood Composition TablesWatt and MerrillWealth of IndiaMiller (1958)Gohl (1981)ZERO-MOISTURE SUBSET

5. AGROFORESTRYEcology SubsetGermination Subset

Cultural SubsetNutrition SubsetUtilization SubsetYield SubsetWood Characterization SubsetPest SubsetINTERCROPPING

6. PEST (fungi and insects only)7. ETHNOMED

Colloquial Name SubsetPesticide SubsetPharmacologically Proven SubsetCancer SubsetMalaria SubsetGeography SubsetAilment SubsetSource

One of our most productive activities was mail-ing over 1,000 questionnaires worldwide to scien-tists and extension people, intentionally emphasiz-ing developing countries. Within 2 years, over 500people had responded, sending published and un-published ecosystematic data (annual rainfall, an-nual temperature, soil type, soil pH, elevation, etc.)on economic plants and some weeds and nitrogen-fixing species. These data, related to about 1,000species, now are incorporated in the EcosystematicFile (fig. 1) and are tabulated in The Quest forTolerant Germplasm (4).

A success story addressing the multimillion-dol-lar problem of iron-efficient sorghum germ plasmillustrates the potential value of the ecosystematicfile in seeking germ plasm for extreme environ-ments (6). Scientists from the Plant Stress Labora-tory were incredulous at the high soil pH reportedfor Sorghum bicolor in the file. Most sorghums arechlorotic and nonproductive on alkaline soils. Thescientists asked for more information on the highpH sorghum. Since each species in the file is re-corded with the name and address of the reportingscientist(s), the computer was able to provide amailing list of 14 correspondents who reportedsorghum at pH 7.5 or higher. Letters were sent to10 of the correspondents. Four responded withseed, two lots of which were iron-efficient sorghumwhich grows and produces without chlorosis on al-kaline soils in the Western United States. Now weare cooperating with the USDA Plant PhysiologyInstitute in a search for soybeans tolerant toaluminum toxicity.

The USDA Economy Botany Laboratory’s Data Base on Minor Economic P/ant Species ● 197

Figure 1 .—Sample Page From “The Quest For Tolerant Germplasm”.—

Scsam um radialum Wild scsn]nc ‘1’111 1’,1[ 4.3-5.0 2 5 - 4 0 25-27 AF 64Scstbania birpino~a Canicha Wm Tvm A,S 4.3-7.5 G-J3 16-29 111 12,24.$esbania exalt ala Ilcinp se bania Wm Tdm P,A,l I 4.5-7.3 7-25 13-27 NA 12Sctaria ilalica Ilulian nil Ilct Clnw Tvw A,G 5.0-8.3 3 - 4 2 6-27 CJ 18Sctaria sphacelata Golden L:nolhy (Mm Tvm P,G 4.3-7.1 7 - 3 3 11-27 AF 18,36,54

Sicana oriorifera CilSClt)i311i na Sdm Tvm P,V 5.0-8.0 7 - 2 8 21-25 SASimarouba glauca Aceituna SmSim mond$ia Chirrensis

‘i’dm P,s:r 5.3-8.0 1 1 - 2 5 2 1 - 2 7 M AJojoba Wxt ‘rd P,S,T 7.3-8.2 2-11 16-26 MA 56,*1OO

S8napi3 alba White rnuslurdSmilax ari~tolochiifolia

Blnw Trl A,l[ 4.5-8.0 4 - 1 8 5-24 ME 24Sarsaparllla Wm Sm P,S,L 17 1 8 - 2 3 M A

Solarium aethiopicum Mock tolnato Cm Tm P,S (3.2-6.2 9 - 4 0 9-25 AF 24So fanum auiculare A u s t r a l i a n nifjhtshrrde C r n w W d m P,S,T 5.5-8.2 7 - 1 3 12-17 AU 46,48,92Solarium ferox Ram-bcgurr Cm Tw P,}l 4.5-5.0 7-42 83-27 111,11 24Solarium gilo Gilo Tm P,S 4.3-4.8 2 7 - 3 3 26-27 AF 24Solauum hyporhodium Cocona Sdw P,s 6.5-7.3 7 - 3 1 21-23 SA

Solarium incanum Sodom nj)plc Sdm 5.5-7.8 8 - 1 7 1 9 - 2 3 AF,III 24Solarium indicurn Indian rrlghlshade S d m ‘rxw 4 . 3 - 7 . 8 2 - 4 2 1’3-27 11[,11 24Solanurn khasianum S o l a r i u m khasianum C w Wm 11 5.0-6.0 9 - 1 3 1 3 - 1 5 1{1 24Solanurn Iociniatu m Kangaroo apple Cmw W d P/A,S,T 5.6-8.2 7-11 12-15 AU 48,92Solanu m mucrocarpon Native eggplant Ww Tdm 11,s 4,3-5.2 13-37 18-27 AII” 36

Tolatturn melongcna Eggplant Csw ‘rxw P/A,ll 4.3-8.7 2 - 4 2 7 - 2 8 CJ,III 24,36,48So[,lr[u m m uricntu m Melon-pear S d m Tri 1’,s 5.7-7.3 7 - 1 5 18-25 SA 24Solanu m niqum Dlack nightsl]ade Bw T x w A,l{ 4.3-8.4 2 - 4 2 5 - 2 7 AF,ES 24,36,48Solun utn q UI loense Lulo C m w T d PJI, S 5.8-8.0 7 - 3 1 11-25 SA 24Solarl um (oruum Tcrongtill Cm ‘1’vw 4 . 3 - 8 . 7 7 - 4 2 9 - 2 9 N’IA }{ I 24

Solan u m lu beru$u m——

I’olirto B m w TVW A,l{ 4.2-8.3 3 - 4 6 4 - 2 7 SA,hl A,ES 24,3i3,48–Solcrrostemon rofundifolius I lausa potato Sm ‘I’d P,ll 5.0-5.0 13-17 23-26 Ak’ f84

Sorgliastrum avenaccurn Indian gritss Wm ‘I’d P,G 5.6-7.1 11-17 12-26 NASorghum X almurn Almum ~orghum Csw Tvd P,G 5.0-8.3 3-25 9-26 SA 40Sorghum bicolor Sorghum Csw ‘1’tw A,G 4.3-8.7 4 - 4 1 8 - 2 7 CJ,II1,ME 2 0

t For nuthorilics on mosl of lhcsr spcci,s, scc I)ukr rrnd Tcrrcll (1974).~ F o l l o w i n g }Ioldridgr (1!347); T-Tropic~l, S-Sul>tropical, W-Wnrnl Trmprra~c, C - C o o l Tcmpcrnte, i)-llorcnl; x-Desert, t-Thrsrn, s-Steppe,

v- Vrry Dry, d-Dry, m-hloist, W- WC 1 and r-Rat ~1.~ A - A n n u a l , Il=i)icnnial, P-i’crennial, I’/A-Perclnial lmatcd as an annual, II=llcrb, G-Grass, L-Liana (woody vine), S-Shrub, T-Tree, V-

1 lcrbaccous vine. ●

1Avcrflgc of monthly means wilh valuci below 00(’ trcalcd rrs O.Ccnlcr of divcrsily, trascrl Iargcly on Zcvcn nnd 7,hukovsky (1975) and Plant Taxonomy files. The first symbol cilcd is possibly a center oforigin. , CJ=China-Japan, 1 l-lndocllilla-l llrloncs’:1, AU-Auslralia, 1+1-l linduslani, CI~-Conlrrrl Asia , NE-Near East, ME-Mcriilcrrnncan, AF-A[rlcn, ES-Eurosibcrinn, SA-South Amcricn, hl A-hlidrllc A m e r i c a , NA-Norlh Amrricn. For space conscrvnlion, nrr Inorc lhnn lhrce ccnlcrsnrc listed.

tl’ Diploid chromosome numbers based Inrgcly on i rlorov (1969), Zcvrn and Zhukovsky (1975), and unpublished compilation by Mac}ierrry Sllff.Only three counls nrc Iislcd IIrrY, bul mnl)y more mny hnvc been rcporlcd.

SOURCE: Duke, J. A., “The Quest For Tolerant Germplasm,” ch. 1, pp. 1-61, ASA Special Symposium 32 “Crop Tolerance to Suboptimal Land Conditions” (Madtson,Wis.: American Society of Agronomy, 1978).

Yield File

In addition to data from the questionnaires, datafrom publications of experiment stations have beenentered into the Yield File. We regret that we can-not keep up with this literature; the entries probablyaccount for less than 1 percent of the yield datapublished annually by experiment stations, By in-creasing the data included in this file, which is im-possible at our current level of fundin,g peoplecould be told the yield of exotic crops (with variouscultural inputs) grown in areas ecologically similarto theirs. The Yield File is clean and useful now,though off-line. With major backing, it could help

strategists predict yields of new crops in particularareas.

For a brief period, funding was available to pro-mote one subset of the file, the Phytomass File (fig.2). (Phytomass is defined as aboveground dry-mat-ter yields of plants.) Department of Energy (DOE]support for that file has been discontinued butsome institutions such as DOE or Oak Ridge mayhave similar files. Data from the Phytomass Filesupport our early contention that C4 grasses areroughly twice as productive as C3 grasses, whichare in turn roughly twice as productive as legumes.Availability of this kind of information could save

198 ● Plants: The Potentials for Extracting Protein, Medicines, and Other Useful Chemicals—Wo&shop Proceedings

Figure 2.–Sample Page From Phytomass File

. .DA~ xm

U n d e r S o u r c e , M - Berbase A b s t r a c t

SOURCE: Duke, J. A. “The Gene Revolution," paper No. l, pp. 89-150,C)ffice of Technology Assessment, Background papers for Innovative BiologicalTechnologies For Lesser Develped Countries (Washington, D.C; U.S. Government Printing Office, 1981)

The USDA Economy Botany Laboratory’s Data Base on Minor Economic Plant Species • 199

countless hours and dollars in screening projectswhere maximum biomass production is a priority.

Climate FileThe easiest file acquired was the Climate File. It

is the computer tape to Wernstedt’s World ClimaticData (1972) and was purchased for less than $200.USDA colleagues have converted the temperaturedata from Fahrenheit to centigrade, and the rain-fall and elevation to metric units. The monthlymeans for these 18,000 stations now are compati-ble with hundreds of climatic figures gatheredthrough questionnaires and publications. Monthlyprecipitation and temperature data for about 20,000stations now are integrated into the Climate File.A species’ ecological amplitude can be determinedby using this file in conjunction with ecologicaldata for geographical areas from which the speciesis reported. For example, if one wanted to knowthe ecological amplitudes of a species that is notin the Ecosystematic File, one could consult her-baria and publications for locales where the plantgrows, choose those that occur in the Climatic Fileand, using the computer, obtain climatic highs,lows, and means of these areas. Further, one couldpick potential germ plasm sources that are mostsimilar ecologically to the germ plasm recipient.This important germ plasm matching capability ap-plies not only to minor, underused economic plantsbut to cultivars and varieties of the big dozen. Asample page from an early version of an economicamplitude paper appears in figure 3. This file hasbeen used in the USDA Plant Physiology Institute

at Beltsville by colleagues who are interested in thetropicality of members of the Malvaceae. They arestudying the distribution of malvalic acid, an acidpossibly involved in responses to temperaturestress in cold- and heat-tolerant mallows.

In a seminar at Beltsville on March 17, 1982, Dr.G. L. Stebbins introduced a list of cold-tolerant toheat-tolerant legumes, speculating that the greaterthe DNA volume, the greater the cold tolerance.Without consulting the Handbook of Legumes ofWorld Economic Importance (5), wherein theecosystematic amplitudes of species are published,I predicted that the legumes’ mean annual temper-atures would line up inversely with Stebbins’ DNAprediction. The lineup was almost perfect, as de-picted:

DNA M e a nvolume (from temperature 0C (from

Stebbins seminar) Handbook of Legumes)Vic ia faba –—–––——– 26.7 12.1Pisum sativum ., ., . . . . . 9.8 12.9Phaseolus vulgaris . . . . . . . 3.7 19.3

Glycine max . . . . . . . . . . . . 2.2 18.2Lablab purpureus. . . . . . 0.7 21.9

The Climatic File can be used to address prob-lems in the global carbon cycle. Tropical forestsplay an important role in the global carbon cyclebecause they store 46 percent of the world’s ter-restrial carbon pool (1). Brown and Lugo presenteddata for each of several Holdridge Life Zones, pro-jecting total forest biomass, soil carbon content, netcarbon content, net primary production, wood pro-duction, and leaf litter production. The EBL has for-mulae for converting its 20,000 climatic data sitesinto Holdridge Life Zones and, using a computer,

Figure 3.—Sample Page Showing Ecosystematic Data For Malvaceae

G!Ultl A AS IATIU L. 6.6 20.2 4:.9 (4) 14.7 II .4 27.4 (4) 6.8 ;.2 7 .’=1-.i LA ~LIA A

(: \

hch. 9 0 14 K z- 8 (6) ~9 A 6 26 6 (6 4 5 s- 1 (4TRllhFFllA W?&IOU J&. 6:7 20:L 4;:9 (2# 18:7 24:6 27:4 (11; 5:0 0:: ;:1 (9;TF.l WHITA ~1’WA bJ 6.7 1 1 . 1 42.9 1s.7 23.4 2 7 . 4 (6) S.o 0.3 7.1 (4

FMILY kwvmw Z.b 1 4 . 1 4 2 . 9 (S13) 7.0 22.6 29.9 (312) 4.3 6 . 3 8.7 (211;UIXOUS ~L&’ti (L. ) Wench. 2.6 14.3 J1 .0 (107) 11.1 24.4 Ins (}~) 4.J :.; :.7 (4;)tidKrX2L5 K?K2WTUS A4edlk e. 1 1s .6 40.3 5.0 . .:

u(4/) 4 . . 0.6 L i z 16;d$iuu haura *X Iuvra &k )7 .

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(3 1 S3 (:)(12;

IX&SYPIU4 lMRMD2JSE L.;:s ;:; 6:4

4.9 13.5 40.3 (2S) t.4 22.6 27.6(1)

(25) 4.S 6.S 8.4 (19:KKsYPILK! KWJACUN L. S.1 11.9 4:,9 [16) 3.2.s 20.7 :7. $CUiTYPIU4 HIW2.MM L. 2.9 11.3 27.8

5.5 6.9 B.4 (13’(M) 7.O ~@. ? ~~ .*

~b CA\~= L6.6 6.4 ;3: t

SINMJll FFA L:s - 14 96:: 17:9 4Z:9

L 61 a-H1 P,] KIIS ~;2; (.~1

6:1 t:: (18,~A L. . . . . 5 (Ii) N -., 2 . . .> ,, . . . (.1s.

FAMILY =~ 4.8 ]6.9 42.9 (136) 1$.0 2s.3 28. SK7B4X CEIM L,rclti \L. ) tact-u-t. 4 .&

Rlo~ n.lrl. 13.5 . ., . (l (/ 7- 7 1->. .0. 4 ( 7 ) 4.3 S.6 6.6 1

FAMILY Sl_EWXL~ 4.8 16.8 42.9 (141) IS .0 25.4 29.9 (140) 4.3 6.2 8.7 (66)CTIA N2D41NATA ( B e a m . ) Wwtt C Emil. 6.4 19. B 4 0 . 3 (12) 21. S 2S.2 26.6 (12) 4.5 5.5 1.0 (7,

1S.6 22.0 ~.8 6) 25.3 2 S . 4 2 6 . 6 (6) 4 . s 4.5 ~.> (4). . . 3 iLi7. . 5 2“0 .5 (> I 4.8 6.4 5.0 (31

TtiSIBW4A OfXO L. 4.8 16.3 42.9 (ltij 11. o 2s.3 2! .s (]08j 4 . 3 6.4 6.7 (i3j

SOURCE: Duke, J. A., “Ecosystematlc Data on Economic Plants,” (Wart. J. crude Res. 17, No. 3-4, 1979, pp. 91-110,

200 ● Plants: The Potentials for Extracting Protein, Medicines, and Other Useful Chemicals—Workshop Proceedings

can generate Holdridge Life Zone maps for coun-tries not now mapped in the Holdridge system. Wethen could project standing biomass, total carbon,and annual productivity of the zonal forests,based on Brown and Lugo’s numbers or refine-ments thereof, and give real or projected yieldfigures for high-biomass grasses, energy-tree plan-tations, or conventional crops for these HoldridgeLife Zones. This could provide some guidelines forchoosing the best crop-agroforestry combinationsfor agricultural development in Third Worldcountries.

We believe that the climate of some remote areacan be deduced by checking the ecological ampli-tudes of dozens of perennials growing there betterthan by measuring the rainfall and temperature for1 year. The fig, scuppernong, and pecan at myHoward County farm are near their northern pro-ductive limits; the ginseng, rhubarb, and sugarmaple near their southern productive limits. Basedon these species, the mean temperature at my farmcan be predicted to be between 110 and 130 C.

Dr. Peter Raven, director of the Missouri Botan-ical Gardens, asked us at what locations in theworld the climate was most similar to that of theMissouri Botanical Garden. If asked simply for an-nual temperature and annual precipitation, thecomputer would indicate many places that do nothave the temperature extremes of St. Louis’ conti-nental climate. Introductions from maritime cli-mates with identical mean temperatures might bekilled by the summer heat and/or winter cold of St.Louis. A continentality variable, which will dif-ferentiate among climates with similar mean an-nual temperatures but different vegetational poten-tial, has been added to the Climate File.

In October 1982, EBL was asked to name localesin Latin American where date palm would grow.As a test case, Dr. Atchley at USDA and I each de-voted no more than 4 hours to this query (app. Iand II). The difference in conclusions reached isdue to Dr. Atchley’s assuming rainfed conditionsand basing his projection on actual reports for datepalm, and my assuming an irrigated situation be-cause artifical or subsurface irrigation is implicitin most of the good date-growing areas I cite. Thecomputer provided lists of possible sites for datepalm under both irrigated and rainfed conditions,and eliminated hours of searching through 20,000climatic data points.

The narcotic-replacement program led us to thecoqueros, the cocaine-leaf chewers of the Andes.The coca leaves chewed by these Andean Indiansare high in calcium and iron, more so than any

plant food in the Food Composition Table for LatinAmerica (fig. 4a). Calcium and iron, as well as cer-tain vitamins and proteins, often are deficient indiets of the farmers we were trying to divert fromcultivating the coca (“cocaine”) bush. The problem,therefore, was one of both nutrition and crop sub-stitution. What commercial food crops could thefarmer grow as substitutes for coca? To answer this,we needed to know their climate. However, theymight be 100 miles and 10 mountain ranges awayfrom the nearest climatic recording station (thatceased recording 10 years ago). This quandaryspawned our Ecological Amplitudes of Weeds pro-gram. We added weeds to our questionnaires tohelp predict climate in remote areas (fig. 5).Another use of the Ecological Amplitudes of Weedsprogram is in mapping the potential for an alienweed to spread in the United States. Determiningecological amplitudes of a weed by consulting itsdistribution and extracting climatic data from theClimate File, we can determine where in the U.S.the climate is most closely and least closelymatched.

Nutrition File

For the Nutrition File, we used at least one credi-ble entry for each plant species in Food Composi-tion Tables for East Asia, Africa, and Latin Ameri-ca, from Watt and Merrill’s Composition of Foods(Agriculture Handbook No. 8) and from The Wealthof India (C. S. I. R., 1948-76), computerizing the prox-imate analyses of hundreds of botanical. I scoredthe plants’ nutritive contents (elements, vitamins,calorie and fiber content) as extremely low (E), low(L), high (H), or very high (V), relative to USDA’srecommended dietary allowance (RDA) (fig. 4b).Unfortunately, I had overlooked Miller’s Composi-tion of Cereal Grains and Forages (1958), whichconsolidated thousands of forage plant analyses, Nosooner had I finished adding this information thananother massive compilation with numerous newdata on forage analyses was published (7). My col-leagues at USDA and I are entering these data intothe computer file which we hope will be tabulatedand published by CRC next year.

We devised a computer program to convert ouras-purchased proximate analysis file to a zero-moisture basis (fig. 6). To ensure that only completeproximate analyses are used, the computer usesonly those columns for which the sum of water,protein, carbohydrates, fibers, and ash is 100 per-cent (±1). The computer then multiplies all col-umns except water by 100 ÷ (100=X), where x

The USDA Economy Botany Laboratory’s Data Base on Minor Economic Plant Species . 201

Figure 4A.—Nutritional Composition of CocaNutritional comparison per 100 g of Coca Leaves with other Latin American Plant Foods

FOOD ITEM 7 in Cal H2 O Prot. Fat Carb. Fiber Ash Ca p Fe V i t Al T h i a R i b Nia Vit Csample g g g g g g mg mg mg IU mg mg mg mg

. — — —

San Francisco coca (1) 305 6.5 16.9 5.0 46.2 14.4 9.0 1540 911 45.8 Ilxm 0.35 1.91 1.29 1.4Bolivia coca (3) –? 8.8 — 1.6 42.4 8.0 53 — — — — — — — —

Peru coca ( 3 ) — 103 18.7 — — 17.5 4.6 2038 363 7.9 9,000 0.81 1.55 6.17 —- .

COCA AVERAGE {7) — 8.5 18.8 33 44.3 13.3 6.3 1 7 8 9 6 3 7 2 6 . 8 10,000 0.58 1.73 3.7 1.4

PLANT FOODAVERAGE (50) 279 40.0 11,4 9.9 37.1 3.2 2.0 99 270 3.6 135 0.38 0.18 2.2 13.0

Nuts & Seeds (10) 521 9.9 16.8 36.0 28.2 3.6 3.1 273 522 4.3 17 0.78 0.28 5.2 2.1

Pulses ( 10) 354 11.3 25.4 5.0 55.1 5.5 33 102 398 7.1 20 0.58 0.24 2.25 1.9C e r e a l s ( 10) 352 11.5 11.7 3.7 71.0 4.0 2.1 74 346 4.8 13 0.41 0.25 2.7 0.8Vegetables ( 10) 74 87.3 1.8 0.4 16.9 1.5 0.9 26 52 12 595 0.09 0.05 1.0 31.0

Fruits ( 10) 93 79.6 12 4.5 14.1 1.4 0.7 20 33 0.8 35 0.05 0.06 0.08 29.0

SOURCE” Duke, J. A., Aulik, D., and Plowman, T. “Nutritional Value of Coca,” Botanical Museum Leaflets, vol. 24, No. 6, (Boston, Mass.: Harvard University, 1975), pp. 113-119.

equals water percentage. The completely new andunique table has hundreds of species compared ona zero-moisture basis. The Nutrition File (as pur-chased or zero-moisture) can be linked through aspecies’ scientific name to the Yield File to convertyields to protein per hectare instead of grain perhectare, and to the Ecosystematic File to showwhich will yield the most leaf protein per hectareunder any specified combination of annual temper-ature, annual precipitation, soil pH, etc.

Before the National Cancer Institute discontinuedits support for the EBL data base, we started a fileon biologically active compounds to parallel theNutrition File. It indicated the toxic compoundsand their LD50’s for plant genera (fig. 7). We regretthat other quantitative data were omitted, Dr.Farnsworth’s comprehensive NAPRALERT pro-gram dwarfs our attempt at computerizing biolog-ically active compounds in plants. Since he alsouses plants’ scientific names, his pharmacologicaldata could be sorted against any one or all of ourdata files, using the scientific names to link the twodata bases.

Ethnomed File

It is ironic that the Ethnomed File (fig. 8), withwhich I worked most closely for nearly 5 years, isnow the lowest priority file. The file was built toencourage Third World countries to supply medic-inal and poisonous plants for a collaborative screen-

ing program with the U.S. National Cancer Insti-tute. With 88,000 entries, the Ethnomed File isprobably the largest extant computerized data basefor folk cancer remedies and is quite good for gen-eral folk remedies. Pesticidal activities, of greatercurrent interest to USDA, also are included (see fig.9 for insecticide subset sample). This file can in-teract with any other file through the same scien-tific name.

Ethnomed is not dead; it lives on as a much con-sulted printout. For example, we have been askedto help an NIH contractor prepare a prioritized listof Nigerian species for antimalarial screening (fig.8). The malaria entries marked with an asterisk con-tain compounds with proven antimalarial activity.The species marked with a double asterisk corrector alleviate malaria. Unfortunately, the commonname file is incomplete. It would be useful to manyagencies, since many plants are recorded by com-mon rather than scientific name. Interlocking sci-entific names with the name of a country from theEcosystematic File should show not only which an-timalarial species occur in that country but shouldgive the names and addresses of the people whoreported them, Using the ecosystematic amplitudesof the target species, the computer could indicatethe country’s climatic stations within the ecologicalranges of the target species. For example, the com-puter could name many antimalarial species occur-ring in Nigeria and list villages suitable as stagingareas to search for the species.

24 - 503 0 - 83 - 14

202 . Plants: The Potentials for Extracting Protein, Medicines, and Other Useful Chemicals—Workshop Proceedings

Figure 4B.—Sample Page From Vegetarian Vitachart

wild grape (qwild lettue (1)

wild -O (f)

w i l d p l u s ( f )

uild rice

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ywtla (r)yebbmt (s)ye:;: ho lua (f)ain (f)yellow rmAti (nut)

Vith tiliifoliaLactuca taraxacifoliaI~ia gabonens~Bcqw.emiodendmn

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Lucu7u salicifoliaHauritia viniferaDioscorea dataDioscorca alata(kurbita rnaxhmCucurbita mxixatkurbiti maxkLyciua ChilunslsLyciKs chinensisRidmdmdmn heudelotflArc*As*t22hylos tmcntcsaChcnopodlm aAmosioidesDiosco-pa S po

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L L H LLHHHH;&Lh;E~EgL L H L HL HLHH L V H ::L L L L itHLLE~glL L H L L LL L L L L L .H t t E : ; flH L H L LHHLHELHEH E L H LLLLLELLHL H V V HHHHVLHVVHLHH LLHLHLLVHHHHL EV HE EEE

LU LE L H VHLHH :; LHHL L L L LL H:: LEHELHL LL LL LEHL L LL L L L L; ;’ L LEHL L H L LLLLLELLjlHLHH LHHLHEHHHHLHH H L VHL L H L HL H% H k kELLE LL ELL L H H L L :L:L L L H L L :: L L HL L V LH LL HLH

yellow vdn (1] Pseudcrantkua reticulate LL LL L H VPm Cumnmopsis eddh H;: Hw= (m Yxu elcphamipes LLLL L: LL H E VW=$ (A) Ywx elcphantipes HLHL LL LL HEH

1d . &y, f . fit, fl - fi-rt ~ - -c 1 - ldt 9- amturu, r - mot, s . s~,Sh . s-t (or M).

SOURCE: Duke, J. A., “Vegetarian Vitachart, Quart. J. CrrJde Drug Res 15, 1977, pp. 45-46.

We receive daily inquiries from all over the worldasking what herbs are used for what ailments. OneSenator asked us for opinions on various quack her-bal medicines. Another Senator has shown an in-terest in the so-called “petroleum nut” Pittosporumresiniferum (fig. 10), an energy plant endemic to thePhilippines.

Thanks to three professors in the Philippines, wenow have seed and a fairly good idea of the eco-systematic amplitudes of the Pittosporum. One pro-fessor indicated where Pittosporum resiniferumwas growing prior to widespread relocations in thePhilippines for potential energy studies. This infor-mation was paired with climate stations in the Cli-mate File to yield ecosystematic amplitudes. Rang-ing from Tropical Dry to Moist through SubtropicalForest Life Zones, the petroleum nut grows whereannual precipitation ranges from 15 to over 50 dm(mean = 27 din), annual temperature from 18-28°

C (mean = 26° C). Of 17 cases where bothtemperature and rainfall data were available to us,13 were found in the Tropical Moist Forest LifeZone, three in the Tropical Dry Zone, and one inthe Subtropical Rain Forest Life Zone. A similar ap-proach could be used to determine the ecologicalamplitudes of a medicinal plant, weed, or promis-ing new economic species from the thousands ofspecies not among the thousands already in ourcomputer.

P~pe8

We have developed the following three data baseprototypes which could be expanded readily if pri-orities dictated.

Agroforestry File: This program was developedfor several species being considered for agrofores-try. Different subfiles contain information on eco-

The USDA Economy Botany Laboratory’s Data Base on Minor Economic Plant Species . 203

Figure 5.—Ecological Amplitudes of 100 Perennial Weeds

Ecological amplitudes of 100 perennial weeds*

ACACIA FARXESLIN4.4CER SACCH4RU31.4CORUS CALWUS.AG4\T LECHkGUILL4AGROPYROS REPi3SAGROSTIS STOIJMIFERAALOPECURUS PR4TESS1S.~J”sI-s VAGISALISAfr,QpHI ~ ~~~IA/L\_DRLW’OGON GiXARDI IARCTIUYI L4PPAARRKENATHERM! EL4TIUSARTE!.IISLA ABSI>THILNARUSDO LxNuATRIPLEX CANESCENSAXOWPUS CC$PRESSUSBO13+ERIA NI\’E4BRACHIARIA MUTICABROIUS INW1lSC4LTH4 PALUSTRISC4RY.LI ILLIiWENSISCASSIA AURICUL4TAC2V5TANE4 D13WATACHEWPODILN A~DROSIOIDESCHLORIS GAY.4NACICHORILN IIN~’BUSCLITORLA TERNATEACOICCOLOBA LR’IFER4C0ROSILL4 \’ARL4COR}’LUS CORWTAC)’xw C4.RWW* -uLusCWWIXIN D.K13’LONC}’ PERUS ROTLNDUSDNTYLIS GL01ER4TADICH%’YTHIUM M!!ULATLBlDIcHo\!R4 REPEMDIGITARIA DECUllBEMDIOSP}’ROS VIRGINIAN!ECHI,WCI-MA CRUSG4LLIELELXHARIS DULCISEQUISETIJM ARVIXSEERAGROSTIS CUFW’ULAFAGUS G’lkVDIFOLIAFF5n!r.\ .l~USO!\:Jc:!FOLNICUIXM \ULGAREFR4G4RIA VIRGIfiIAMG.E.NISTA TI~ORIAG~WIfWIA IAJTEAG~}”~~+~~fl. GL’~R~

HELIAN17+US TUBEROSUSHORDELN BULFWW1tn”PARRIW!IA RUFAINUL4 HELENILNJUGMNS NIGRAJUNIPERUS CO! NUSISLESPEDEZA STRLATALESQUERELL4 GORKNI1

HUIS.4CHESUCAR FWLESh’EETFLAGLECHEGUI LL4QUACKGRASSCREEPING BL\TGRASSMEADO\< FOXTAILAL>’CE CLO\IZREUROPEW BISWHGRMSBIG BLUEST131GRMT BURDKKTALL OATGR%SS.4BSIkTH Ni3RJlW~DGIAN REEDFOURh’ISG SALTBUSHTROPICAL C4RPETGWSS~LIIEPARAGRASSSMXYl?+ BROhlEMAWN4R1GOLDPEGLVA\l~~lAMERICAN CHEs’11,’urNfEXICAATE4RHODESGRASSCHICORYBLUE PEASEAGR4PETR41LING CROWTTCHBEAKED HUELCARIx30!iBER~W’D.4GRWPURPLE WTSEDGEORCH4RDGR4SSDIA2 BLUEST131DICHOMIR4P.4XOLAGRWSPEW L~fi13\BARNYARDGRASSWTEFWJTFIELD HORSETAILWEEPING lJ3\%GRASSWZRI(AY BEECHT.4LL FLSCLIECCMION F13XELVIRGINIA StrawberryDYERS GREINWDYELIJlh’ GENTIANc~~!~x LICo~~cEJERLISAIJ31 ART ICWKEBULBOUS R4RL~’JAR4GW GRASSELE.GWPAYEBL4CK h:4L\~COMKIN’ ~’IPERJAPAM5E LESPEDEZrlmm~ BLUIDERPOD

h’d TmCmw SmCm Tvwh’t Ttv%-m StBm \(mB~ h’tSm TdiiCmh’Bm CsmCmh h’tmBmh’ h’tmCmw SdCh’ Tdw}(tSm TmwWm TvwSdh’ ?VW

Bmw KtdGrrh’ Wmhtm SmSdm TvwCsm hinCK TdwCs TvwBm TvmSdm TvwSdm TvmCmK h“dmBm CwCmK NtrnCsk TXTJBm TwBmh %Sdm TxmIidm Stm.% Tdwh’dh’ .$mBmw T\’wS&I Tdhi TwcSh’ TdCh” Sm:., --,, c.

h’ i;mBrm+’ Sd.mCm+’ h’dCmw Mm‘- lit“, ,Crrrw TmCs SdSdh’ TdwCnm’ h’dmCmh” SmBrmi Td\(dm Smlit

4.2-8.04.5- 7.35.5-7.57.0- 7.74.2-8.34.5-8.34.5-7.84.2- 4.84.5-6.26.3- 7.54.5- 7.84.5- 8.36.3- 8.25.5-8.57.3- 8.05.84.5- 7.34.3- 7.95.3- 8.24.8- 7,55.8-8.34.3- 7.3S. 8-7.35.5-8.34.3- 8.34.5- 8.55.8-8.05.8-8.05.8- 6.85.8- 7.55.0-8.34.3- 8.54.5-8.54.5- 8.35.7-7.55.0-8.34 .:-7.85.8-8.05,0-8.35.5-5.74,5-7.54.3- 8,34.5- 6.89.2 .5. :5.7-8.35.3- 7.54 . 5 - 7 . 55.8- 6.8.06.2. a-o.-4.5- 8.55.8-8.24.5-6.24 . 5 - 7 . 55 . 8 - 8 . 34 . 5 - 7 . 5

5 . 0 - 8 . 87.3- 7.8

6-405-155-4?~-63- ‘1 j5-173- 17’10-425-115-113-155-163-1 j3-405-511-40: -408-5:3-174-145-157-4?5-113-423-403-407-4211-256-404-95-123-42j.~~3 - 2 12 - 83 - 1 5g- 26

7-173 - 2 38 - 2 3

5-253-15

2-15;- :A

3-264-17

7 - 1 17-11:-::-;8

8-405-133-134-115-173-9

o-IIo-s5-12~ -50-90-60-69-122-60-110-60-60-60-11--

S-121-12s-l?o-sO-60-7S-125-50-120-12(-J-12S-125-122-11o-sO-T0-120-120-90-60-94-121-90-125-100-9()-gj- y

0-121 - 91-61 - 6

7

~;i~ .

0-54-121-60-60-63-9

--* For explanation see text.

SOURCE: Duke, J. A., “Perennial Weeds as indicators of Annual Climatic Parameters,” Agricu/tura/ A.feteoro/ogy, 16:291-294,(Amsterdam: Elsevier Scientific Publishing Co., 1976).

204 ● Plants: The Potentials for Extracting Protein, Medicines, and Other Useful Chemicals—Workshop Proceedings

000

Z - u u - z

0ko. .0

Z - u v - z o0000

..

n

u

vaJ

0dwN

m.

al

.w

00

G0000

o0

The USDA Economy Botany Laboratory’s Data Base on Minor Economic P/ant Species . 205

Chcmml

Qurnaldmr

QurnazolineQuuuc acid

Quindi.m

Qumint

Quinolme

RatonRed squtilRed thyme oilRescin.namrneReserpine

Retronwine

RetirroI

Genus a

Figure 7.— Pertinent Pages From Phytotoxin Tables

Toxins: Their Toxicity and Distribution in Plant Genera

TO\ ICIVa”b

orl ral LD, ,, 1,230 mgskn rbt LD,, , 1,870 mgsk.n mus TDLo, 4,000 m~f}’1 h’EOscu mus LDj ~, 10,000 mg

or] rat LD$ ~, 1,000 mgor] mus LD$ ~, S94 mgipr rat LDLo, 114 mgipr mus LD, ~, 190 mgml wmn TDLo, 20 mg

(4-5 U’ preg) TERor] rbt LDLo, 800 mgorl gpg LDLo, 300 mgUSA gpg TDLo, 200 mg preg TERorl ral LDj ~, 460 mgIpr mus LDLo, 64 mgskn rbt LD, ~, 540 mgscu rat TDLo, 31 g/61 V’] NEOorl rat LDj ~, 200 mgor] rat LDt ~ , 4,700 mgor] mus LD, ~ , 1,420 mgor] hmn TDLo, 14 Pp PSYiins hmn TDLo, 357 Pg PSYunk rat TDLo, 1.500 Bg

(9- 10 D preg) TERIWI rat LD, *, 1,311 rrsgivn mus LD ,,, 634 mg

Family

RubiaaaeLaura-e

or] rat TDLo, 5S mg

Clm”umb AsteraceaeO“ssusb Vjtarxae

a“sfus Cistaceae

Plant gencrs

Colipca

Dtihroa?A conitum, Angelica, A rc!ostaph>los. Cinchona,

Daucus, Euca!>”prus, Illicrum, Linunr. MOIULMedlcago, ,Vicorianc, Plsrocia, Prunus, Rosa,Terminalio, Vaccinium

Cinchona, Cou Iorcc. Enanti, RcM~w, Srr},chno$

Cinchono, Corrrus. Coutorti. Enantic, Ladenbe~,A“crolemma. Renrrjia. Stnchnos

Cilms

Glin”cidirrScillaThyrnusRauw’olfw, Torr&ziaA Istonia, A spldosperma. Bleektrio, Excaroria,

Ochro~ia. RcuW%l.fu. Tondu:ia, V’allesw. Vinca,Voawrrga

Usually combin& A msinckio, Brach.sglorris,Cwraloria, k cAu8m. L n)ilif. Lrrcll tites.Heliorropiurn, ?’i:asltcs, Stnecio, Trichodesrna,Tusrilago

M’idesprcad?

TABLE 2 (con?inucd)

Higher Plant Genera and Theis Toxins

Toxin

Cinchonidine, cinchonine, quink add, <uiitidine, quinine, s.apc..lnAwtaldehyde, tmzoic acid, oorneol, c+imc acid, CJFij’~C a&, w-

vacrol, cassja oil, cineole, cin.namaldeh~+de, cinnarnyl alcohol, citr-nellol, coumarin. cuminic a l c o h o l , c-amin.ic aldehyde, cymene,

decanal, eugeno~ eugenol methyl erlaer, formic a c i d , furfural,geraniol, hydrocyan.ic acid, isobutyric acid, meugend, isoVdmkie-hyde, isovalenc acid, launc acid, Iimonene, Wool, myristic acid,myristicin, nonJyl alcohol, phellandmm, piperonal, propionic acid,safrole, Qicylaldehyde, sal.icylic aci~ shikimic acid, tannic acid,terpineol

Hydrocyanic acidHydrocyanic acidAcetophenone, formic acid

SOURCE: Duke, J. A,, “Phytotoxin Tables,” CRS Critical Rev/ews in Toxicology 5(3): 189-237, 1977,

206 . Plants: The Potent/a/s for Extracting Protein, Medicines, and Other Useful Chemicals—Workshop Proceedings

Figure 8.—Sample Ethnomed Printout

Ose

AIA L AR I AMA L A R J AMA L A R 1 AMA L A R 1 Ah~A L A R ] AMA L A R 1 AhlA L A R 1 A?; L L A R 1 AMA L A R ! ANA L A R 1 AMA L A R 1 AIII A L L f{ i AMA L}, R I AhlA L“L R I Ahl~ L L R i AMA L A R : Ah!A L A R 1 AMALARIAMA L A R 1 At.!A L A R I“A!,lA L A R 1AMA L A R 1 AhiA L AR 1 Ah:A L A R 1 AhlA L A R I AMA L A R I At.l A L A R : AMSLA171 AMA L A R I AhtA L A R 1 AhlA L A R I AMA L A R !,AhlA L A R ;.&MA t. A R 1;AMA LA R I*A 4

hlA L A R I A ●

LIA L A R I A ●hlA L A R I A “MA L A R I A*hlA L A R I A ●

MA L A R 1 A ~MA L A R 1 A ‘!,1 A L A R i /. *MA L A R 1 A ●

MA L A R 1 A ●

t,l L L A R I A ●

hlA L A R I A ●

l,i A L A R 1 A “hlA L A R I A ●

hlA L AR I A ●

MA L fl R 1 A“ *MA I A H I A* ●

SOURCE: Duke, J. A.,

T RACHE LOS PERMUhl LUC I DUMT IT I CH1 L I A HAVAIJENSI ST R I CHOSANTHES CUCUhlER 1 NAT R I L ISA OOOR& T I SS 1 MAT RL)P 1 L) I A CUCIIR L 1610 I oEST U RNE !?A D I F C d$. LURAR I J L2GOPCIQ101 CESu~ Lf? 1 A p RLJN E L L A E F fJL I AURERA BACC I FERAVERBA3CUM THAPSU~k“E REErJA CAROL I NAVER2ENA L 1 TORAL 1 SVE R@E’iA OFF 1 C I NA L I SVEFi BENA OFF IC INAL I SVERNON I A C I tlE REAvETIVERIA Z! ZANIOIDESVIBURNUM OBOL’ATUMV I BURNUS NUDUMVI CIA HIRSUTAv INCETOX ICU:~: AT RATUMV I SCUhl ALBUMV I T E X NEGUN50VITEX PEDUNCULARISXANTHIUhl SPINOSUMXANTHIUM SF’l NO SUMXANTHIUM SP1)JOSUMXANTHIUht SPltJOSUF~lXANIHIUhl ST RU:~:AR1(JhlXANTHIUM ST RUftlLRIUftlXANTHIUM ST RUMARIUMZANTHOXYLUM PI PER1 TUMZING I BER M1OGAZI//GIBER OF FICINALEZING IBER OF FICINALEAND IRA IN ERhl ISBRUCEA JAVANICABuPLEURUM CHINEN5EBUPLEURUM FALCATU!.1CINCHONA OF FICINALISDICHROA FE8RI FUGADICHROA FE BRI FUGAEuca lyp tus SPLECf/OTIS r/ EPETAEf CLIALEONOTIS NE PET AEf OLIAPC) PULUs ALi3ASALIX BABY LC)l~ICASALIX FRAGILISTALi ARIX Cli IIJt N>i5TINOSPORA COft CIFO1. IATR!CLISIA GE LLETilC I NC MONA LEDCE:4!A14:WI ON A Qf F i C 1 )Jit !. I S

CMWON

NCNCY I LA NKABAG INCNCr~cNCNCNCrdcNcNcL U N G YA TS’AONCNCNCricNCCH’ IAO YAOPA1 W E !NCtJcNCNCNCp 1 T RAKC LOT WE E DHSI E R HNCNC

S H U CHIAOJANG HONCNCNCNCNCNc

NCEUCA L 1 PTONcricHURAL DAK!NCN:NC

BAI (OT 07

COUNT Ry

I ND1 AGUATEMALATURK EYusE L SEWHE R EME X 1 COI r/D I A ( AYdRVED I C)E L SEWHE REMEXICOUS ( CO LON I A L )hlE X I COhlE X 1 COCHINAhlE x I COE L SEWHE REINDIA ( SANTA L, )E L SE WHEk EusCH 1 NACH 1 NA

E L SEWHE REcH 1 NAE L SEWHE R EE L SEWH E REINDIATURKEYusCH 1 NAE L SEWHE REE L SEWH E R EcH I NACH 1 NAT R I N 10AOTRINIDADMEXICOCH 1 NACH 1 NAE L SEWH E REE L SEWHE R ECHINAcH I f/AHA J T IE L SE\fi-+ E R ET K J iq 1 L~A D! !7 AQI z L()E L SEWH E REE L LE ;,’1 t S R :E L SEkHE R EZA 1 REMEXICOh~sx I co

SOURCE.

WO I .10.STAND LEY. ST EYE RMARKST E I NMETZKROCHtJALWC) I .10ST ANDLEYh’o I .10Wo I .10ST AND L EY

KROCHMA LAL T SCHULA L T SCHULELI SShlA R T I N EZW() I .10EB24: 244h’o I .10KROCHMALB LISSB LISSh’O I . SYRIAHUNANWo I .10wO I . SYRIAWC) I .11ST E I NhlETzUPHOFBLISSWO I . SYRIAW() 1.11BL Is sBL 1 SSWONGEB30: 1 1 4MARTINEZ .NAS

L1KEYSWO I .2NASKEYSL 10G I EREB30: 136v$or4GAL - RAW IA L - RAW]

WC) I . SY R I Ai:E Y s

w I .10UPHOFhlART I NEZhlART I NEZ

and Waln, K. K., “Madlclnal Plants of the World,” computer Index with more than 85,000 entries, 3 VOIS., 1981.

The USDA Economy Botany Laboratory’s Data Base on Minor Economic Plant Species • 207

u~c

I tt’L L C T I C I DE

J NS EC T I C I DEI N S E C T I C 10E ( V E T JINS ECT I C I DE ( VET )I IJS E C T 1 C I DE*I N S E C T I C I DE ●

] NS EcT ] c ] DE ,

1 )J S E C T I C 1 DE*INSECTICIDE*INSECTIC1OE4INSECTICIDE*INSECTICIDE*INSECTICIDE*INSECTICIDE*INSECTICIDE?INSECTICIDE’I N S E C T I C I D EINSECTICIDE*IN15 CTICIOE*INSECTICIDE’ItJSECTICIDEvINSECTICIDE”I N S E C T I C I D EIN5ECTICIDETINSECTICIDE*INSECTICIDL’Ih’SECTlCIDE4INSECTICIDE*INSECTICIDE?INSECTIC1OE*INSECTIC1DE4INSECTICIDE*I N S E C T I C I D E ’I N S E C T I C I D E ”I N S E C T I C I D E *I N S E C T I C I D EI N S E C T I C I D E *I N S E C T I C I D E ”I N S E C T I C I D E *I N S E C T I C I D E *I N S E C T I C I D E *lt/SECTICIDE*J:,:::T :c!~~ ~ *

I N S E C T I C I D E * *INSECTICICE**ItlSECTICIDE**I}JSECTICIDE”*

I N S E C T I C I D E ’ *INSECTICIDE+*INSECTICIDE+*I N S E C T I C I D E * *INSECTIfUGE*

Figure 9.–Sample of insecticide Subset of ETHNOMED

PCANT

ZANIHOXYLUM ARMA7UMZAtJIHOXYLUM NITIDUMDELPHIhJIUhl f3RUNONlANUhIGARUENIA LUCIOAACORUS CALAfitUSADHATODA VASICAAf4t!L’NA CHERIhlOLACII:CHONA OFFICINALISECLIPTA ALBA~ALI”HILIIA GLA~CA

GyHOcAROIA C)I)!)RATA

ilAL’L’EA AR:LRI CANANERIUhl ItJDICU&’1OCIL”UM F3ASILICUhlOCI;7JM SANCTUMPACliYRR:{IZUS EROSUSPIIELIGDENDRON Ah!URENSEPICRAShlA E X C E L S APl~ll’lNELLA AF/ISUfi]

PISCIL)IA PISCIPUIAPSEUOOTSUGA MENZIESIICUASslA AIJAf?ARYANIL SPECIOSAS A L V I A CFFICINALISSAIJSSUREA LAPPA

SOFJIORA TOLIENTOSASPHAERANTHUS AFRICANUSSPILANTHES ACMELLASPII.ANTHF.S OLERACEAT~G[TES P A T u L A

TEFI{ROS!A BRACTEOLATATEPtli?OSJA CANDIDATEPHROSIA NOCTJFLORATEF}IROSIA PROCUhlnfNSTEPtlROSi& VOGELIITRACHYSPEPMUhl ALffllITEIANTHELIA PORTULAcASTRUMTRILHODESMA ZEYLANJCUhlVERATRUtd VIRIDEZ~JJIHOxYLUM OXYPHYLLUhID~P1/IS ELL!pT]CA

DENR!s FERRuGINEA

DERfiIS MALAC’CENSISGtinRIS RGUUSTAEllcllRF5TA HoRSFIELDIIhUSA CREPITANSl,lLt,f.’EA Af,:ERIc ANAhlELIA T(X)SENL)ANSpE~GULA ARvENSISCA~ApA GUIANENSIS

c~NC:

NCNCNCNCNCCHERIMOYANCNCNCNCNCMAMEYNCNCNCNCYAMBEANNCNCNCNCNCNCNCNCNCNCNCNCNCNCNcN~NCNCNCNCNCNCNCNcNcNCNCNCNCNcNCNCNCNC

MWTRY

ELSEWHEREELSEWHEREELSEWHEREELSEWHEREELSEWHEREINDIALAELSEWHEREELSEWHERENLINDIAELSEWHERELATRINIDADINDIAELSEWHEREELSEWHERELAELSEWHEREELSEWHEREELSEWHEREELSEWHEREELSEWHEREELSEWHEREELSEWHEREELSEWHERECHINAELSEWHEREELSEWHEREELSEWHEREELSEWHEREELSEWHEREINDIAINDIAItJDIAINDJAINDIAELSEWHEREELSEWHEREELSEWHEREu sELSEWHEREIF{DIAINDIAELSEWHEREELSEWHEREIND!AELSEWHEREELSEWHERECHINAELSEWHEREELSEWHERE

Wunct

w~;;1

UPti&FUPHOFWol,tWOI.SYRIAI.EWISWOJ.2NASLEWISWO1.4E1330: 1 3 2LEWISWONGWO1.7WO1.SYRIAWO1.-7LEWISNASWO1.8WO1.SYRIAWO1.8WO].8WOI.8EB26: 2 3 3WOI.SYRIANASW’01.9Wol.loWol. 10WO1.1OWol.loWO1,1OWol.loWol,loWol.loWol.loWOI.SYRIAWol.loWol.loWol.loWol. 1 I‘h’ol ,3WO1.3WO103WO1.3%X)1.3WOI.5WOI.6LlWol.SYRIAES30: 127

SOURCE: Duke,J, A.and Waln, K.KV “Medicinal Plants of the Worfd;’ computer Index wlthmorathsn 85,000 entrles,3vols. 1981.

208 ● Plants: The Potent/a/s for Extracting Protein, Medicines, and Other Useful Chemicals—Workshop Proceedings

Figure 10.—Pittosporum resiniferum

SOURCE: @Peggy Duke,

logical parameters, germination requirements,nutrition values, cultural requirements, yields,wood characteristics, use, and plant pathology. Asample of the Agroforestry File is given in figure11. Perhaps the greatest impact of the prototypewas to show that almost no data were available onmost nonconventional economic plants. The Agro-forestry File is most applicable to Third Worldcountries.

Pest File: This prototype has only about 2,500 en-tries. It lists the scientific name of the host plant,the plant part affected by the disease or the insect,and the name and type of pest. The scientific nameenables this file to communicate with any other file,such as the Agroforestry File (fig. 11).

Our ecosystematic file has helped locate herbs im-portant to nematode taxonomy. Nematodes should

be included in any pest prototype, Several yearsago, Russian workers reported a most unusual nem-atode from a limited area of Russia on Mentha long-ifolia. Soon afterwards Dr. Morgan Golden founda nematode similar to Meloidoderita kirjunovae, theRussian species, on a polygonum at Beltsville. With-out Russian specimens or a better description ofM. kirjunovae, it was impossible to make a finalidentification of the Beltsville specimen. After test-ing true Mentha longifolia with this Melodidoder-ita specimen, Golden found that his nematode didnot attack M. longifolia, the type host for the Rus-sian nematode. With this information and furthermorphological study, Golden proved that theBeltsville specimen represented an undescribedMeloidoderita species. Without testing with Men-tha, the identification and classification of the Mel-oidoderita would have been much less conclusive.

For years I have campaigned for a program thatwould record the ecological amplitudes of pests anddiseases as we have done with economic plants andweeds, Knowledge of the ecological amplitudes ofcrops and their pests could launch a new phase inbiological control of pests’ “biological evasion” (4).Where the host tolerates more cold than the pests,planting in the colder area might be advantageous.For example, in Chowan County, N. C., near thenorthern limits of the cotton plant and the bollweevil, the cotton grows well but the weevil doesnot. This lack of crop and pest overlap may be usedto good advantage by the USDA (2).

Intercropping: Because of our involvement withthe Agroforestry project, we had a greater interestin intercropping than most conventional farmingunits in the USDA. My colleague at USDA, Dr.Atchley, setup a prototype Intercropping file. Nowon tape but not on-line, it lists major and minor cropcombinations, all species in pasture mixes, yielddata, yield differentials, cultural variables, etc.Using the scientific names to link this and otherfiles, one could find out which crops have beentried around the world as intercrops. In denselypopulated Third World areas, intercropping clear-ly promises more quality, quantity, and/or varietyof crops per hectare than monocropping.

Limitations

In intermediate ecotypes, the effects of factorssuch as slope, soil porosity, soil type, vegetationcover, cultural conditions, insolation, prevailingwinds, etc. on plant characteristics may be signifi-cant. Few data are available and we have enteredsome of these variables for only a few places. Thisis a major limitation of our program.

PLNA PLCO AUTHOR

E U C A L Y P T U S CAMALDULENSIS 453046001 SCti LECHT.EuCALYPTUS CITn IODORA 4 5 3 0 4 6 0 0 3 H O O K .EUCALYPTUS GLOOULUS 4 5 3 0 4 6 0 0 4 LABILL.

E u c a l y p t u s GLOBULUS 4 5 3 0 4 6 0 0 4 I.ABILL.EUCALYPTUS GLOOULUS 4 5 3 0 4 6 0 0 4 LABILL.EUCALYPTUS GLOEIULUS 45304GOo4 LABILL.EUCALYPTUS GLCJOULUS 4 5 3 0 4 6 0 0 4 LAUILL.EUCALYPTUS GLOBULUS 4 5 3 0 4 6 0 0 4 LABILI.E U C A L Y P T U S GOMpHOCEPHALA 453046005 OC.EuCALYPTUS GRAIJDIS 4 5 3 0 4 6 0 0 2EUCALYPTUS GRANDIS 4 5 3 0 4 6 0 0 2EUCALYPTUS MARGINATA 4~30460to !jhl.EUCALYPTUS MARGINATA 4 5 3 0 4 G O 1 O Sh!.EUCALYPTUS MARGINATA 4 5 3 0 4 6 L I 1 O Shl.EuCALYPTUS hllCRCTHECA 4 5 3 0 4 6 0 0 6 F.MUELL.E u c a l y p t u s O C C I D E N T A L S 45304bO07 ENOL.EUCALYPTUS SP. 453046GO0EUCALYPTUS TERETICORNIS 4 5 3 0 4 6 0 0 6 SM.

Figure 11 .—Agroforestry Pest FileI’IANIS TIIAI Ali[ I’(JI11411 A I fitrt. :[)llllc[~

COMPUTCR12ED BY Tl{[ IGLMIOI.lIC UOTANY LAU(INAIOIIYALAN A, ATCHL[Y AfiU C~lC S . hlATtil:

GLEDITSIA TRIACANTHOSGLIRICIDIA SEPIUhlGtJELINA ARBOREAGREVILLEA ROBUSTAGUAZUMA ULh41FOL1AHALOXYLON PERSICUMINGA DOURGON11tJGA S P .INGA URAGUENSISltJGA jEIIALESpEOEZd BICOLORLESPEOEZ2 CAPITATALESPEOEZ4 CUNEATALESPLDEZA CYRTOBOTRYALESPEOEZA HIRTA

LESpEDEZA HOMOL08ALESpEDEz4 PILoSALESpEOEZA PROCUtJBENSLESPE13EZ4 REpENSLESPCOEZA SP.LESpEDEZA STIPULACEALESPEDEZA STRIATALEUCAENA LEUCOCEPHALALEUCAENA LEUCOCEPHALALKUC&ENA LEUCOCEPHALALEUCf.ENA LEUCOCEPHALALEUCAENA LEUCOCEPHALALEUCAENA LEUCOCEPHALALIELIA AZEDARACHt.l:L”OSA SCABRELLLL:u,.TIIIGIA CALAE!URAPI{YLLAIJTHUS EIJULICAPITtlLCILIODILJf.1 OULCEPITtlEcELLOOIUf.1 OULCEpIT}iLcELloO1uLI GuLcE

SOURCE: Econofnlc Botany Laboratory.

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210 ● Plants: The Potentials for Extracting Protein, Medicines, and Other Useful Chemicals—Workshop Proceedings

We need to get soil taxonomic units from a uni-fied soil classification system for all 20,000 localesfor which we have climatic data. This would re-quire a major cooperative venture. Much more ofthe world is mapped in the FAO system than in theUSDA Soil Conservation Service’s Soil Taxonomy.The Benchmark program is using the USDA ratherthan the FAO system for site management.

There is a tendency of some soil scientists to as-sert that soil is THE determinant in the distribu-tion and yield of economic plants, of some clima-tologists to believe the climate is the determinant,and of some plant ecologists to believe the vegeta-tion type is the determinant. I suspect that all plantdistributions are determined by interaction of allthree and other factors as well, Unfortunately, thecomputer cannot identify the most important fac-tors affecting a given species. For some species,vegetation will be the most definitive determinant;for others, soil; for others, climate. We need a ma-jor program to collate the FAO and/or USDA soilunits with the 20,000 climatic data sites, soil pH,weeds, crops, yields, diseases, insect pests, nativeperennials, etc. This should be done for a sufficient-ly large number of the 20,000 sites to develop eco-logical (including both climatological and pedolog-ical data) amplitudes and means and determine op-timal conditions for all the economic species of theworld and their pests and pathogens. This system,which could be called the International PlantUtilization Data Base (IPUD), would answer a mul-titide of questions and avoid many costly problems.

For example, with this one-time multimillion dol-lar project, one could prevent many multimilliondollar mistakes made in introducing the wrong spe-cies in developing countries. It could help develop-ing countries develop import substitution programswhich might save them million of dollars. Thismight make the country more self-sufficient anddecrease its need for transporting goods.

The perennials growing in remote areas can helpone assess the plants best grown there. The IPUDcould help one map the areas in a country wherea plant introduction is most likely and least likelyto succeed. Ancillary to this should be the develop-ment of an economic data base (such as is hintedat in fig. 12), which includes transportation costs,shelf life, world demand, trends in production, andcurrent price of a species, Crops that make the mostsense economically then could be chosen from themany crops ecologically adapted to the remote area.All should be tried experimentally before plantedon a large scale. Experimental data resulting fromtrials would be used to select the right species for

that particular area and to augment and refine thedata base.

We have developed several prototype files thatcould attack big problems systematically. Current-ly these files are undersupported; we have not yetconvinced international authorities of the value ofan International Plant Utilization Data Base. Sucha data base could reduce international agriculturaltrade while improving internal trade deficits ac-cordingly. It could reduce the petroleum used ininternational transport of agricultural goods. TheIPUD could select species best adapted to a givenclimate for whole-plant utilization schemes inwhich food, oilseeds, leaf-proteins, chemurgics,drugs, etc. would be the main products and biomasswould be an energy-producing or commercial fiberbyproduct. Greater plant use becomes more impor-tant as petroleum supplies become more scarce andexpensive.

Implications

Without funding, our data bases now have a lifeexpectancy of no more than 3 years. The cost ofmaintaining our files online is more than $10,000a year, even before any programs are run on thedata. Are they worth the cost? Who can use them?The data bases’ contribution to the quest for sor-ghum tolerant of high alkali soils, a multimilliondollar problem, already has been cited. Similarsearches for germ plasm suitable to marginal envi-ronments might be made for any of the hundredsof economic species and thousands of medicinalspecies. USDA is a constant user; daily it consultsthe hard copy generated by the EBL data base toanswer questions on agronomy, agroforestry, cli-mate, ecology, ethnomedicine, nutrition, pathology,and utilization.

Many other agencies have benefitted from thefiles and could reduce future costs by consultingthem,

AgencyAID

APHIS

CIA

Some examples are given below.

Questions We Can Help AnswerWhat crops are best adapted to Lesotho?What trees can you recommend for reforest-ation in Haiti?USDA, in collaboration with NAS and NIF-TAL, is setting up some provenance trials.What species would you suggest?Where in the U.S. is niger seed, an ingre-dient of birdseed, most likely to become aweed?Which of the Chinese medicinal plants-e.g.,honeysuckle, kudzu, and perilla-are mostliable to become weeds around the variousports of entry?Where in South America can Erythroxylumbe grown?

File(s)ECOSYSTEMAT

AGROFOREST

ECOSYSTEMAT

ECOSYSTEMAT

ECOSYSTEMATCHINACLIMATE

CLIMATEECOSYSTEMAT

The USDA Economy Botany Laboratory’s Data Base on Minor Economic Plant Species ● 211

DOD

DOE

FDA

NAS

NIDA

NIFTAL

NIH

NIOSH

OTA

SBA

VITA

Do the trees in the background behind thesemaneuvers indicate that this is a tropical,temperate, or subarctic area?What trichothecene-like compounds are pro-duced by species tolerant of the Laotian cli-mate?If our supplies of atropine were cut off, whatwould be the best places in the United Statesto grow the various species that containatropine?Give us addresses of seed sources from ourallies.Which herbs grown in Teheran are goodsources of vitamin C?List the edible and medical species of Iran.

What phytomass yields have been reportedfrom Panama? What species is the highestbiomass producer reported in your file?What is the standing biomass of the Repub-lic of Panama?List the major crops and energy potential oftheir residue for 66 developing countries.

What species contain safrole?We need 100 lb of comfrey root from dif-ferent latitudes to check out variability incarcinogenicity.What is the nutritional value of the neglectedlegume species of the world?Assuming Bolivia, Colombia, and Peru allphase out coca, where else in Latin Americacan it best be grown? What about Cannabis?Papaver somniferum? What tree crops canbe grown around Chipiriri, Bolivia, wherecocaine production is being discouraged?What herbs can be grown in the Golden Tri-angle where they are phasing out poppy pro-duction?What crops can be grown in the peatswamps of Jamaica, where the ganja is be-ing grown?What legumes, other than caesalpinoidlegumes, can you recommend for tropicalmoist forest, elfin forest, subtropical thornforest, and warm temperate rain forest?

What are the medicinal uses of our 44 ma-jor nitrogen-fixing species?Where can we get several tons of wingedbean?What are the folk anticancer plants ofChina?What carcinogenic compounds are found inthe herbs and spices processed here in theUnited States?List in order of decreasing protein contentthe top 100 leaf-protein producers on a zero-moisture basis.Which would do best in the tobacco belt ofthe Carolinas?Which species could give the most leaf pro-tein per hectare?What commercial crops can you recom-mend for the Lake Miragone region of Haiti?What firewood trees can you recommendfor our site in Ecuador, with a climate iden-tical with that in Quito?What natural pesticide species—such asneem, pyrethrum, and ryania—can you rec-ommend for the San Jose area of Costa Rica?What living-fence post trees produce thebest firewood for Columbia?

CLIMATEECOSYSTEMAT

CLIMATE

PHYTOTOXINECOSYSTEMATCLIMATE

NUTRITIONGEOGRAPHYUTILIZAT

PHYTOMASSYIELDS

ECOSYSTEMATPHYTOMASSYIELDSPHYTOTOXIN

ECOSYSTEMAT

NUTRITION

ECOSYSTEMATCLIMATE

ECOSYSTEMATCLIMATE

ETHNOMED

ECOSYSTEMAT

ETHNOMED

PHYTOTOXIN

NUTRITION

YIELDSCLIMATEECOSYSTMAT

AGROFORESTCLIMATE

ETHNOMEDAGROFORESTCLIMATE

VISTA What esoteric culinary herbs can you recom-mend for the climate in Oregon? ETHNOMED

WHO List contraceptive plants. List molluscicidalplants. ETHNOMED

WRAR What are the medicinal uses of Polygonumalpinum? ETHNOMEDWhat antimalarial species grow in Nigeria? ETHNOMED

AID – Agency for International DevelopmentAPHIS – Animal and Plant Health Inspection ServiceCIA – Central Intelligence AgencyDOD – Department of DefenseDOE – Department of EnergyFDA – Food and Drug AdministrationNAS – National Academy of SciencesN I D A – National Institute of Drug AbuseNIFTAL — Nitrogen Fixation By Tropical Agricultural LegumesNIH – National Institute of HealthNIOSH – National Institute of Occupational Safety and HealthOTA – Office of Technology AssessmentSBA – Small Business AdministrationVITA – Volunteers in Technical AssistanceVISTA — Volunteers in Service to AmericaW H O – World Health OrganizationWRAR – Walter Reed Army Research

There are partial or complete answers to thesequestions in the files of the data base, now off-line.These are samples representing only a few of theinnumerable possible questions, many of whichhave not even been asked, much less answered. Thedevelopment and maintenance of an InternationalPlant Utilization Data Base, an on-line interlockingsystem with agronomic, biochemical, climatologi-cal, ecological, economic, entomological, geograph-ic, pathological, pedological, and use data on thethousands of economic plant species, could help an-swer present and future questions.

Appendix I:Latin American LocaIities

SuitabIe for Date Palm Cultivation

by Alan A. Atchley*

“The date palm must have its feet in water and its headin fire, ” goes an old Arab saying. The familiar image ofa desert oasis supporting a grove of these palms sur-rounded by barren dunes seems to fulfill this proverb,for the trees are “naturally irrigated” by the waters ofthe oasis and their crowns are exposed to some of thehottest weather in the world. But the oasis draws its waterfrom the natural rainfall over a wide expense, and thepalms are not independent of the rainfall component ofthe climate as they would be under artificial irrigation.

Can modern data processing techniques reveal the cli-matic tolerances of this important palm species and sug-gest where it might be introduced successfully? The Eco-nomic Botany Laboratory’s methods were applied to findsites in Latin America where, based on the computerizedinformation in AEGIS (Agricultural, Ecological, Geo-graphic Information System), date palms might grow suc-cessfully. (AEGIS is handled with the SAS programing

● Research Botanist, USDA, ARS, Economic Botany Laboratory, Beltsville, MD20705.

272 ● Plants: The Potentials for Extracting Protein, Medicines, and Other Useful Chemicals—Workshop Proceedings

Figure 12.-Sample Page From Botanical Price Lists

.Uie .s si5erica cil. . . . . . $ 8,5(3 - 9. 00/1!2‘ “ q c 3 i ze---- - - . ● . . . ● . . ● ..*. ● .*$ 1.02 - 1. lg/1~>.: 1>-1 ~sothizcyznaze. . . . $ ? . 25 - 7. gO/~b.Cxczi oil. . ● ● ● ● ., . ● .., ,$ 1.2(I - ~ . OQ/1~All~ . . . . . . . . . . . . . . . . . . . . $ .51 - 1. 50/lb.*Join . . . ● . . . s 5.75 -. . . . . . . . . . . . . 6. 00/lb-AATris. . . . . . . . . . ● ●

- ●

. . . * $ - 9. ~0/lbk; tkcle . . . . . . . ● . . . ● ● . . ● $ 2. 50/15.Ac~eli2a rooc oil. ., ... .$ 80~ . ()()/ lb$zis e oil . . . . . . . . . . . . . . . $ 11 ● 5 0 : 13.09/15.+-~c= ~eeA Q 1. <Jo -k. . . ● . . . ● . . . . . ● 7 1. 60/lbA“= ricc~ kernel oil. . . . . . $ - 2. 00/lbd- L . -~~ a- 1 c ~ um. . . . . . . . . . . . . . $ .89 - 1.44 /lb

.~-\-z c Zez oil . . - . . . . . . . . . . $ 1:. og - 4 .Z5/lbB Q 10 .75 - 12. 50/lb;.. =~~ ● ● . . . . . . . . ● . ● ● . “ “ ~B:;tb =Y:>* ~“=~. . . ● .... .... $ 2.70 - 3. 00/lbSzL1223nza leaf . . . . . . . . .$ 2 . 4 0 - 2. 45~lb~=n ~ a~~ehj-d e . . . . . ● ● ● ● ● ● “ $ 1.24 - 1. 28/lb-E: f=.>er . . . . . . . . . . . . . . . . . 4. 50/lbC:lzus cil. . . . . . . . . . . . . ; : 55.09/1?sC=p~cr. . . . . ..... .: ..... $ 3.63 - 2. 7!2/ 15C=p5cr oil c 1 ● ~o -. . . . . . . . . . . . . . 2.25 /lbr .s LnL7g2 oil. . . . . . ● . . ● ... $ 22.00 - 23. @/~~Can<elilla wax. , c 1. ?0 -. . . . . . . . . 2. 10/lbCa?sicom oleoxesin.. . . . . $ , 8 . 4 0 - 1 6 . 5 0 / l bCsr==~ay nil. ..$. ... ... ..$ 2 9 . 0 0 - 3 0 . 0 0 / l bCar~-~”a:: seed. . . . . . . . . . . . $ -55 - .69 ~ lb

s 3.00-C=r5a=2n . . . . , . . . . . . . ● ● ● “ . 4. 50/lbc. .-C~.au;a WZX. . . . . . . . . . . . $ ~o l ~ - 2. 05/lbc!-C2 y-~ze. . . . . . .“. . . . . . . . $ - ‘:8.00/lbl-CZrx x-e. . . . . . . . . . . . . . . $ ~ . 5 Q - 9.75 /~bCzsczrz zzgz~d=.. . . . . ... $ 1. 00/lbQsz iz c. . . . . . . . . . . . . . . . . . . .67 - . $ofl~Castor oil. . . . . . ........5 .45 - . 6g/ lbCzztar po=cc. . . . ● ... ... $ - 13~*5n/t~~C2:e:k31. . . . . . . . . ... ... .$ 2.94 - 7. 48/!:il:;CedarlaaS oil. . . . . . . . . ● ● $ logo _ 2. 10/lbCed=m-uod cei l . . . . . . .. ..$ 2.35 -CslerY seed. . . . .

3. Q()/~b. . . . . . . . $ .46 - .47 /lb

Csl~=Y s e e d cil. . . . . . . ..$ 29.50 - 1:5.>5/lbC~.a=zALe flo-wrs. . . . . . . $ 3.35 - ~ . 94/13. .fl.-=J-3-&le C1l. . ● . . . . . . . .“---- $ - 370. 90/lbr.-~-~;;~i~~ Oil. . . . . . . . . $“ . . . . . 11. ()~/1~

Ck.s rq: kernel oil*.*.. ... $ 1.00: ~ ● 4g/llJ

C:nC3=3n. . . . . * . . . . . . . . . . 1 ● 35/lbcti22zan bark oil. . . . . . . :2/,0: ;: : 250. 00/kilcCim2==2n l e a f o i l . . . . . . . $ 2.90 - 3. 00/15c~:r~~ 6. ‘)5 /~~Xz:ural . . . . . . . ● ● $(“’’tr~~~~~a ~8~, ceylo~,.$ 2.ZO - 2.60/lb

-. . T c 3.45 -C-Er2..2l3a oll,dava. . . . . . 4.75/15

CLzr3z51La oil, Chiza. ..$ ?.75/15c~~r~ae~~a~....a .=. . . . . . $ 4.00 : .6.20/lbSOURCE:Chemlcal Marketing Reportec 1992.

4,90 - in.on/1~~l~ronellcl. . . . - . ● . ““ “ “ “+

cloYe leaf oil e 1.95 - 4.00/lb. . . . . . . ● ..V~lOY~ bud Oil. . . . . . . . . . . $ 19.50 - 28.00/lbrlo...es- , , . . . . . . . ● . . ● ● “ “. ● $ 5.00 - 5.lo/lbCoc=inc hj.dro:hlsride.. .$ -900.00/kiloCocillana bark <. . . . . . . . ..> .4@ - ,45/15co?s~:e. . . . . . . . . . . . . . . . . $ -9Q0.fJO/~il~Co=i~~dez oil.. . . . . . . . . . $ 25.00 - 3 7 . 0 0 / l bCcri=.nder szed . . . . . . . . . . $ .34 - .41/lbCCrn Sil... . . . . . . . . . . . . . $ .134- .14/lbCottonseed oil. . . . . . . . . .$- .13/lbCouiirin.. . . . . . . . . . . . . . . $ - 6c~0/~bCube root.. . . . . . . . . . . . . . $ .60/lbCu~ene . . . . . . . ..* “. . , . , ● . .$: .23~/lbCuin see~ . . . . . . . . . . . . . . $ - 1 . 0 3 / l bC;cl:nen aldehyde. . . . . . . $ - 6 . 0 0 / l b>Igzcaxln. . . . . . .. . c 2.60 -

● . . . . . . ● T 3.00/gr2mDill=eed oil.... . . . . . . . . $ 9.00 - 13.75/lbF.phedrine. . . . . . . ... .....$ 1.25/oz-pine?hrfie. ! . . - . . . . . . . .$: .5!?/gzam

c - 4eoQ/15ruczlj,;to~= ● ● .****.. ● .=*7Eucal>-pt.Gs o i l ~ 20Q0 _ 3 . 1 0 / l b. . . . . . . ..,yr-l c 3*9O - 4,0~/~~~ugcno~. . . . . . . . . . . . . . . . . .YFennel ail. . . . . . . . . . . . . . $ - 10.00/lb~~nn~~ s~ed . . . . . . . . . . . . . $ .57 - 1.07/lb

.37/lb~oep.ugreek Seed. ... .....$Carlic Gil. . . . . . . . . . . . . .$: 25.QO/lbCeraniol .. . . . . . . . . . . . . . $ ~O()@ _ 1 2 0 0 ( ) / l bCcranitc o i l . . . . . . . . ....$ 21.50 - 69.75/lbc~ng~r. . . . . . ... .... ....,$ .46 - . .88/lbUlnser cil. . . . . . . . . .....$ 24.!?0 - 40.00/15l-.Ci~-;zr oleorssin.. . . . Q...,* - 22.00/lb~~a;a~=uiz o i l . . . . . -....$ 1.15 -.- 2.Qo/~DGuaiecol. . . . . . . . . . . . . . . . $ - 2060/15Cu=ia:vocd ceil . . . . . . . .. $ - 2.60/lbP,___-,-c- :U=. . . . . . . . # . . . . . . . $ .79 - : ,~r;/~’;uel~o~iop~n, . . . . . . ● . - - ..$ 8 . 2 5 - 9 . 0 0 / l b. .2emlock .011. . . .* .*. .*. .* $ - 8.oQ/lbEenbzne leaves . . . * . * . .O,y .55/151ncsicol... . . . . . . . . . . . . .;: 2~.)Q/k~lo~De~ac root . . . . . .* ..*... $ - ~0.~0/lbJLjo?2a oil. . . . . . . . . . . . . . $ 90.00 -lOC1.00/gal~=ni;er ~erV o~l.......$ 55.oo - 65.@O/lb?kra;-a S:O. . . . . . . . . . . . . . $ 1.75 - 2.On/lbKola Zucs. . . . . . . . . . . . . . . $ ,69 - ,65/lbLaurel Ie=ves. . . . . . . . . ..$ .52 - .85/15Lavantin ceil . . . . . . . . . . . $ 50~5 _ 7Q50/lbLaveadzr flowers . . . . . . . . $ .65 - .75/lb

‘1~av~~~~r flobwr Od ..*P- $ 11.75 - 15.45;lbLemn oil, #.rgcntina. ...$ 6.50 - 7 . 0 0 / 1 5Lezongrzss oil c. . . . . . . ...y g,]j/ki.1~~i~orice :OOS. ... .....O .$ ● 4Q - .g~/llJ

The USDA Economy Botany Laboratory’s Data Base on Minor Economic P/ant Species ● 273

language on the computer facilities of the WashingtonComputer Center.)

First, locations for which date palm has been reportedwere retrieved and their climate parameters analyzed.The result is the range of climates which would besearched for; only 13 locations report date palm at pres-ent and the application of statistical methods is only sug-gestive of the palm’s ecological tolerances and not de-finitive.

The arithmetic means of several climatic parametersfor our small sample of stations suggest that ecologicaloptima for date palm are approximately: average annualprecipitation ca. 1,000 mm, average annual temperatureca. 23 “C. Seasonality of the infrared optimal climate isnot apparent from arithmetic means, but the minimumvalues for monthly rainfall and temperature suggest a sus-tained warm summer (temperature 21°C or higher foreach month) and a coldest month with an averagetemperature not less than 8°C. Precipitation peaks in thespring and autumn and a driest-month average precipita-tion of 4 mm suggests that a dry period is required, andappears to coincide with the temperature minima.

To select candidate climates from our climate filewhich contains data for more than 18,000 meteorologicalstations around the world, several assumptions weremade based on the information above. This illustrateshow AEGIS can be used to approximate the potentialrange of a given crop based on some knowledge of thecrop and within the limits of reliability of the data fromthe file containing known distributions. First, stationswere selected that had an average June temperature fig-ure in excess of 20 “C, a January temperature figure notless than 8°C, a July precipitation figure not less than 6mm, and a continentality (Conrad’s index) between —8and 31 mm (the range found for those stations reportingdate palm), This yielded 862 stations, many in LatinAmerica. As some of these were found to be character-ized by sustained rainfall throughout the year, additionalconstraints were added to improve the seasonality match:either the February or July precipitation was not to ex-ceed 10 mm (for Southern and Northern Hemispheres,respectively), and the annual average precipitation wasnot to exceed 1,500 mm. (The minimum reported for datepalm was 140 mm.) This generated a printout of 125 sta-tions, including the following in Latin America:

Brazil: Araquai. Ecuador: Milagro, San Cristobal, Por-toviejo. Guatemala: Amatitlan, Castaneda, GuatemalaCity. Honduras: Comayagua, Tegucigalpa. Mexico:Abasolo, Acaponeta, Ahome, Alcozauca, El Burro,Calaya, Carbo, Carrillo, Cerritos, Chiautla, Cintalapa, Col-ima, Comonfort, Concordia, Coguimatlan, Cuautla, Cuer-navaca, Dolores Hidalgo, Ejutla, La Esperanza, Etla, Florde Jimulco, Gongorron, Guayamas, Huajuapan, Ixmiquil-pan, Jonacatepec, Lagos, Lerdo, Manual Doblado, Mez-cala Isla, Miahuatlan, Monte Puerta, Moroleon, Moto-zintla, Nazas, Piaxtla, La Providencia, Puente de Ixtla,Rioverde, El Rodeo, San Bias, S. J. de Guadelupe, SanMarcos, San Carlode de Yautepec, San Miguel Allende,Santiago Vane, Sierra Mojada, Tamazula Giordano, Tax-CO, Tehuacan, Tlacolula, Toliman, Topolo Bampo, Tuxt-

la Gutierrez, Union de Tula, Ures, Zimapan, Zinapecu-aro, Ameca, Guadalajara, Leon, Oaxaca, Penjamo, Sal-vatierra, Zamora. Venezuela: Barquisimeto, Guigue,Valencia.

If more time were available for this quest, the selec-tion process could be refined by entry of more data onthe actual occurrence of date palms correlated withweather stations, and particularly on the yield of thepalms at such places. At present AEGIS has no yield dataat all on date palms, though published reports surely ex-ist. Such data would help decide whether the palmswould do well, rather than merely survive, at the stationsindicated above. Other refinements, such as better atten-tion to the reversal of seasonality in the southern hemi-sphere, could improve this kind of approximating retriev-al and, in the present case, probably increase the listingfor Brazil.

Appendix II:Rating American Localities

Suitable for Date Palm

by James Alan Duke

Rather tardily, I am responding to a request to identi-fy localities in Latin America best adapted to the datepalm. I am passing on some of the data to demonstratemethodology (with a copy to OTA, which requested thatI prepare a paper on applications and uniqueness of ourdata base here in EBL).

First the caveats! I have intentionally devoted less than4 hours to this question. I have asked Dr. A.A. Atchleyof this lab to devote a similar amount of time but to usehis own devices. I hope that some of our conclusions willbe the same! One should devote 4 months, not 4 hours,to a feasibility study such as this. What we will both sendyou are approaches at climatic analogues, very crudeones at that,

Once analogous climatic stations are uncovered, soils,availability of water for irrigation, peculiar atmosphericconditions (such as the fogs in the Chilean-Peruvian des-ert), and many other factors must be assessed as well.

Here is a thumbnail sketch of some of the date palm’speculiar ecological “whims”:

It is very tolerant of alkali soils and can grow in soils con-taining 3 to 4 percent white alkali, but to bear well, thepalm’s roots must be in a stratum with less than 1 percentof alkali silts.

Grown ideally where the permanent water table is within9 to 16 of the soil surface. At least 8 to 9 acre feet of ir-rigation water per year is necessary for good productionon bearing palms.

Daytime temperatures of 50° C are tolerated. For properripening of fruit, the mean temperature between the periodof flowering and ripening should be above 21.20 C risingto 26,70 C for at least a month.

Finest date varieties require 3,300 units of heat, a unit be-ing defined as a degree above a daily mean of 64.40 F be-tween the flowering, fruit development, and ripening peri-ods.

214 . Plants: The Potent/a/s for Extracting Protein, Medicines, and Other Useful Chemicals—Workshop Proceedings

Israelis blame some of their problems on inability tocontrol flowering time (it takes 6 months for fruits toripen). There can be some control by withholding irriga-tion during fall and winter. There must be no rain dur-ing flowering time. An average temperature of 30° C isgood for proper ripening. Winter temperatures below–80 C (ca 170 F) are harmful.

Any good soil that is not too heavy will do. In cleansoil, a little hard water is acceptable; but a combinationof alkaline soil and salty water is too much. Dates do welleven where there is a crust of salt on the soil surface.If, in the top 2 to 2.5 m, there is a 30 cm layer or stratawith 1 percent alkalinity, the date roots will “find” thestrata and flare out there.

Indio, Calif., has long been a center for study of Amer-ican plant introductions of the date palms. The Indio sta-tion is rumored to be in jeopardy, considered by someas excess government property, at least in part. Jim Car-penter (714-347-3414) should be consulted. He is one ofAmerica’s leading experts on date palms. He could prob-ably point out flaws in this 4-hour document. However,we are proud of our ability to identify rough climateanalogues, once the specialists tell us what is required.

The following places are reported to produce good datepalms:

ECOSYSTEMATIC ECOSYSTEMATICPlace Code P l a c e CodeAswan, Egypt . . . . . . . . . 0026 Yuma, Ariz. . . . . . . . . . . . 0122Fayum, Egypt . . . . . . . 0021 Beer Sheba, Israel ... , . . . . 0219Ciza, Egypt . . . . . . . . . . . 0020 Bagdad, Iraq. . . . . . . . . . . ., 0123Thermal, Calif. . . . . . . . . 0123 Basra, Iraq ., , . . . . . . . . . . 0224Mecca, Calif. ., . . ., . . . 0121 Alexandria, Egypt . . . . . . . . 0220Indio, Calif. . . . . . . . . . . 0123 Tempe, Ariz. . . . . . . . . . . . . 0220

The first two digits of the ecosystematic code corre-spond to annual precipitation rounded off to the nearestdecimeter. The second two digits correspond to annualmean temperature rounded off to the nearest 0 C. Month-ly totals should also be consulted in a more refinedfeasibility study,

One can then look for comparable examples in a Tableof Ecosystematic Values for Mexico and see that Baja,California, has several localities with identical ecosys-tematic codes to those for some of the better date pro-ducing localities–e.g., Comondu is analogous to Bagdadand Indio, Magdalena to Yuma, etc. Based on annual cli-

matic averages alone, one might consider Comondu orany other place in Latin America with a ecosystematiccode of 0123 to be a possible target for date palm cultiva-tion. Several places in Peru (e.g., El Alto, Bededero,Campo de Marte, Cayalti, Talera, Trujillo, Zorritos, etc.)have ecosystematic codes similar to some of those listedabove and could be investigated as date palm targets,

This is just a superficial sketch. While I would bet onthe Baja, California, stations, I would be leary of fog inPeru (unless hand pollination were guaranteed) and inall cases I would question the availability of irrigationwater equivalent to 2,300 mm/year.

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6,

7,

8.

RoforoncosBrown, S., and Lugo, A, E., “ The Storage and Pro-duction of Organic Matter in Tropical Forests andTheir Role in the Global Carbon Cycle,” Biotropica14(3); 161-187, 1982.Coulson, J. R., Chief, Beneficial Insect IntroductionLaboratory, USDA (ARS), Beltsville, Md., personalcommunication, 1982.Council of Scientific and Industrial Research (CSIR),The Wealth of India, CSIR, Delhi, India, VOIS 1-11,1948-76,Duke, J. A., “The Guest for Tolerant Germ Plasm,”ch. 1, pp. 1-61, ASA Special Symposium 32 “Crop Tol-erances to Suboptimal Land Conditions, ” AmericanSociety of Agronomy, Madison, Wis., 1978.Duke, J. A., Handbook of Legumes of WorldEconomic Importance (New York: Plenum Press,1981).Duke, J. A,, “The Quest for Iron-Efficient GermPlasm,” J. of Plant Nutr. 5(4-7): 637-638, 1982.Gohl, B., Tropical Feeds, FAO, Animal Productionand Health Series #12, FAO, Rome, 1981.Miller, B, F., “Composition of Cereal Grains and For-ages, ’’” NAS Publication #583, National Academy ofSciences, Washington, D. C., 1958.

9. att, B. K. and A. L. Merrill, “Composition of Foods,”Agriculture Handbook No. 8, USDA, Washington,D. C., 1963.

10. Wernstedt, F. L., World Climatic Data. (Lemont, Pa,:Climatic Data Press, 1972).