Choosing New Crops

R.J. Fletcher1, G.E.A. Ferguson2, G.M Kregor1 and C.H McConnell2.
1 Department of Plant Production,
The University of Queensland Gatton College, Gatton, 4343
2 Department of Management Studies,
The University of Queensland Gatton College, Gatton, 4343

Summary

The process of selecting new crops in which to invest research and development effort and funds has, in the past, been largely subjective or based on a limited number of criteria.

Improved screening and selection procedures will assist in choosing new crops worthy of future development by industry and will reduce the number of expensively funded failures.

The RIRDC/GRDC funded project, UQ33-A, at the University of Queensland Gatton College seeks to develop a comprehensive and objective procedure for selecting new crops suitable for northern Australia. In this paper, we will review some recent developments in new crop selection and present the approaches that are being evaluated. We will also report progress on constructing information systems and a selection procedure and their ultimate extension into a decision support system.

Introduction

A crop is a group of agricultural or horticultural plants cultivated for a purpose, usually with some form of harvest in mind. The most important crops used by man are listed in Table 1, ranked in terms of production. Each of these crops has a combined annual value of more than $US1 billion (Harlan, 1975).

The most important tree crops are highlighted in Table 1 and include citrus (ranked eleventh in production), banana (fifteenth), palm oil (twentieth), coffee (twenty fourth), rubber (twenty sixth) and cocoa (twenty seventh).

It is surprising that man has domesticated and developed so few crops for extensive use. There are at least 3000 potential food plant species available for development and as many as 20,000 plants available for domestication (Jain, 1983).

New crops include those plants which have not yet been domesticated, new species, plants adapted to new climates, cropping systems or areas, and plants giving rise to new products (Figure 1).

Figure 1. The production of a new product from a new crop is the ultimate challenge: the production of new products from established crops or established products from new crops is the more likely scenario in Australia.

New
Cropping system (Production)
Established
Established
New
Crop Product

(Marketing, Processing)

Table 1. The 28 most important crops in the world, ranked in terms of estimated production (Harlan, 1975)
CropProduction
(M metric tons)
Crop Production
(M metric tons)
1Wheat343 15Bananas28
2Rice308 16Tomatoes28
3Maize308 17Millets22
4Potatoes306 18Cottonseed22
5Barley152 19Sesame21
6Manioc (cassava)92 20Palm oil20
7Oats54 21Peanuts18
8Sorghum49 22Sweet potatoes & yam 15
9Soybean49 23Cotton (fibre)11
10Cane sugar41 24Coffee4.9
11Citrus37 25Tobacco4.5
12Beet sugar31 26Rubber3.5
13Beans,peas,chickpeas 3127Cocoa 1.5
14Rye31 28Tea1.3

The Australian Institute of Agricultural Science National Conference in 1993, entitled 'Making It Happen' was told, by representatives from their Queensland Zone, that 'there has been a preference in Australia to focus on established crops. There needs to be much greater emphasis on new crops and new products, which will help to reduce the impact of global crop wars...' (AIAS, 1993).

Fletcher (1993) produced a listing of over 4500 potential new crops for Australia, from descriptions of plant species which have been found to be useful somewhere in the world. Among this listing, there were over 1600 tree crops, including 1451 fruit crops, 160 nut crops and 44 windbreak crops (Table 2). The fruit and nut crops from this listing are included in Appendix 1.

This listing demonstrated the scale of the problem of selecting potential new crops, such as new tree and nut crops, in which to invest research and development effort. The aim of this paper is to address the most appropriate method(s) for tackling this problem.

Table 2. Summary of the different crop types included in the Listing of Potential New Crops (Fletcher, 1993)
Crop types
Number
Crop types
Number
1Beverage
333
15Oil
216
2Cereal
72
16Pesticide
32
3Drug
39
17Pseudocereal
15
4Dye
27
18Resin
32
5Elastomer
47
19Root
496
6Forage grass
53
20Spice
367
7Fibre
69
21Starch
270
8Forage legume
62
22Soil stabiliser
19
9Fruit
1451
23Sugar
50
10Green material
22
24Sweetener
3
11Gum
61
25Tannin
31
12Legume
88
26Vegetable
817
13Medicinal
195
27Wax
10
14Nut
160
28Windbreak
44
TOTAL(some crops were classified as having multiple uses) 5081

Recent history of new crop development

Wood, Chudleigh and Bond (1994) investigated the factors determining success or failure for 35 new Australian crop industries established since 1950 (Table 3). Among their general conclusions, they found that:

Table 3. New crop industries established in Australia since 1950, grouped according to their estimated annual value, in $AUD million (Wood, Chudleigh and Bond, 1994)
High$M Medium$MLow $MZero $M
Cotton806Sunflower 48Oilseed poppy10.0 Rice (WA)0
Lupin160Broccoli 37Pyrethrum8.0 Arrowroot0
Mushroom99Soybean 35Safflower6.4 Cassava0
Melon 35Rice (Qld)5.6
Canola 27Blueberry4.5
Triticale 27Ginger4.5
Avocado 23Mungbean4.4
Macadamia 22Navy bean4.0
Chickpea 21Duboisia3.5
Mango 16Pecan2.2
Kiwifruit 15Persimmon2.0
Almond 15Eucalyptus oil2.0
Garlic1.5
Tea1.3
Alfalfa sprout1.0
Aloe vera0.4
Jojoba0.1

Figure 2. Representation of the change in gross value of a new crop industry (derived from information included in Wood, Chudleigh and Bond, 1994 and other sources).

**scan**

The factors having the greatest impact on the development of new crop industries in Australia were the availability of research and development funds in Australia, and the marketability of the crop product, especially in terms of satisfactory quality (Table 4).

The impact of government support in new crop industries was significant, through the provision of research and development funding, especially in the area of plant improvement.

The growth characteristics of many of the new crop industries, in terms of gross value, could be approximated by the relationship in Figure 2. Growth was rapid at first (stage A), after which a plateau was reached (B). After this time, the performance of the new crop industry was likely to be determined by the research and development conducted (Table 4); the outcome could have been positive (D) or negative (C). At stage E, the crop industry could probably be referred to as being established.

The growth characteristics of the macadamia, mango and almond industries indicated that these industries had progressed beyond the plateau stage (to stage D), whereas the avocado industry appeared to be at the plateau stage (Wood, Chudleigh and Bond, 1994).

Table 4. Summary of the more significant success factors identified among the 35 new crop industries developed in Australia since 1950 (Wood, Chudleigh and Bond, 1994).
Success factors:
Number of new crop industries affected (/35)
Positive Production Factors:
Research and development conducted in Australia Plant improvement (20); Cultural practices (15); Pests and diseases (6); Mechanisation(5)]
32
Availability of overseas technology
12
Investment incentives
11
Dissatisfaction with alternatives
6
Negative Production Factors:
Pests and diseases (often solved)
12
Reduced productivity
10
Scarce labour
7
Marketing Factors:
Demand (positive)
17
(negative)
8
Market development(positive)
13
(negative)
12
Quality(positive)
13
(negative)
19
Competition(negative)
17
Processing Factors:
Facilities established
7
Overseas technology available
6
Government Factors (apart from research funding)
Regulation of this or some other industry
12
Assistance
7

The current situation in new crop research and development in Australia

A survey was conducted among the 500 Australian readers of the Australian New Crops Newsletter in July 1994. Among the 400 respondents, 70 had an interest in new fruit crops, 56 were interested in new nut crops, and 45 in windbreak crops (Fletcher, 1995a).

Specific crops identified by these readers as the subjects of current or past investigations are listed in Table 5.

Table 5. Tree and nut crop species being researched and species indicated as having been the subject of past experiences by the readers of the Australian New Crops Newsletter (Fletcher, 1995a)
Species being researched:
Anacardium spp. (Cashew)Macadamia spp.
Annona cherimola (cherimoya)Mangifera indica (mango)
Athertonia diversifoliaMusa spp. (banana)
Averrhoa carambola (starfruit)Myrciaria cauliflora (jaboticaba)
Carica spp. (Papaya)Nephelium lappaceum (rambutan)
Ceratonia siliqua (carob)Olea europaea (olive)
Cocos nucifera (coconut)Prunus mume (Japanese apricot)
Diospyros spp. (Persimmon)Psidium guajava (guava)
Euphoria longana (longan)Santalum acuminatum (sweet quandong)
Ficus spp. (Fig)Santalum spp. (sandalwood)
Flacourtia inermisSclerocarya caffra
Garcinia mangostana (mangosteen) Syzygium spp.
Inocarpus tugiterTerminalia karnbachii
Litchi chinensis (lychee)
Species with which some experience has been gained:
Albizia spp.Indigofera spp.
Castanospermum australe (blackbean) Luffa spp.
Eriobotrya japonica (loquat)Pyrus spp. (nashi)
Flindersia grayliana (Queensland maple) Ziziphus jujuba (common jujube)

Techniques and approaches in new crop selection

The development of new crops does not only involve new species producing new products (Figure 1). Such a combination is the ultimate challenge. A new crop may have some advantage over established crops in producing a product already well established in the marketplace. Conversely, an old crop producing a new product or being introduced into a new geographical area can be considered as a new crop, having the difficulties associated with new crop development.

In developing an approach to selecting new crops for research and development, four decisions need to be made:

Each of these matters will be discussed briefly to indicate the reasoning behing the decisions which have been reached.

The total information approach is an attempt to identify all criteria likely to be relevant to the selection of new crops and attempts to provide information for each of the criteria. Table 6 describes a potential information structure that may support this process, with the most likely sources for the relevant information.

The disadvantages of the total information approach are that the numbers of relevant criteria will be substantial and reliable information for new crops is not often available. Reliability may have significant implications in a process such as new crop selection: small differences in the initial conditions of some variables may provoke large differences in the final outcomes (Hall, 1992; Sigmund, 1993). The advantage of the total information approach is that the generic set of criteria created requires that many of the potentially important factors will need to be considered before any research and development commences and are thus not likely to be overlooked.

The major factor approach has the advantage that it will be easier to assemble and carry out. Single factors can sometimes have a major influence on the success of new crops and may warrant analysis as a predictor of future potential among new crops. It is difficult, however, to make such an approach generic. Should the major factor change in its importance, the data and the problem will need to be reassessed.

As an example of the major factor approach, would monitoring of the shelves of US supermarkets give a sufficient indication, by itself, of the future trends in the marketability of new food innovations? Although such an approach may have some usefulness in certain situations, it does not appear to warrant general application.

Table 6. List of criteria for the selection of new crops and the likely sources of the relevant information for use in making these decisions.
Information category (criterion) Information source / format
1 (Ethno)botanical/geographical
1.1 Image of plant or parts
1.2.1 FamilySEPASAL,Index Kewensis,NICU,Grays
1.2.2 GenusSEPASAL,Index Kewensis,NICU,Grays
1.2.3 SpeciesSEPASAL,Index Kewensis,NICU,Grays
1.2.4 SynonymsSEPASAL,Index Kewensis,NICU,Grays
1.2.5 Common namesSEPASAL,Index Kewensis,NICU,Grays
1.3 Life form, habitSEPASAL, Literature
1.4 OntogenySEPASAL, NICU
1.4.1 Physiology/genetics of ontogeny Literature
1.5 Geographical originSEPASAL, Literature
1.5.1 Centres of originSEPASAL, Literature
1.6 Current distributionSEPASAL, Literature
1.7 History of domesticationSEPASAL, TDWG
1.8 UsesSEPASAL
1.8.1 Useful plant partsSEPASAL
1.8.2 Image of useful plant parts
2 Agronomic
2.1 Climate,PLANTGRO, CLIMPROD, ECOCROP,CLIMEX
2.1.1 Matched climate in AustraliaPLANTGRO, CLIMEX
2.2 Landscape linked to regionsSEPASAL
2.2.1 Matched landscape in Australia SEPASAL
2.3 Soil typesFAO, SEPASAL
2.3.1 Matched soil type in Australia FAO
2.4 Areas of cultivation (if any)Literature
2.4.1 World mapGIS
2.4.2 World past areas of cultivation Literature, GIS
2.4.3 World current areas of cultivation Literature, GIS
2.4.4 World potential areas of cultivation GIS
2.4.5 Australian mapGIS
2.4.6 Australian past areas of cultivation GIS
2.4.7 Australian current areas of cultivation GIS
2.4.8 Australian potential areas of cultivation
2.5 Breeding systemGRIN, Literature
2.6 Genetic diversity available
2.6.1 World accessions heldIPGRI
2.6.2 Australian accessions heldGenetic Resource Centres
2.7 Breeding method to be used
2.7.1 Type of commercial cultivar to be used
2.7.2 Selection or crossing
2.7.3 Objectives comprising ideal cultivar
2.7.3.1 Critical objectives
3 Production
3.1 Quantity of information/support available Worldwide Literature
3.1.1 Related information available
3.1.2 AustraliaLiterature, experts
3.1.2.1 Related information available
3.2 PropagationLiterature, Horticulture Section
3.3 PlantingLiterature, AgMech
3.3.1 Preparation of planting site
3.4 Degree of mechanisation possible AgMech
3.4.1 Planting
3.4.2 Maintenance during growth
3.4.3 Harvesting
3.4.4 Post-harvest treatment
3.5 Current/potential yieldsFAO, ABS, PLANTGRO
3.5.1 Generic yield models available e.g. CERES
3.6 HarvestingAgMech
3.6.1 Specialisation of labour required FAO
3.6.2 Seasonality of harvestingFAO
3.7 NutritionHorticultural/Agronomy Sections
3.8 Major pests/diseasesPlant Protection Section
3.8.1 Availability of control measures
3.8.2 Comparative damage
3.9 Pesticide registrationsPESKEM
3.10 Rotations availableLiterature
3.11 Landcare considerationsLiterature, Land Resources Section
4 Production economics
4.1 Competing alternative crops
4.2 Gross margins analysisGreg Ferguson, QDPI
4.3 Crop budgetQDPI software
4.3.1 Inputs
4.3.1.1 Variable
4.3.1.2 Fixed
4.3.1.3 Random
4.3.2 Prices
4.3.3 Land/site preparation
4.3.4 Cultivation
4.3.5 Harvest rate
4.4 Tax incentivesATO, DPIE
5 Industry economics
5.1 Critical mass for infrastructure
5.2 Specialised processing
6 Domestic production
6.1 Areas of productionGIS, ABS
6.1.1 Dispersal/concentration
6.2 VolumesGIS, ABS
6.2.1 By areasGIS
6.2.2 By years
6.3 Characteristics of producers
7 World trade
7.1 FAO statisticsFAO, USDA
7.2 Trade volumeFAO, USDA
7.3 PriceFAO, USDA
7.4 StabilityDerived
7.5 Dominant players/marketsFAO, USDA
7.5.1 Timing of production
8 Australian trade
8.1 Trade statisticsABARE, ABS, AQIS
8.1.1 Customs import/export codesSITC
8.2 Trade volumeABARE, ABS, AQIS
8.3 PriceABARE, ABS, AQIS
8.4 StabilityDerived
8.5 Tariffs and import dutiesACS
8.6 Quarantine considerationsAQIS
8.7 Dominant players/trading system Derived
9 Marketing
9.1 Product categoryACS, ABS
9.2 Potential substitutesABS, experts
9.3 Market characteristicsChai McConnell
9.4 Quality considerationsAQIS, wholesalers, manufacturers
9.5 Public awarenessExperts
9.6 Marketing bodiesChai McConnell
9.7 Registration/recognition barriers AQIS, Customs, AMA
10 Handling
10.1 Technology transferAgMech, FST
10.2 Transport systemAgMech, FST
10.3 Packaging standardsFST
10.3.1 Image of packaging standards
10.4 Shelf lifeHorticulture Section
10.4.1 Wholesale, retailCommercial resellers
10.4.2 Maturity indices, profilingHorticulture Section
10.5 Postharvest technologyHorticulture Section
11 Processing
11.1 Potential products/usesLiterature
11.1.1 Image of products
11.2 Product standardsRelevant Industry bodies
11.3 Specific product charactersFST
11.4 Processing technologyFST
11.4.1 Image of machinery
11.5 Processing infrastructureFST
11.6 Health/hygiene considerationsFST
12 Funding of domestic research
12.1 Current researchSurvey via Newsletter
12.2 Potential funding bodiesExperts, literature
13 General
13.1 Industry champion
13.2 Seminal referencesCDROM abstracts
13.3 World authorities/referencesFAO, Literature
13.4 Australian authorities/references DPIE, CSIRO, survey
13.5 Potential interest groupsSurvey
14 GlossaryANBG

Abbreviations:

ABARE: Australian Bureau of Agricultural Resources and Economics

ABS: Australian Bureau of Statistics

ACS: Australian Customs Service

AgMech: Agricultural Mechanisation Centre, Department of Plant Production, The University of Queensland Gatton College, Gatton.

ANBG: Australian National Botanical Garden

AQIS: Australian Quarantine Inspection Service

AMA: Australian Medical Association

ATO: Australian Taxation Office

CDROM: Compact Disc Read-only Memory

CERES: Software package

CLIMEX: Software package

CLIMPROD: Software package

DPIE: Commonwealth Department of Primary Industries and Energy

CSIRO: Commonwealth Scientific and Industrial Research Organisation

ECOCROP: Database

FAO: Food and Agricultural Organisation of the United Nations

FST: Food science and Technology Department, The University of Queensland Gatton College

GIS: Geographic Information System

Grays: Database

GRIN: Genetic Resource Information Network, National Resources Program, United States Department of Agriculture

IPGRI: International Plant Genetics Resources Institute

NICU: Names in Current Use

PESKEM: Database

QDPI: Queensland Department of Primary Industries

SEPASAL: Survey of Economic Plants of Arid and Semi-arid Lands

SITC: System of International Trade Classifications

TDWG: Taxonomic Databases Working Group

USDA: United States Department of Agriculture

Figure 3. Representation of the need for more attention in the choosing of which potential new crops are investigated.
World-wide Flora
A?
Useful Plants
B?
Promising New Crops
C
Crops Being Researched
D
Established Crops
Proposed
Discards

Identifying a plant as useful indicates that its product has been defined. The Listing of Potential New Crops for Australia (Fletcher, 1993), adopted this approach.

The advantage of the usefulness approach was demonstrated in Figure 1. To consider species that are useful, avoids the problems of establishing a new crop product from a new crop. A defacto product has already been identified in these cases.

Many systems to comprehensively evaluate 'promising' new crops already exist (step C in Figure 3). Such an approach has been used by such organisations as the USDA and the New Zealand and Tasmanian Departments of Primary Industry and Fisheries.

The nature of the process in step B that identified the promising crops to be investigated is not clear. The current project aims to carry out both steps B and C systematically and in one operation.

Due to limitations on research and development resources, selecting one new crop would be advantageous, yet risky. The new crop that is chosen will have to be commercially successful to warrant its choice.

From an economic standpoint, a basket of new crops has many advantages.

An economic rationalist would select new crops worthy of financial support by benefit/cost analysis. Such analyses, as conducted on established crops, would need to be modified before being used for new crops.

An investment that produces a marginal improvement in an established industry, in the short term, will usually be more attractive than the same investment in a new crop industry. This would occur because new crop industries have extra costs associated with establishment of the industry. With a basket of new crops, these costs can be shared. As well, the benefits from new crops will be longer in coming.

Most of the benefits from established crop research flow to the consumer. Increased productivity results in lower product prices in the marketplace and for exported products, these benefits are shared globally.

For new crops, there is more opportunity for the producer, as well as the consumer, to benefit from research and development. With a basket of new crops, these benefits would be spread more widely. There would also be greater potential to retain, within the national economy, a larger share of the research benefits from new crops research.

There is also significant risk associated with funding of any new crop research. This risk is likely to be higher, and probably more difficult to estimate, than that associated with established crop research. The risk with new crops has also been publicised through several ill-advised ventures that have given rise to new crop failures in the past.

The higher risk involved with new crop industries is quantified in benefit/cost analyses through discounts applied to benefits. The selection of a basket of new crops would avoid the discounts associated with these higher risks.

Portfolio selection in stock market trading has techniques available to measure and select groups of shares which provide a particular expected return, with a certain level of associated risk. Such methods can be used to select portfolios of new crops on which research and development funds can be spent, with a predetermined level of risk. The method of genetic algorithms has potential for this purpose.

The choice of a selection procedure

Several methods have been investigated in a preliminary fashion to determine which may be most useful in comparing potential new crops and selecting the most suitable for research and development. Currently, genetic algorithms has the most promise and will be investigated further. An example of the use of genetic algorithms to choose new crops worthy of research and development is included below.

Development of information systems

There is a lack of high quality, structured and reliable information available on new crops. This is especially true of commercially relevant information and is a factor preventing the adoption of new cropping options and hence the diversification of Australian agriculture.

A survey of fifteen extension personnel responsible for advising primary producers on new crop choices (Fletcher, 1995b) has identified that the unavailability of useful information is their major difficulty in providing interested producers with advice on alternative cropping options (Table 7).

Industry is understandably reluctant to commit research and development funds to any project for which the outcomes are uncertain. Thus, in any investigation of new crops for commercial adoption, lack of information becomes a de-facto selection criteria itself, prompting the discarding of those potential crops about which little information is readily available. This situation is not desirable.

As long ago as 1957, R.D.Lewis, as the chairman of the US New and Special Crops Task Group, in reporting to the President's Appointed Bipartisan Commission of Increased Industrial Use of Agricultural Products, recognised this. His task group reported that collating and structuring the existing literature was the first requirement for expanded new crops research and was the foundation for any intelligent program of plant evaluation. He advocated the total information approach, but, in the intervening forty years, this has not been undertaken (Jolliff, 1995).

There is, therefore, a need for some form of information system on new crops.

There are two distinct and possibly conflicting requirements for information systems on new crops.

Table 7. The sources for the information on new crops supplied by extension personnel to primary producers (Fletcher, 1995b).
Personally-produced information:
Verbal discussion based on previous experience
Personally-conducted trial work (more limited these days as time available becomes short)
Personal experience generally with crops
Information generated from within the industry-based group or project team
Personally-conducted market research
Use of files collected over time
Information sourced from an expert:
Referral to an industry expert on that crop (if available)
Discussions with other producers who have grown the new crop
Contacts established with leading farmers with experience from other areas
Personal and direct contact with importers and local buyers
Personal and direct contact with overseas grower associations and networks
Contracts for market research
Contracts for whole farm economic analysis
Information sourced from those with more generic knowledge:
Contacts established with those in related industries, innovative producers, others with specific information, researchers from various agencies
Discussion with relevant officers of state departments of agriculture, company representatives, traditional primary producers
Word of mouth
Information from publications:
Specific interest magazines
Relevant state government department of agriculture published research
Locally produced information sheets
State department of agriculture information centres
Articles from the local press and rural newspapers
Local publications; Interstate publications; Books
Scientific literature; journals
General magazines (which can be incomplete in their information)

Construction of a Decision Support System

A decision support system is any resource that we use to assist in making better informed decisions. Computer-based decision support systems provide a means by which we may process large quantities of information and make comparisons between that information, based upon pre-defined rules.

Human experts typically work on a select subset of any given information. The particular subset depends on their area of expertise. As the level of expertise increases, the ability to articulate knowledge and thought processes (that is, to elucidate evaluation techniques) decreases. In other words, several experts can often provide conflicting opinions on a subject and yet be unable to provide justification for their decision beyond invoking "experience".

The main advantage of applying computer technologies to new crop selection is that data may be treated objectively and comprehensively, even if they may vary in quality or completeness.

Improved methodologies and skilful identification of the information will decrease the complexity of the task. Good design is needed to ensure that all vital information is included.

An example of the use of genetic algorithms

The software 'Evolver' (Axcelis Inc., 4668 Eastern Avenue North, Seattle, Washington, USA 98103-6932) has been used for this demonstration. A model comprising a number of useful plant species, a number of criteria and ratings was firstly set up in an Excel database (Table 8).

An estimate for the cost of fixing all limitations for each plant species was derived by multiplying the ratings by the cost and summing (Table 9). The basket of the five most worthy plant species for research and development included species 15, 7, 12, 18 and 4 (Table 10). A range for each cost was then used with the 'Evolver'software to find a basket of five species with the lowest total cost and the basket included the same five species (Table 10).

There are many possible developments for improving this model, including such elements as:

Table 8. The model for choosing new crops worthy of research and development: twenty useful plant species, fifteen criteria and ratings for the limitations of each new crop in terms of each criterion (this is an example including random numbers for the ratings).

20 Useful Plant Species:
1
2
3
4
5
6
7
8
........etc
15 Criteria:
Ratings:
1
-1
0
-1
0
-1
-1
-2
0
........etc
2
-1
-1
0
0
0
0
-1
-1
3
0
0
0
-1
-2
0
-1
0
4
0
-1
-1
-1
0
0
0
0
5
-1
0
0
0
-1
-2
-1
0
6
0
0
0
0
-1
0
0
-1
7
0
-1
-1
0
-1
-1
-1
-1
8
0
-1
0
0
-1
-1
-1
-1
9
-1
-1
-2
-1
-2
0
0
-1
10
-1
0
0
-1
0
-1
0
0
11
0
-2
-1
-1
0
-1
0
0
12
-1
0
0
-1
-1
0
0
-1
13
0
0
-2
0
0
-1
-1
-1
14
-1
-1
0
-1
0
-1
-1
-1
15
-1
0
-1
0
-1
0
0
0

Table 9. Derivation of the total cost (in arbitrary units of value) of rectifying the limitations for each useful plant species in the process of choosing new crops worthy of research and development.
Cost of fixing:
1
2
3
4
5
6
7
8
....... etc
2000
2000
0
2000
0
2000
2000
4000
0
....... etc
2000
2000
2000
0
0
0
0
2000
2000
4000
0
0
0
4000
8000
0
4000
0
4000
0
4000
4000
4000
0
0
0
0
6000
6000
0
0
0
6000
12000
6000
0
6000
0
0
0
0
6000
0
0
6000
8000
0
8000
8000
0
8000
8000
8000
8000
8000
0
8000
0
0
8000
8000
8000
8000
10000
10000
10000
20000
10000
20000
0
0
10000
10000
10000
0
0
10000
0
10000
0
0
12000
0
24000
12000
0
12000
0
0
12000
12000
12000
0
0
12000
12000
0
0
12000
14000
0
0
28000
0
0
14000
14000
14000
15000
15000
15000
0
15000
0
15000
15000
15000
16000
16000
0
16000
0
16000
0
0
0
TOTAL COST
73000
71000
90000
67000
86000
81000
61000
75000
....... etc
(arbitrary units)

Table 10. The total costs of fixing all limitations for each of twenty useful plant species and the results of using genetic algorithms to choose the five species producing the minimum cost of fixing all limitations, once a range of costs has been estimated for each criterion.
Useful plant species
Total cost
Estimates after genetic algorithm analysis
1
73000
70379
2
71000
67978
3
90000
86512
4
67000
63671
5
86000
84107
6
81000
76541
7
61000
58791
8
75000
72892
9
76000
71700
10
77000
76227
11
75000
72183
12
63000
59703
13
72000
69581
14
79000
76159
15
53000
51356
16
74000
69969
17
73000
71794
18
66000
62572
19
69000
67779
20
70000
66290

Five Species with minimum cost:
Original estimates
Genetic algorithms
53000
15
51356
15
61000
7
58791
7
63000
12
59703
12
66000
18
62572
18
67000
4
63671
4
310000
296093

Conclusions

From the considerations of the approaches to the selection of potential new crops it is concluded that:

The technique of genetic algorithms offers an opportunity to select such new crops as soon as the information is compiled.

There are great opportunities looming in the field of new crop development. However we need to heed the lessons from the past and cooperate throughout the industry to ensure that those crop industries which are targeted for research and development are the ones most likely to succeed with the limited resources available.

References

AIAS (1993). Making it happen. A national strategy for professional support for Australian agriculture to the year 2020. Proceedings of the Australian Institute of Agricultural Science National Conference pp. 14-20. Australian Institute of Agricultural Science Canberra ACT.

Fletcher R.J. (1993). Listing of Potential New Crops. Department of Plant Production The University of Queensland Gatton College Gatton Queensland.

Fletcher R.J. (1995a). Survey of the Australian readership of the Australian New Crops Newsletter. Summary of responses: January 1995. The Australian New Crops Newsletter 3 2-5.

Fletcher R.J. (1995b). Survey of Extension Activity in New Crops in Australia. The Australian New Crops Newsletter 4 12.

Hall N. (ed.) (1992). The New Scientist guide to chaos. Penguin Books London England.

Harlan J.R. (1975). Crops & man. American Society of Agronomy Madison Wisconsin U.S.A.

Jain S.K. (1983). Domestication and breeding of new crop plants. In Crop breeding (ed. D.R.Wood K.M.Rawal and M.N.Wood) pp. 1-20. American Society of Agronomy and Crop Science Society of America Madison Wisconsin U.S.A.

Jolliff G. (1995). Personal communication.

Lewis R.D. (1957). Report of President's Appointed Bipartisan Commission on Increased Industrial Use of Agricultural Products by the Task Group on New and Special Crops. Texas Agricultural Experiment Station College Station Texas.

Sigmund K. (1993). Games of life. Explorations in ecology evolution and behaviour. Oxford University Press Oxford England.

Wood I. Chudleigh P. and Bond K. (1994). Developing new agricultural industries. Lessons from the past. RIRDC Research Paper series 94/1. Rural Industries Research and Development Corporation Barton ACT.