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MULTIPLE CROPPING SYSTEMS ARE DOLLARS AND "SENSE" AGRONOMY PETER E. HILDEBRAND
An invited paper prepared for presentation at the Multiple Cropping Symposium
American Society of Agronomy Meeting Knoxville, Tennessee, August 24-29, 1975
Sector Plblico Agricola Instituto de Ciencia y Tecnolog.a Agricolas Guatemala, Guatemala, C.A.
MULTIPLE CROPPING SYSTEMS ARE DOLLARS AND "SENSE" AGRONOMY PETER E. HILDEBRAND1
A Salvadorean farmer trying to feed his family on a hectare of irrigated land, A Guatemalan farmer planting beans between rocks in powder-dry soil while keeping a hopeful eye out for rain which will signal the start of the rainy season, Two men, neighbors but on different sides of an international boundary, planting different crops. What do they have in common? Multiple cropping systems. The systems are different even though located near each other where climatic conditions are similar. Yet, each of these men has developed a multiple cropping system which simultaneously fulfills a complex blend of agronomic, cultural and economic conditions peculiar to his own area, farm and family situation. This is the promise and the challenge of multiple cropping systems.
For the past two years I have been working in the design of
improved multiple cropping systems and I think of this work as much an art as it is a science. I use the word "design" in the architectural sense--that is, designing multiple cropping systems to satisfy the needs of a group of clients-as much as development of systems
1Agricultural Economist, The Rockefeller Foundation, assigned as
Coordinador de Socioeconomia Rural, Instituto de Ciencia y Teenologla Agrlcolas, Guatemala.
or simply research in cropping systems. Army, Isleib, and Greer2 express this idea quite well and although they referred mostly to fellow agronomists I would also apply their statements to agricultural economists. They say, "Although most of us have been tearing everything apart to examine small parts of the whole, some of our colleagues have been struggling valiently to put things together again. These lonely souls have been developing systems for crop production."
Not many agronomists nor agricultural economists are well equipped to design cropping systems when economic and cultural requirements are integrated with the agronomic aspects of the system. Perhaps part of the reason is pointed out by Army, et. al., when they say that developing systems for crop production has been called "applied research" by some and not worthy of reporting in many of our learned journals. To qualify for most professional journals an article nearly always must be highly technical and usually very specialized; a condition not easily attainable in "applied research." To this I can only say that probably little of what I could report on my work in systems over the last two years would be acceptable for publication by the American Society of Agronomy Journal or the American Journal of Agricultural Economics, because it has been too "applied," but it is already being utilized by small farmers in many parts of El Salvador. This, of course, was the real
2Army, T.J., D.R. Isleib and F.A. Greer. 1971. Integrating production systems to advance yields and quality, p. 83-89. In Moving off the yield plateau. ASA Special Publication No. 20.
reason the research was undertaken in the first place.
Army, et. al., also refer to an article in the Australian Journal of Science by F.H.W. Morley in which he says the economic and the biological aspects of cropping systems often develop in different directions even though agronomy is "dollars and cents biology." There is certainly a strong need for narrowly oriented specialists--be they economists or agronomists--to work in the refinement of cropping systems, but to be rapidly effective, the initial design of a system which farmers can readily use requires broadly oriented scientists who can comprehend all the conditions farmers face in making cropping decisions. I would go one step further than Morley and say multiple cropping systems are dollars and "sense" agronomy.
In this paper I will define some terms which are essential to economic considerations in cropping systems, then describe the more relevant bio-economic relationships. Later, with the use of examples, I will illustrate how economics affects and must be incorporated into work in cropping systems. Finally, a model for research in multiple cropping systems will be presented which utilizes the capabilities of broadly oriented scientists to provide improved systems tailored to specific farm conditions and of more specialized scientists to refine the systems over time. I should emphasize that most of what I will say reflects my current and recent involvement with the problems of small farmers in lesser developed countries, but should not be in conflict with the needs of systems in mechanized, large scale agriculture.
florley, F.H.W. 1968. Computers and designs, calories and decisions, Australian J. Sci. 301 405-409.
PRODUCTIVITY OF MULTIPLE CROPPING SYSTEMS
Productivity is a term widely used but seldom well defined. In monoculture it is often considered simply as production per unit of land area. I would prefer to use the term yield for that concept and the term production to refer to yield times area. In this v,-y, productivity can be reserved for litb m=o -4ohnio.l use which is output (or yield) of any product per unit (either total or additional units) of any particular input or factor of production. It could refer, for instance, to yield per unit of seed or labor or water as well as per unit of land. It can also refer to energy or
protein produced per unit of one of the inputs used in the production process. In other words, to describe productivity one must define the product and the input to which he is referring.
The habit of using yield per unit of land area as the primary measure of productivity in agriculture stemmed from our traditional concentration on monoculture, and a basic assumption that land was the most limiting factor for a farmer. Historically in the United States advances in monoculture proceeded hand in hand with the development of the infrastructure required to support it. This infrastructure provided markets, credit, chemicals, seed and machinery in quantities and qualities usually sufficient so that in most cases the farmer's basic limitation really was land.
In lesser developed countries of today, however, infrastructure
is not always capable of supplying sufficient quantities of inputs
so that factors other than land are often more limiting to farmers4. For farmers in this situation, measures of productivity other than yield per unit of area become more important. In -he Punjab region of West Pakistan, for example, yield per unit of water has historically been much more important to the farmer than yield per unit of land even though the averago fo.m ctmo ir only about 3 hectares5. Under certain conditions in Colombia6 ndr-Guat*_.emala one finds that for some crops farmers refer to their production in tems of yie3d per unit of seed planted because to them seed, which they can eat or sell and which often is ruined before planting time, is a much more scarce resource than land.
In the United States where farm labor is relatively scarce and high priced, it is common to refer to labor productivity or output per man hour of labor. This concept is also important to farmers in
Hildebrand, Peter E. and Edgar G. Luna T. 1973. Unforeseen consequences of introducing new technologies in traditional agriculture. Fifteenth International Conference of Agricultural Economists. Sao Paulo, Brazil.
west Pakistan Water and Power Development Authority, and Tipton and Kalmbach, Inc., Engineers. 1967. Regional Plan-Northern Indus Plains. Vol. II, Economics, Appendix B. Value of Water in the Northern Indus Plains. Lahore, Pakistan and Denver, Colorado.
Andrew, Chris 0. 1969. Improving performance of the productiondistribution system for potatoes in Colombia. Instituto Colombiano Agropecuario, Departamento de Economla Agricola, Boletin No. 4, Tibaitato, and unpublished Ph.D. thesis, Dept. of Agricultural Economics, Michigan State University, East Lansing.
Agro-socio-economic study in the Oriente of Guatemala. In
process. Instituto de Ciencia y Tecnologla Agricolas, Guatemala, Guatemala, C.A.
areas oven where rural labor is generally considered abundant. In
Central America large areas are affected by a 6 month dry season and a 6 month rainy season. When the rains begin everyone plants at the
same time over large areas and labor becomes very scarce. Hence,
even though there is frequent under employment in these areas# at a
very critical time in the production process labor is one of the
* most limiting factors of production and the productivity of labor
for planting is an important consideration.
Problems of measuring output were relatively few when we were
dealing only with monoculture. A field of corn produced corn, a
field of beans produced beans and a field of beets produced beets.
occasionally refinements were added and a field of corn could produce silage or grain, the output of a field of beets could be measured in tons of sugar as well as tons of beets, and we sometimes 0 -thought about the production of protein from a field of beans or
from a field of alfalfa. But the measurement of production from a
multiple crop system is much more complicated. A field might yield both beans and corn and a measure must be devised which helps determine when we are better off raising the production of corn and decreasing the production of beans or vice versa or raising the production of beans proportionately more or less than corn.
The unit for measuring production from a multiple cropping
system must satisfy several criteria. First, it must be common to
all the products. Protein, energy, or dry matter, for instance,
could have this attribute. Second, it should be relatively easy to measure. Third, it must be capable of reflecting quality differences between the products. Fourth, it must provide a means of comparing very different cropping systems.
Energy is a candidate for measuring product that is currently on everyone's mind. This meets the four criteria cited above, but it falls short in a fifth, and this may be the most important of all. The manner of measuring product from a multiple cropping _system must be meaningful to a farmer in such a way that it helps him to allocate his resources between enterprises on the farm. While any unit which fails to meet this criterion may be interesting from a purely scientific point of view, it will not be useful as an aid in desiging systems for farmers.
The market value of the products may be the only unit available which meets all five criteria. Its major weakness, the fact that prices change over time and differ between regions, is at the same time one of its major strengths. This attribute allows it to adjust to changing conditions. As an example, different forms of energy have a different value in the market place. If at some point this value is out of adjustment with reality then price will change to reflect the new supply and demand situation (unless artificial controls are operating in the economy). Biologic conditions in Guatemala are appropriate for the production of sweet potatoes, but very few farmers produce this source of energy because the Guatemalan market puts too low a value on it. Instead, they produce beans and corn which provide energy in a form desired by the buyers and this
is reflected back to the farmer in the market value of the product. Admittedly I am biased, but I opt for market value as the best unit available for measuring products in a multiple cropping system.
BIO-ECONOMIC RELATIONSHIPS RELEVANT TO MULTIPLE CROPPING SYSTEMS8
There are three bio-economic relationships which form the basis for design and analysis of multiple cropping systems. One deals with the relationship between input and output, a second treats the interaction of two or more inputs to produce a given product, and the third concerns the effects between two or more crops.
The most basic bio-economic relationship relevant to cropping systems is that between quantity and value of inputs (factors) and quantity and value of production (product). It is based on the biological response of plants to a factor of production. The growth curve of plants over time (as an input) or the response to fertilizer are examples with which all are familiar.
The maximum rational range of input use can be defined biologically as being between the amounts of input (X) which are equal to or greater than the quantity which maximizes average physical production (APP) and equal to or less than the quantity which maximizes total physical production (TPP), Figure 1. Economically, this range
81n this paper these concepts receive only cursory treatment. For a complete, yet very readable presentation sees Bradford, Lawrence A. and Glenn L. Johnson. 1953. Farm Management Analysis. Wiley and Sons, Inc., New York. Chaps. 8-11.
j Rational Bi3ologic
RATIONAL BIOLOGIC. RANGE OF INPUT USE
is narrowed by considering the price of the nput and the price of the product. The curve which results from multiplying the total physical product by its price is total value product (TVP) and from it are derived average value product or AVP (total value product divided by number of units of input) and marginal value product or MVP (the value added to production by the last unit of input), Figure 2. The minimum rational limit of input use is the same as that determined from a strictly biological consideration, or the amount
which maximizes average value product The maximum rational limit is the amount at which marginal value product is equal to the prioe per unit of the input (Px). This is the amount which maximizes profit (total value product minus cost of the input) and always represents fewer units of input than that which maximizes total physical product unless the input is free.
Any recommendation to a farmer regarding the use of one or more inputs in a single crop or in a cropping system must fall within these economic limits. If it pays to use the input at all, one should use no less than the minimum as defined above because efficiency (average physical or average value product) increases up to that point and unit cost of production declines. Even farmers who are very short of capital, if they apply any of the input, should be encouraged to use no less than this amount. The small irrigation farmer in the Punjab distributes his precious water so as to apyly this quantity and the small farmer in the south of Colombia dos the
9This is also the amount which minimizes unit cost of proluction with respect to the same input, a concept very important to s small farmer with few resources.
! I 1 1 I I I
RATIONAL ECONOMIC RANGE OF INPUT USEtional
i I l'"Economic
RATIONAL ECONOMIC RANGE OF INPUT USE
same with his potato seed.
The maximum economic limit on input use is more meaningful to
the farmer with abundant capital or credit. At this level, the farmer makes more net income even though the efficiency with which he is using his capital and inputs is less than the maximum possible. In view of his favorable economic situation, however, it is not critical for him to be so concerned with this measure of efficiency. Also, because of his higher economic status, he is better able to cope with the risks associated with using more and more inputs at ever decreasing levels of productivity and increasing unit osts of production.
The second basic bio-economic relationship relevant to the design of cropping systems is that dealing with how to combine two or more factors of production, or inputs, to produce a given product. This relationship is presented graphically in Figure 3. In this figure, the quantity of two inputs, X1 and X2 are measured on the 1/
two axes. Topographically, the amount of product, which would be measured on a third axis, is presented by contours or iso-product lines (Y1p Y2p etc.) shown in the figure. Contour Y4 represents more of the product than contour Y3 which represents more than Y2 etc. Along any one iso-product contour, any combination of X1 and X2 represented will produce the same amount of product (based on the biological relationship between the factors and the product). On contour Y1' for example, c units of X1 and d units of X2 produce the same amount of product as e units of X1 and f units of X2.
I I Y
d f bi X2
COMBINING INPUTS TO PRODUCE ONE PRODUCT
Once again, without regard to economics, a rational:-maximum range of combination of factors X and X can be defined. This
- 1 2
range is that between the scale lines a1 a2 and bI b2 because outside this range, the use of more of one input, without changing the use of the other input, decreases the total amount of product forthcoming.
Economically, the best combination of the two factors to use to produce a given amount of product depends on the prices of the two inputs. If factor X1 in Figure 3 is inexpensive relative to X2P one would suppose the combination of c of X1 and d of X2 to be a better (lower cost) means of producing Y1 of the product than e of X1 and f of X2. Figure 4 represents this case. The iso-cost line a1 a2 represents all combinations of the two inputs which can be purchased for a given cost, and more X1 can be purchased for this amount than X2. For the amount of cost represented by aI a2 the best combination is b units of X and c units of X2 because more of Y can be produced for the given cost with this combination than with any otherI0
If the amount of capital available to a farmer is not limited, then he must consider how much to produce by purchasing more X1 and X2. In its simplest form this procedure reduces to a factor-product relationship in which the factor becomes a combination of X1 and X2
10Mathematically, the best combination of inputs is the amount which satisfies the relationship MPPx2/ MPPxI = Px2/ PxI1 where the biological factor-product relationship is Y = f (X1, X2) and the given cost C Px1 X1 + Px2 X2 and PxI and Px2 are prices of the
* FIGURE 4
BEST ECONOMIC r;OMIN~ATON OF INPUTS TO USE
in some fixed proportion. A premixed fertilizer such as 16-20-0 is a common example where the use of this particular formula is based on the assumption that 16 units of N and 20 units of P2 05 satisfy the factor-factor relationship over all levels of application.
The factor-factor relationship can also help to visualize the effect on factor productivity caused by the interaction of inputs.
Figure 5-B is derived from 5-A and shows the effect on the amount of product Y produced by a given amount of X1 (= c) as the amount of X2 is raised from a units to b units11, The relationship can readily be interpreted if one considers X1 to be nitrogen and X2 to be soil humidity, and quantity a of X2 is insufficient for proper plant growth while quantity b is adequate.
The most important bio-economic relationship relevant to multiple cropping systems is that between two or more crops or products. Historically, in making recommendations to farmers, each crop has generally been considered independently even if more than one crop was being produced on the farm, This is a valid procedure from the farmer's point of view only if he has no limit to the capital he can spend on each of the crops and uses the amount of each input required in each crop to maximize profit (equate marginal value product with price of the input). On most farms, in most areas of the world,
"The lower curve in 5-B shows the factor-product relationship between X and Y when X2 is fixed at a units, or Y = f (X1jX2 = a). The upper curve is Y = f (XIx2 = b).
d X2= a
FIGURE 5 a. INTERACTION EFFECT OF ONE INPUT ON PRODUCTIVTY OF ANOTHER,
this is not the case. When funds are scarce, a farmer must decide upon the quantity of an input to use on one product based not only on its profitability in producing that product but also in the profitability of alternative uses of that input in other products.
In Figure 6p AVPA and MVP are the average value product and marginal value product of X in producing A while AVP Band I4VP Bare the same functions for product B. The Y axis of the graph in this
case is in terms of market value because we are measuring the response of two different crops and the X axis measures physical units
of input X to produce either product A or product B.,
If a farmer Is going to apply any of input X he should use no less than amount c for crop B because this is the lower rational
limit as defined previously in the discussion of the factor-product relationship. If he is exceedingly limited on funds he could apply
only c units of X in the production of B without using any in the
*production of Abecause the marginal productivity of Xin Aistoo
low to warrant its use for that crop.
After deciding to use c units to produce B9 if funds are still available, a units of X could be purchased to produce A and d-c
additional units could be invested in X to produce B. If after investing in a units for A and d units for B, additional funds are
still available for investment in this input, the amount destined
for A and the amount allocated to B should be proportioned such that the MVP of X in A is always equal to the MVP of X In B. The use of
b units in A and e units in B, resulting in an MVP in both crops equal to f# would be an example. The upper limit in the use of X
--- --- ~AVP B
MVPA., MVP B
ALLOC"AIOFA IU EWNTOPDCS
is the quantity for which the MVP in each crop drops to the price of
the input, g, and the maximum profit level of investment has been
achieved for both products 12.
The important concept to be gleaned from these last few paragraphs is that as one is considering investing in more and more of an input to be used in two (or more) crops the amount allocated to 0 each crop should always be such that the MVP of the Input is equal
in each altenative use. For farmers with limited capital to invest,
-this concept has important implications and means that no one crop
can be considered independently from any other. The critical importance of this principle to a multiple cropping system should be
obvious and will be illustrated with an example in a later section
of this paper.
The product-product relationship also has Important implications
in another aspect of multiple cropping systems, In Figure 7-A are
shown two independent prod uction functions for crop A and crop B as they respond biologically to an input (or package of inputs) X. In Figure 7-B the quantities of crops A and B produced are measured on
the two axes. The curve bcd3 in 7-B shows all possible combinations
of A and B which the farmer can produce by using his inputs,, Xp in
one or in both crops and is known as the pucionossibilities
curve.* This curve manifests some important characteristics.*
12 Admittedly this is a rather loose description and presents a
slight error in allocation between the investment in c total units and d + a -total units, but to clarify this would unduly complicate
an already complex concept and figure. The reader is referred again to Bradford and Johnson, 1953, or Heady, Earl 0. and John L. flillon,
1961. Agricultural production functions. Iowa State University
FIGUR 7 B
COMB3IN~~flON OF CROPS WITH A FIXED SET OF RESOURCE S*
some of the inputs are shifted from producing all A (b units of Y to producing mostly A but some B, the output of both crops increases (portion of the production possibilities curve between b and c). Obviously, c is a better combination of crops for the farmer than b because he produces more of both for the same cost (using the same
set of inputs). Economists call this phenomenon complementarity between two products. To differentiate it from a similar biologic effect it can be called economic complementarity.
The best combination of crops A and B to produce with a given set of resources depends on the price of the two products and will always fall between c and d on the production possibilities curve, the area in which the crops are competitive. In this area, more of one crop can be produced only at the expense of the other. Some of the most interesting work in cropping systems deals with the effects of competitive crops. Shifting the relative populations of corn and
beans is a common example13.
The production possibilities curve fg in Figure 7-B demonstrates biologic complementarity between the two products. This kind of complementarity is caused by the relationship which exists between a legume and a grain in a rotation or in a multiple cropping system. This phenomenon differs from economic complementarity in that it
causes a shift upward of the whole production possibilities curve without any increase in inputs on the farm. The result is the same, however, in that more of both products are produced for the same
13See, for example, IRRI Annual Report for 1973. Multiple Crop-
investment. All who have worked with multiple cropping systems have seen the effect of this cause of complementarity.
A third concept important to the study of cropping systems is
derived from the product-product relationship and is shown in Figures 8 and 9. Production possibilities curve ahb in Figure 8 is the same as in 7-B and represents a farm which has abundant resources. The
production possibilities curve ef in Figure 9 represents a farmer so short of resources that he barely achieves the minimum rational level of input use in either crop A or crop B. When he uses his resources in both crops, the amount in each is less than that required to reach
the minimum rational level. This situation gives rise to the inverted production possibilities curve in Figure 9.
The line chd in Figure 8 is an iso-revenue line representing
all combinations of A and B which would result in the same income to the farmer. At h, the point of tangency, the production possibilities curve reaches the highest possible iso-revenue curve and hence this represents the best combination to produce.
The form of the production possibilities curve is fixed biologically and by the amount of resources the farmer has. The slope of the iso-revenue curve is determined by the prices of A and B. As a
result, the best combination of A and B shifts as prices of the crops
change For a farmer with abundant resources, his best alternative
The equating of the two slopes at the point of tangency is
the same as equating the MVP's of the input (or inputs) in each of the crops, as discussed previously.
* BEST ECONOMIC COMBINATION OF CROPS
will nearly always be a combination of the two crops, which means he should have a diversified farm.
The iso-revenue curve in Figure 9 represents a farmer with very few resources. In this situation it is apparent that specialization
in one crop or the other should yield more income. Yet in the case of subsistence farms, the most common type with very inadequate resources, they are nearly always diversified. In this regard, a multiple cropping system, which could be considered and can be managed as a single enterprise, can have very important economic implications. It allows a farmer to concentrate in one basic economic activity-his multiple cropping system--but at the same time produce several crops for subsistence and his need or desire to reduce risks. Yet
because he is specializing, he moves to a higher iso-revenue curve and increases his meager earnings.
SOCIO-ECONOMIC CONSIDERATIONS IN DESIGN OF MULTIPLE CROPPING SYSTEMS
Three of the most important bio-economic relationships affecting multiple cropping systems have been presented. In this section three examples of how bio-economic and socio-economic considerations have been incorporated into work on multiple cropping systems will be described. The first two are examples of systems for very different conditions in Central America. The third illustrates the use of the product-product relationship in fertilizer experiments and recommendations.
A Salvadorean Multiple Cropping System15
El Salvador, the smallest Central American Republic has, along with Haiti, the highest population density in the western hemisphere, numbering nearly 500 people per sq. mile. Although the country is more industrialized than the average in Central America, it still
depends heavily on agriculture to generate income, feed its people, and employ the still predominant rural population.
In 1973, in the face of worsening rural conditions and a declining food supply, the country placed urgent priority on the production of basic grains and vegetables, generating productive sources of rural employment and increasing rural income, with special emphasis given to irrigated areas. It was in response to these conditions that the Salvadorean system of multiple cropping was designed.
Some of the most important considerations in designing the system were the followings
1. The system could utilize mechanization for land preparation but
should not depend on it because the majority of farmers do not
have access to tractors.
2. It should create additional, remunerative employment per unit
of land area as well as increase family income potential.
3. The system could include vegetables but must be based on corn
and beans, the staple diet of the country, without which the
15Hildebrand, Peter E. and Edwin C. French. 1974. Un sistema Salvadore-o de multicultivos. Departamento de Economla Agricola, Centro Nacional de Tecnologia Agropecuaria (CENTA), Ministerio de Agricultura y Ganaderla. San Salvador, El Salvador, C.A.
system would be unacceptable to the farmer.
As developed, the most interesting characteristic of the system is the use of double or twin rows of corn which allow more open space 16
between them for other crops without reducing the corn population The double rows are planted 30 cm apart and the present recommendation is 1.5 m between the centers of twin rows, Figure 10. In practice, this distance varies because the rows are usually made by bullocks and a wooden plow which provides poor control on row width.
In the basic system radishes and beans are planted in the
space between the twin corn rows simultaneously with, or a few days before the corn is planted. Radish harvest (about 30 days) occurs just as they are beginning to compete with the beans for solar energy. The beans reach a mature green pod stage before being shaded excessively by the corn and when mature are pulled, providing working space once again between the double rows of maturing corn.
Before the corn is "doubled'18 cucumbers are planted between the
l6For information on how and why the double row concept was developed as well as a history of the development of the system, see: French, Edwin C. 1975. Development of multiple cropping systems for small farmers of El Salvador. Unpublished M.S. thesis. Department of Horticulture. New Mexico State University. Las Cruces, New Mexico.
17For a complete description of this basic system as well as other related systems, seel Hildebrand, Peter E., Edwin C. French, Mario A. Barahona, Adrian E. Chac'n and John Bieber, 1975. Manual pama Multicultivos. Ministerio de Agricultura y Ganaderla, Centro Nacional de Tecnologia Agropecuaria, Departamento de Economla Agricola, Santa Tecla, El Salvador, C.A.
18A process common to the area in which the stalks are bent over just below the ears, so that they can be left inverted in the field to dry and await harvest in the dry season.
FIGURE 10 BASIC MULTIPLE CROPPING SYSTEM DEVELOPED
FOR EL SALVADOR.
DAY PItOCEDURE r
Qm BEAN JORM
-5 Radish 6*64f"s.
-3 OW*h Dean MOO.
0 Corn seeding.
76 gush been harvest.
0 Vt 73 Bad preparation.
90 twoumber $244140.
104 FormaVort of 1006040 ucumseft
training of owtumberm.
190 Harvest of try torn.124 First eveaffiber harvest
Tromaplooll of r4bbalo.
173 t.4*1 owcombor harvest.
--I$$ sef'ond iseedine of 44#6. CASB= MUSPLANTS
--2,29 cabbage 1141fmt.
864 01teparallok 14
Z t-te I-Ims botia essent r."T ON" C"BA"
309 Cora bafv"%*
342 Harvest at P110 1100114% FOL9 W N
twin rows after applying fertilizer, soil insecticides, and/or nematocides. This preplanting process also includes bed formation and weeding. After the cucumbers germinate the corn'is harvested or doubled and the leaves are stripped off so that full sunlight is available for the cucumber plants. The cucumbers are staked with twine to a tripod formed from corn stalks in the double rows providing important advantages at very low cost.
Before the last cucumber harvest, cabbage (or broccoli or
cauliflower) is transplanted on the outer edges of the bed and following the last cucumber harvest the corn stalks and cucumber plants are cut and placed in the rows between the cabbage. Three to four weeks following the transplant of the cabbage, corn is planted, once again in double rows, in the space where formerly there were.beans. Three to four weeks after tasseling of the corn and shortly after the harvest of the cabbage, pole beans can be planted at the edges of the corn to use the stalks as soon as they are doubled and stripped of leaves.
The pole beans are the seventh crop-, the complete system being easily terminated within a year's time. With irrigation, the system produces two full corn crops, more than the equivalent of one full bean crop, heavy cucumber and cabbage crops and a partial crop of radishes. The system is so labor intensive that a family can manage only up to a half hectare, yet income for the family is considerably more than they could make on several times that amount of land in
traditional production methods. In one year, on 900 sq m, this system produced U.S. $772 in net family income (net income plus value of family labor)19.
The system is not complicated for farmers accustomed to multiple cropping systems although highest productivity does depend on closely adhering to a calendar of events. No tools beyond simple hand tools and wooden plows are required except for sprayers, which most have because of a recent.increase in vegetable production in the irrigated areas. In general, the farmers use the varieties they know and the system is sufficiently flexible that they are encouraged to, and do, modify it on their own.
Because of the interest of farmers in the system and in the way it satisfies the urgent priorities of the country, a program to introduce it on a pilot basis over a large part of the country was initiated by the extension service less than two years after design of the system was originated. If results are as expected, this will be a national program next year. At the same time, the system as designed is serving as the basis for several new research projects which will refine the basic system and provide increasingly better recommendations, varieties and ideas to farmers.
A Multiple Cropping System for Grain Production in a Dry Area
In southeastern Guatemala, the government has initiated an
19Chac'n, Adrian E. and Mario A. Barahona. 1975. Granos b~sicos en multicultivos. pp. 63-76, Vol. I. In XXI Reunion Anual, Programa Cooperativo Centroamericano para el Mejoramiento de Cultivos Alimenticios (PCCMCA). San Salvador, El Salvador, C.A.
intensive program to increase grain production (corn, sorghum and beans) and increase the income of the small and medium farmers in the
area. The majority of small farmers till rolling to steep land, much of it rocky (some almost pure rock), highly susceptible to the drouth conditions which characterize the region. The most common traditional system is corn, sorghum and beans all planted together. Yields for small farmers (fewer than 3.5 hectares) in the area in 1974 were 536 kg/ha for corn, 412 kg/ha for beans and 631 kg/ha for sorghum20 There is apparent under employment among the small farmers in this area, but there is a severe shortage of labor for planting in May and June when the rains start. This is created by the strong seasonality of the rains, their uncertainty even in the rainy season and a very short critical period for planting. To cope with these conditions the farmers have devised a unique system. As the rains are approaching, but before they start, they plant their scarce and valuable bean seed in powder-dry soil. As soon as the rains start, and they hopefully, but not always, begin with heavy downpours, the corn and sorghum are planted on top of the beans without knowing where these were sown.
With the local varieties and in this system, if the beans germinate before the corn and sorghum are planted, they tend to dominate the taller species, while these will dominate if they germinate before the beans. Hence, timing is a very critical factor, aggravated by the fact that planting is done by hand, using a
20Agro-socio-economic study in the Oriente of Guatemala. In process. Instituto de Ciencia y Tecnologia Agrcolas, Guatemala,
metal-tipped pole. As a result, there is feverish activity to plant corn and sorghum in all the land that has beans before the beans germinate. Later, the rest of the land is planted with only corn and sorghum.
This system allows the farmers to accomplish their planting, but it also creates a risk for them. Beans planted in dry soil before adequate moisture is available are subject to the risk of receiving moisture adequate to initiate germination but inadequate to sustain growth. This could result in a complete loss for the farmer, and is a situation which happens not infrequently.
Several experimental multiple cropping systems planted in May of this year are designed to cope with the conditions 'which the farmers face in this area, yet to increase production and income. The3y utilize the advantages of the double corn row developed in El Salvador, and are designed to reduce the risk by waiting to plant beans until adequate soil moisture is available to sustain growth*
In the most promising system, 3 rows of beans are planted
21, ewe hs osa
about 30 cm apart .Btenhse3rwand the adjacent 3 rows, sufficient space is left for double rows of corn 22 After the beans have emery ged, the corn is planted. If, as happened this year, the rains stop for a period after bean planting, the corn planting can be delayed without fear of dominance by the beans. In fact, the
2k0T facilitate adoption by the farmer, local measures are used in the system.
22The distance between centers of the double rows of corn is 2 I"varas"' or 1.68 m.
delay improves the bean crop by reducing even further any competition with the corn.
The beans used this year are a short season variety from El Salvador and can be harvested in 60-65 days. As soon as the beans are harvested a short season sorghum is planted in the space between the corn rows, and will be growing about a month before the corn is doubled. About two weeks before th6 corn is doubled, cowpeas will be planted on the outer edges of these twin rows and the leaves of the corn will be used as a mulch to conserve what humidity is available as the rainy season ends.
The results of this system are still unknown but appear promising. Labor requirements fit in well with availability and only hand tools are required. A local 'criollo' corn variety is being used
although a hybrid adapted to better conditions in the region is being tested. The system requires short season beans and sorghum- the beans being used come from a nearby region with similar conditions and appear to be well adapted. The sorghums23 were developed locally, and produce well in good conditions, but their adaptability to the conditions of these small farmers remains to be seen.
With minimum fertilizer and insecticide use, in accordance with the economic possibilities of these farmers, it is hoped that production potential of corn and sorghum per farm can be doubled owing to a doubling of the population of each. The production of beans per
23Two varieties are being tested Guatecau from Guatemala and CENTA S-1 from El Salvador.
farm should be maintained even though the yield will decline somewhat per area planted. This will be partially offset by an increased area planted and partially by an increased yield per plant because of less 24I
competition with the corn and sorghum Any production from cowpeas, which have been raised-as a substitute for beans in the area but on a small scale, will be a bonus.
Fertilizer Allocation in Multiple Cropping Systems
In order to improve the recommendations to farmers in the pilot promotion program in El Salvador, an experiment was undertaken to determine the appropriate distribution of nitrogen to each of the six crops fertilized in the system. The crops were: radishes (no fertilizer), beans, corn, cucumbers, cabbage, a second crop of bush beans and onions. The system, designed for an onion producing area, was a modification of the basic system.
Without going into detail on the experimental design, the treatments were zero, 200, 400, 600, and 800 pounds of elemental nitrogen
per manzana (7000 m2) per year, distributed in fixed proportions between crops. That is, each crop in the 800 pound treatment received
twice the N received by the same crop in the 400 pound, or central treatment. Quantities for thp central treatment and the proportion for each crop were based on prior information obtained from monoculture trials plus what little information was available from previous
94The increased yield per plant (or per pound of seed planted) will please the farmers who calculate yield in this manner rather than in yield per area. However, the use of short season varieties may cancel this effect until ... -... short season .... are selec-
work in systems, and were the following in terms of kilograms of N per hectares corn and cucumbers, 82 kg in 2 applications; beans,
7 kg in one application; and cabbage and onions, 41 kg in 2 applications. The source of nitrogen was ammonium sulfate. The data on onions were not available at the time this was written; the first crop of beans was lost and the response derived from the second crop; and the analysis of the other data should be considered preliminary,
but will serve as an excellent example25.
Analysis of each crop individually is by quadratic regression based on the response of each within the system. Each regression equation relating production to nitrogen can be considered as the response of a separate product and the appropriate economic allocation of fertilizer can be made on the basis of the product-product relationships presented earlier. In the case of five crops, the analysis is comprised of a set pf either 5 or 6 equations depending on the economic conditions of the farmers for whom the system is designed.
For each crop, and derived from the production function,.. there is a marginal value product function equating this to a constant value: Py1 (dyi/ dN) K. The minimum value which K can assume is the price of the input, nitrogen. For the wealthy farmer, these 5 equations complete the system and K is the price of nitrogen. The solution of the system, distributing the nitrogen between crops, is
25The soil was high in potassium and previous trials had produced no response to phosphorus. For these reasons and to keep the experiment simple, only nitrogen was varied.
the one which maximizes profit for the farmer who does not have a limit on the amount of fertilizer he can purchase. If the amount of fertilizer is limited by the farmer in accordance with his economic situation, a sixth equation expressing this limit is required SNy = F. In this equation Nyi is the amount of N to be allocated to the ith crop and F is the total amount of fertilizer the farmer can obtain,
The following biologic production functions were derived from the fertilizer trial. For each function N is 100 pounds (cwt.) of N and product is also measured in 100 pound units, or suintales.
First beans F = 7.59 + 41.32 Nf 173.26 Nf 2
Corns M = 33.78 + 28.28 N 6.98 N 2
Cucumbers P = 74.12 + 416.87 N 97.63 N 2
Second beans B 13.67 + 74.38 Nb 311.87 Nb2
Cabbages R = 54.66 + 104.34 N 16.75 N 2
Using the following as prices of the products: beans, $20.00
per cwt; corn, $6.00 per cwt; cucumbers, $2.50 per cwt; and cabbage, $5.00 per cwt; the MVP of nitrogen for each crop or Pyi (dyi/ dN) is shown below and equated to the constant, K:
for F s 826,40 6930.40 Nf = K (1)
for M 1 169.68 83.76 N = K (2)
for P I 1042.18 488.16 N K (3)
for B s 1487.60 12,474,80 Nb K (4)
for R 521.70 167.50 Nr K (5)
Adding the restriction for the amount of fertilizer the farmer can obtain or is willing to purchase, gives the sixth equation:
Nf + Nm + Np + Nb + Nr =F (6)
Equations 1-6 contain 7 unknowns, but because either K or F will be given, the system is complete. In the case of a wealthy farmer with no restrictions on purchase of fertilizer, K can be the price of N. When a poorer farmer determines F, then K is the unknown value of the M for N in each crop.
If the farmer has no restrictions on fertilizer then K = 44, the price of 100 pounds of N, and the solution defines the maximum rational limit on fertilizer use. In this case the solution in pounds of N per manzana and kilograms of N per hectare are shown below and compared with the distribution utilized in the experiment. Table 1. Fertilizer distribution between crops for a wealthy farmer
and comparison with experimental distribution.
0Crop lbslMz kg/Ha kg/Ha
First beans 11.3 7.3 1.7 13.4 311
Corn 150.0 97.4 22.7 161.2 37.5
Cucumbers 204.0 132-5 30.8 161.2 37.5
Second beans 11.6 7.5 1.7 13.4 3.1
Cabbage 285.0 185.1 43.1 80.6 18.8
TOTAL 661.9 429.8 100.0 429.8 100.o
If a farmer (or his credit source) limits the amount of fertilizer he will purchase to, say, 20 hundred pound bags of ammonium sulfate per manzana per year then F = 4.2 or 21 percent of 2,000 pounds, expressed in cwt. From equations 1 to 6, the solution resulting in K 165.7 is shown in Table 2.
These two solutions illustrate the interrelationship between
the crops and the effect on optimum allocation as fertilizer quantity is changed. In the experimental design, based on information primarily from monoculture, the three grain crops were alloted 43.7 percent of the fertilizer. In the system and for the poorer farmer the grains receive only 5.9 percent and this increases only to 26.1 percent in the high profit solution of the wealthy farmer. The vegetables yield a greater return on the investment in fertilizer and should be allocated more when considered with the grains than was done in the experimental design. In practice the poor farmer should probably not use any fertilizer on his beans but instead allocate that fertilizer to the corn. Small amounts are difficult or impossible to apply and the additional amount on the corn serves the double purpose of strengthening the stalks which will be used for staking cucumbers.
Table 2. Fertilizer distribution between crops for a poor farmer
and comparison with experimental distribution.
Crop Solution Experimental
rolbs/Mz kg/Ha kgla
First beans 9.5 6.2 2.3 8.5 3.1
Corn 4.8 3.1 1.1 101.5 37.5
Cucumbers 179.5 116.6 43.1 101.5 37.5
Second beans 10.6 6.9 2.5 8.5 3.1
Cabbage 212.5 138.0 51.0 50.8 18.8
TOTAL 416.9 270.8 100.0 270.8 100.0
A MODEL FOR DEVELOPMENT OF MULTIPLE CROPPING SYSTEMS
In my work over the last two years, a model utilizing multiple cropping systems as a basis for conducting coordinated research has evolved. The model reflects the need for rapid results from research particularly important in El Salvador where traditional procedures of spending several years on vaguely oriented research before recommendations are made is a luxury which can no longer be afforded.
Two completely different situations for which multiple cropping systems are being developed were presented earlier. In each case,
the system was being developed for precisely specified agronomic and economic conditions. The basic cropping system designed in El Salvador satisfied the necessities of the farmers as well as the country sufficiently well that it is now being utilized by many farmers (some
for as long as 18 months) and Is the focus of a national promotion program.
The system was developed without the benefits of a team of
agronomists and many more agronomic questions were raised than were answered, yet the farmers for whom it was designed are eager to utilize it. I am convinced the reason for this ready acceptance of a new technology is because it was designed specifically for them. It satisfies their needs because its development 'Was based on a study to determine what these needs were and to identify the restrictions relevant to them. The system meets conditions important to this group of farmers and which make it possible for them to use given their economic, social and agronomic situation.
In the development of the system which finally emerged we had to, and were able to, cast off many traditional concepts which are second nature to a modern agricultural scientist. One of the most interesting related to our extremely high use of manual labor. Most non-farmers who visited our experimental plots suggested that we should be able to make the system more "efficient" by the use of small, walking tractors and specialized equipment. This, idea never occured to the farmers for whom the system was designed because 1) a tractor, of whatever size, is completely out of the
range of possibilities for them for a myriad of reasons, and 2) they saw the system as a means of providing them gainful employment and increasing their incomes in conditions in which they could work.
An augmented team of foreign and national scientists began a
concentrated effort this year to refine the system and to answer
many of the agronomic and economic questions which were raised.
There is no doubt that the basic system will be modified to adapt it to differing conditions and each modification can be improved time and time again. But even while this is going-on, -the basic
system is being used and the farmers are benefiting from it.
For multiple cropping systems development in countries which
cannot afford to wait for results from traditional research methods,
I recommend a procedure structured after the process which evolved
in El Salvador and which is being utilized in Guatemala. The model, shown in Figure 11, has three characteristics which are valuable in
developing countries. It maximizes the probability of rapidly generating a technology immediately available and highly appropriate to
the target group-, it provides orientation for more detailed research
to follow; and it creates a multidisciplinary environment so vital to
successful research in multiple cropping systems.
0 The focus of the model is on farmers--on a target group whose
so cio-economic conditions and agricultural situation are sufficiently
homogeneous that their needs and capabilities can be readily specified. These farmers are the subjects of a three-pronged attack,
The first Is an agro-socio-economic survey to determines 1) What
-they are doing, and 2) Why they are doing it the way they are. In
order to determine the latter it is necessary to understand economic and cultural as well as agronomic restrictions which condition their
cropping patterns and practices.
Cogrop Saige Etc.a rSoco Imdat.e,
The second prong of the attack is to initiate experiments on improved systems designed specifically for these farmers. For the results to be immediately transferable the experiments must be conducted under the same conditions as those of the farmers. The same person or persons responsible for the agro-socio-economic study should share responsibilities for design of the experimental systems with one or more agronomists. Ideally, the agronomist should also have
responsibility in the agro-socio-economic study of the farmers.
I would suggest that the team responsible for the experimental systems be small--just two people may be optimum--and the project should be kept highly flexible to take advantage of all new information as soon as it is available. In Guatemala our current systems experiment is being modified continually. At times, such flexibility can disturb the statistical accuracy of the trial, but the goal of the project is information and not a publication. For this first stage of research, treatments need not be defined so narrowly that only one factor varies between them. The object is to design a system that works so treatment differences can be complete changes
of systems. Refinements to determine the cause of a particular effect can wait on the second, or refinement stage of the research effort, which is the third prong of the attack. The refinement of the basic system involves more traditional research procedures by more narrowly oriented scientists. Fertilizer use, varietal improvement, disease control, product quality and timing of production are examples of refinement needs.
The advantage which this model offers is that the effects being made by the specialists are coordinated and oriented toward known conditions. These conditions are those 0$ the farmers as they have been defined in the study of the farmers themselves, from the results of the systems experiment conducted under farm conditions, and later from the results obtained by farmers who have used the "improved" system derived in the first stage of the process.
Economics and agronomy are inseparable in multiple cropping systems. Unlike monoculture crops, which can have rather wide adaptation, multiple cropping systems must be designed for specific agronomic, economic and cultural conditions. A farmer's economic situation, which dictates how many and what kind of resources he has to work with, is as important in determining a feasible cropping system as are his soils and climate. Because it is the farmer who makes the decision whether or not to utilize any particular cropping system he needs a unit of comparison between systems which is meaningful to him and which he can interpret in his decision making framework. The only practical unit for measuring production which meets this and four other necessary criteria is market value of the products. Hence, both in use of inputs and in selecting products, the union of agronomy and economics is essential in multiple cropping systems.
Multiple cropping systems, as a field for research endeavor, provide an excellent framework within hich to undertake multidis-
ciplinary research and development, but require that many traditional research procedures be reconsidered. Because multiple cropping systems are specific to regions and types of farms, initial experimental research should be undertaken after determining the agro-socio-economic conditions of the farmers for whom the improved system is to be designed. Later, the improved system or systems can be refined with the help of more traditional research procedures, but these efforts will be more productive because they will be oriented toward specific farm situations. The multidisciplinary demands made on us by implicitly considering the needs and conditions of the farmers for whom we are working reflect both the challenge and the promise of multiple cropping systems.
Andrew, Chris 0. 1969. Improving performance of the productiondistribution system for potatoes in Colombia. Instituto Colombiano Agropecuario, Departamento de Economla Agricola, Boletin
No. 4, Tibaitati, and unpublished Ph. D. thesis, Dept. of Agricultural Economics, Michigan State University. East Lansing.
Army, T.J., D.R. Isleib and F.A. Greer. 1971. Integrating produotion systems to advance yields and quality, p. 83-89. In Moving
off the yield plateau. ASA Special Publication No. 20.
Bradford, Lawrence A. and Glenn L. Johnson. 1953. Farm management
analysis. Wiley and Sons, Inc., New York. Chaps. 8-11.
Chacon, Adrian E. and Mario A. Barahona. 1975. Granos bisicos en
multicultivos, p. 63-76, Vol. I. In XXI Reuni6n Anual, Programa
Cooperativo Centroamericano para el Mejoramiento de Cultivos
Alimenticios (PCCMCA). San Salvador, El Salvador, C.A.
French, Edwin C. 1975. Development of multiple cropping systems
for small farmers of El Salvador. Unpublished M.S. thesis, Dept.
of Horticulture. New Mexico State University. Las Cruces, New
Heady, Earl O. and John L. Dillon. 1961. Agricultural production
functions. Iowa State University Press, p. 48-50.
Hildebrand, Peter E. and Edwin C. French. 1974. Un sistema
Salvadoreno de multicultivos. Departamento de Economla Agricola, Centro Nacional de Tecnologa Agropecuaria (CENTA),
Ministerio de Agricultura y Ganaderia. San Salvador, El Sal- vador, C.A.
HildebrandI Peter E., Edwin C. French, Mario A. Barahona, AdriAn
E. Chacon and John Bieber. 1975. Manual para multicultivose.
Departamento de Economla Agricola, Centro Nacional de Tecnologla
Agropecuaria (CENTA), Ministerio de Agricultura y Ganaderla.
San Salvador, El Salvador, C.A.
Hildebrand, Peter E. and Edgar G.. Luna T. 1973. Unforeseen
consequences of introducing new technologies in traditional
agriculture. Fifteenth International Conference of Agricultural
Economists. Sao Paulo, Brazil.
IRRI Annual Report for 1973. Multiple Cropping. Los Bahos, Laguna,
Morley, F.H.W. 1968. Computers and designs, calories and decisions.
Australian J. Sci. 30s 405-409.
West Pakistan Water and Power Development Authority, and Tipton and
Kalmbach Inc., Engineers. 1967. Regional Plan-Northern Indus
Plains. Vol. II, Economics, Appendix B. Value of Water in the Northern Indus Plains. Lahore, Pakistan and Denver, Colorado.