drought as a challenge for the plant breeder

Plant Growth Regulation 20: 14‘%155, 1996.

@ 1996 Kluwer Academic Publishers. Printed in the Netherlands. 149

Drought as a challenge for the plant breeder

S. Ceccarelli & S. Grand0 International Center for Agricultural Research in the Dry Areas, P.O. Box 5466, Aleppo, Syria

Abstract

Since agriculture began, drought has been on of the major plagues affecting crop production causing famine and death. Despite many decades of research, drought continues to be a major challenge to agricultural scientists. This is due to the unpredictability of its occurrence, severity, timing and duration; and to the interaction of drought with other abiotic stresses, particularly extremes of temperature and variations in nutrients availability; and with biotic stresses. Breeding has not been as effective in improving crop production under drought-stress conditions as it has in their absence - or where the stress can be alleviated by irrigation. This paper argues that the relative lack of success of breeding for stress conditions in general, and for drought-stress conditions in particular, can be partly attributed to use of the same breeding approach that is successful for favourable environments. A different breeding approach for drought-stress conditions is discussed in relation to the environment in which selection should be conducted, the germplasm to be used, and the experimental designs and plot techniques to be employed.

1. Introduction

Drought continues to be a challenge to agricultural scientists in general and to plant breeders in particular, despite many decades of research. Drought, or more generally, limited water availability is the main factor limiting crop production. Although it reaches the front pages of the media only when it causes famine and death, drought is a permanent constraint to agricultural production in many developing countries, and an occasional cause of losses of agricultural production in developed ones. The development, through breeding, of cultivars with higher harvestable yield under drought would be a major breakthrough; that is one of the reasons why drought is such a challenge. However, the ability of some plants to give a higher economic yield under drought than others in a very elusive trait from a genetic point of view. This is because severity, timing and duration of drought will vary from year to year, and cultivars successful in one dry year may fail in another. To make matters worse, drought seldom occurs in isolation; it often interacts with other abiotic stresses (particularly temperature extremes) and with biotic stress. Also, areas with a high risk of drought (and/or other abiotic stresses) generally have low-input agriculture. Thus, breeding for drought resistance is

made more complex by the interactions of drought with other stresses. This problem is a challenge due to its complexity, as well as its gravity. The objectives of this paper are: to discuss key problems faced by breeders when they breed for stress environments; to analyze possible reasons for the limited success breeding has had in dry areas; and to indicate ways to over- come the inherent difficulties in breeding for stress environments.

2. Breeding for drought resistance

In areas affected by drought, progress with empirical breeding has been negligible. As a result the yield of some important staple crops has shown only modest increase. This has been attributed to the difficult nature of the target environment [3,12] and has been accepted as inevitable. Therefore, most of the selection work in breeding programmes is done in favourable conditions and much research has been done to seek alternatives to empirical breeding for unfavourable conditions. Much less has been done to question whether the slow progress of empirical breeding for stress environments has been due to a wrong breeding approach.

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2.1 Challenging conventional breeding concepts

Most plant breeders assume that breeding for environments where drought (and other stresses) are unpredictable and variable is too slow and too difficult. The target is hard to define; and progress with selection is too low to achieve meaningful results. Therefore, most of the breeding for stress environments has been actually conducted using the same approach that has been very successful in areas where lack of water (and other abiotic stresses) is seldom important.

With few exceptions, most breeding programmes share the following concepts: (a) Selection has to be conducted under the well-managed conditions of research stations; (b) cultivars must be genetically homogenous (pure lines, hybrids, clones) and must be widely-adapted over large geographical areas; and (c) locally-adapted landraces must be replaced because they are low-yielding and disease-susceptible.

Breeders have very seldom questioned these assumptions. When they have, it has been found that: (a) Selection in well-managed research stations tends to produce cultivars which are superior to local landraces only under improved management - not under the low-input conditions typical of the farm- ing systems of stress environments. The result is that many new varieties are released, but few if any are actually grown by farmers in difficult environments; (b) poor farmers in stress environments tend to main- tain genetic diversity in the form of different crops, different cultivars within the same crop, and/or heterogeneous cultivars to maximize adaptation over time (stability), rather than adaptation over space. Diver- sity and heterogeneity serve to buffer the risk of total crop failure due to environmental fluctuations. This is in sharp contrast with the trend of modern breeding towards uniformity.

2.2 Breeding for stress environments

This section is largely based on the strategies and methodologies developed during the last 10 years in the ICARDA barley-breeding programme for continental areas receiving less than 300 mm rainfall. They will be described to demonstrate that it is indeed possible to improve the production of a typically low-input crop such as barley, grown in environments with low and poorly-distributed rainfall, low temperatures in winter, high temperatures and drought during grain filling, low soil-fertility and poor agronomic management.

The key aspects of these strategies and methodologies are 1) direct selection for specific adaptation in the target environment, 2) use of locally-adapted germplasm, and 3) use of plot techniques and experimental design to control environmental variation.

2.3 The environment of selection and speci$c adaptation

This has been one of hottest topics of debate among breeders during the last 30 years. The debate is between those who advocate selection in favourable environments, where genetic differences are maximized and environmental noises minimized; and those who believe that selection has to be done in the target environment or in conditions as near as possible to it. The latter are a minority among breeders but have on their side geneticists and physiologists. The theoretical framework to this issue, which in essence is a problem of Genotype by Environment (GxE) interaction, has been provided by Falconer [8], who wrote “If a breeder wants to improve performance in environment A he should select in environment A”.

GxE interaction becomes a problem to plant breeders when it is of cross-over type, i.e. it affects the ranking of breeding lines in different environments [2]. Examples of GxE interaction of cross-over type have been found in a number of crops and environments (reviewed by Ceccarelli [4], and a simplified graphical representation is given in Figure 1. The two boxes represent an example of two geographical areas with large cross-over interactions between areas and little or no interaction within areas.

There is much experimental data supporting the theoretical expectations, but there are also data which disprove it. The former are usually obtained from experiments covering a wide range of environmental conditions. Most of latter are obtained from experiments conducted in environments which lie on either one or the other side of the cross-over point, i.e. within the same box as represented in Figure 1.

Figure 1 explains why selection done on well- managed research stations is very effective in produc- ing varieties for high-input agricultural systems (they are in the same box). It also explains why the same varieties, grown on an equally well-managed station, but in a developing country where the “real” crop is grown with low inputs in stress environments, are released but not adopted by farmers. This research station, and these farmers, are in different boxes. This is implic- itly recognized when it is recommended that farmers

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0 1 2 3 4 5 8 7 8 Meana of the environments (t ha”)

Figure 1. Hypothetical GE interaction of cross-over type between experiment stations and farmers fields: A and B are typical genotypes selected in high and low yielding environments, respectively.

should use more inputs before they can benefit from breeding; in other words, that they should move to the box where breeding has been traditionally effective. But, because farmers cannot pay for the inputs and breeders do not move off the research station, each remains in his own box - and yields do not change.

When the target environments lie within the same box, the ideal cultivar is the one which performs better in all environments within the same box. When the target environments lie in different boxes, productivity is maximized by selecting specific lines for specific environments.

Figure 1 also helps in explaining some of the disagreement among breeders on the tissue of optimum environment of selection. When the target environment is a geographical area represented by the larger box in Figure 1, where expected yields range from medium to high, the discrimination between breeding lines occurs in high-yielding environments. In the lowest-yielding environments within that area, breeding lines tend to look alike; hence the low heritability which is often found. When the target environment is a geographical area which has a range of expected yields represented by the smaller box in Figure 1, the differences between genotypes are maximized at the lowest yield levels, and the identification of the best genotypes becomes increasingly difficult as yield levels increase.

When environmental variation at individual locations or groups of locations is large, and yield levels as low as 1 t ha-’ and as high as 6 t ha-’ have similar probability, the exploitation of the population buffer-

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ing of genetically-heterogeneous cultivars such as mixtures of lines may represent the best strategy to cope with an unpredictable environment (Allard and Hansche 1964). This is exactly what farmers in unpredictable environments have been always doing.

The importance of breeding for specific adaptation is not new [see for example 7, 91. Fifty years after the papers by Hayes and Engledow, Hill [lo] noted that plant breeders were still confronted with the very same problems. Seventy years later, one of the hottest debates among breeders is on very much the same issues.

2.4 The value of locally-adapted germplasm

The adapted germplasm that will be discussed in this section is represented by the landraces - also called farmer’s varieties, old cultivars or primitive cultivars. Landraces have been the starting points of breeding programs in many countries and for many crops. While landraces have been nearly completely replaced in most industrialized countries, they are still the back- bone of agricultural production in developing countries, and for crops grown in stress environments and/or by small farmers. In Syria, for example, barley production is based entirely on two landraces, Arabi Abiad (white seed) and Arabi Aswad (black seed). The first is common in slightly better environments (between 250 and 400 mm rainfall) and the second in harsher environments (less than 250 mm rainfall) - an example, perhaps, of farmers recognizing the value of specific adaptation.

We have learned anumber of lessons while working with Syrian landraces [6]. Two lessons are pertinent to this meeting. The first is illustrated by the data from two sets of yield trials, with 300 and with 280 breeding lines (Table 1). In the locations with the highest yields the yield advantage of non-landraces over landraces ranged from 0.2 to 1.6 t ha-‘. In the location with average yields below 2.0 t ha-’ the landraces outyielded the non-landraces, the only exception was Terbol1989 where they were affected by lodging. In some dry years and locations the yield advantage of landraces ranged from 38 to 83%; this suggests that they should represent the major germplasm pool in breeding for stress environment and for resource-poor farmers who cannot afford high levels of inputs.

Most breeding programmes, particularly in developing countries, conduct selection and germplasm evaluation only in environments with average yield levels similar to those of Tel Hadya in 1988 and

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Table 1. Grain yield (mean and standard error in kg ha-‘) of all breeding lines (population) tested in two sets of breeding trials, each conducted in eight year-location combinations, of Syrian landraces and of breeding lines unrelated to Syrian landraces (Nonlandraces). The number of lines in each group is in parenthesis

Location/yea?

First set KS89 B089 TR89 TH89

TH87 B088 TH88 AT89

Rainfall (mm)

234 186 344 234

358 386 504 344

Population Landraces Non landraces

(n = 300) (n=44) (n - 207) 374 f 0.8 488 f 20.4 339 f 9.9 687 f 16.3 1038 f 25.4 591 zt 16.7

1771 f 15.8 1585 f 36.1 1816 f 18.3 2667 ct 27.2 3311 f 45.9 2477 f 24.7

2876 dz 55.1 3738 f 204.9 2680 f 48.1 3205 i 44.2 3105 * 107.9 3291 zt 49.1 4532 f 46.3 4365 zt 117.3 4564 f 55.2 5824 f 59.6 4506 f 114.6 6153 f 60.3

Second set (n = 280) (n = 76) (n = 165) BR90 185 471 f 10.0 610 f 4.9 388 f 10.9 AT90 210 506 f 8.2 515 zt 4.6 493 f 11.3 B089 186 696 zt 19.1 971 & 6.4 530 f 20.3 TH90 233 789k 11.4 960 f 4.6 696 f 11.8 TH89 234 3244 f 26.6 3485 f 5.9 3072 f 32.0 TR90 317 3346 f 25.9 2956 f 5.3 3529 rfr 29.0 BR88 408 3392 f 50.6 3724 f 10.1 3307 f 67.0 TH88 504 4593 f 82.9 3611 f 16.2 5126 f 97.1

a KS - Ksabya; BO - Bouider; BR - Breda; TH - Tel Hadya (all these locations arc in northern Syria); TR - Terbol (Lebanon); AT - Athalassa (Cyprus).

Athalassa in 1989. These high-yield levels are obtained either because the station is located in a favourable area, or through agronomic management (fertilizer, weed control and irrigation), or both. The danger is not only of selecting breeding material poorly adapted to stress conditions, but of discarding germplasm which would have been specifically adapted to them.

The second lesson we learned from landraces is that landraces are genetically heterogenous [6]. An example of variability within landraces is given in Figure 2 for single-head progenies derived from two collection sites in the north-east and north of Syria. The lines from site 24 yielded more but were shorter under drought that the lines from site 21. There were also large differences within collection sites for both traits. What is less obvious is the possibility of genetic heterogeneity being the key adaptive characteristic of landraces to a stressful and unpredictable environment [I]. While we do not have experimental evidence that this is the case, we do have evidence that landraces and non-landraces differ in a number of developmental, morphological and agronomic traits. This suggests that the adaptation of Syrian landraces to the type of stress environ-

ment described earlier is probably not associated with one or a few traits, but with an adaptive complex of traits [5] which are present not necessarily in one individual plant but at population level. Short term progress can be made by selecting superior pure lines within landraces; but constructing mixtures with a number of superior, yet genetically different pure lines selected from landraces could be a safer long-term objective than pure-line breeding.

2.5 Plot techniques and experimental designs in breeding for stress environments

When genotypes are compared at increasing levels of moisture stress, small variations in soil depth and texture have increasingly large effects on plot-to-plot variability. So it becomes essential to adopt those techniques and experimental designs that can mini- mize these effects. Test sites are needed which are representative (climatically and agronomicahy) of a given target environment; and possess minimum soil variability under moisture stress. Selection for these requirements should be made one or preferably more

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30 1 I site 21 L.S.D. 10.1 cm

“24 28 32 36 40 44 48 52 56 60 (cm)

Figure 2. An example of variability within Syrian barley landraces: grain yield and plant height in Breda in 1994 (290 mm rainfall) of single-head progenies from two collection sites (site 21 is in the north-east, site 24 in the north). The number of progenies is 86 and 64 for site. 21 and 24, respectively. Ll and L2 are two local landraces (Arabi Aswad and Arabi Abiad); Arta and Zanbaka are two cultivars selected respectively for high grain yield and plant height under drought.

years in advance by inspecting farmers’ crops for uniformity.

As water stress increases, competition among genotypes for water also increases and bordering becomes critical. Many breeders assume that all plots are equally affected by the border effect and do not remove plants bordering alleys prior to harvest. However, this can introduce significant error in yield estimates, when there is strong genotype x border effect interaction. Reduction of border effects can be achieved in small- grain cereals by avoiding empty rows between adjacent plots and by planting the alleys. The resulting “dirty” alleys are not very attractive, but their effect on uniformity within the plots is remarkable. Removing the alleys can be done at heading or shortly before maturity. The control of border effects is also important in breeding nurseries, usually planted as individual rows or as two-row plots. The common practice is to leave one empty row between adjacent entries. The result is that everything we observe is border effect - with the exception, perhaps, of simply inherited characters.

Small plots should be avoided as much as possible when conducting yield trials. Missing rows also have a marked effect on performance of neighboring rows, and it is advisable to check lines for germination prior to establishing a trial in a dry site.

A series of check entries, spaced at regular inter- vals throughout unreplicated progeny trials, is essential to correct for the effects of soil variability. Plot data are expressed relative to the check, adjusted for the physical distance between the nearest check plots and the plot of interest. The check genotypes must always include the farmers’ cultivar(s), lines that are well known to the breeder; and the best lines previ- ously identified by the breeding programme. A trial should be arranged in the field to ensure that check entries will not all be on the same columns; rather, they should form a grid which will provide a visual impression of the uniformity (or the variability) of the field.

In replicated yield trials, where genotypes under test may number 200-500, improved statistical designs can lead to important increases in trial efficiency. Despite the greater efficiency of lattice designs, generalized lattices and neighbor analysis, the randomized complete block (RCB) design is still dominant, particularly where an increase in trial efficiency is most needed. The use of generalized lattice designs [ 131 combines good error control with flexibility in the num- bers of treatments required. A promising extension of this design that removes both row and column effects has been described by Patterson and Robinson [ 141. Nearest-neighbor analysis [ 1 l] have been used exten- sively in Australia to remove the effects of gradients of moisture stress within replicated and unreplicated trials.

When all these techniques are used in a site with high stress-level, environmental variability can be kept at levels comparable with those of high-input research stations.

A breeder working in stress environments must be ready for disasters. In very dry years most, perhaps all, of the plots may fail. But this will tell the breeder that he/she has no breeding material to cope with that level of stress, so he/she does not make false promises, Irrigating nurseries and trials in a very dry year to avoid a crop failure only creates the illusion of a successful breeding programme, and the opportunity to observe whether there are differences at levels of stress causing crop failures will be missed. Applying more fertilizer (and inputs in general) than the farmers only tells him what they already know. What farmers want to know is whether they can get a better crop at the level of fertilizer they can afford.

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3. Breeding methods and genetic gains in stress environments

The use of direct selection for specific adaptation in the target environment, of locally-adapted germplasm, and of plot techniques and experimental design to control environmental variation are far more important than the choice of breeding method. However, when selection is done in a stress environments, the preference should go to breeding methods which rely on evaluation of crosses before individual plant selection is made. This is because at a dry site even the small irregularities of the soil surface, such as depres- sions and bumps, can greatly affect the growth of individual plants when space-planted, thus making breeding methods such as the typical pedigree nearly useless. The value of a cross can be determined by the evaluation of a random number of families/crosses if the number of crosses is not too large. If they are, the segregating populations can be yield-tested as bulks for a number of years, and single plant selection is done only within the best crosses.

We have used this method, which is one type of bulk-pedigree method, in conjunction with the pure- line selection within landraces, to develop germplasm for the stress environments in Syria. The objective is not only or even primarily to produce cultivars, but also to develop a methodology which could be useful in other crops and/or in other types of stress environments. The procedure is as follows: a) Breeding material (pure lines from landraces,

bulks, introductions, etc.) is tested in the target environments using farmers’ agronomic practices. This involves the use of two sites in northern Syria (Breda, with long-term average rainfall of 290 mm, and Bouider, 233 mm) where the three stresses have a high occurrence. In these two sites the breeding material (including F2 bulks) is evaluated without use of fertilizers, pesticides and weed control. Concurrently, the material is evaluated at the main research station (Tel Hadya, with long-term average rainfall of 337 mm) with a level of inputs commonly used in moderately favourable areas. In all the sites, the material is evaluated under strictly rainfed conditions.

b) Grain yield is the major selection criterion. At each site and in each cropping season, only the material outyielding the best check is promoted to further testing. Other selection criteria are: early growth vigor, plant height, tillering, straw softness and disease resistance in the two driest sites, earliness,

and lodging and disease resistance in the wettest sites.

c) Breeding material is tested for at least three years, taking advantage of the large year-to-year variation in total rainfall, rainfall distribution and temperature patterns. Each year, breeding material yielding less than the check is discarded unless it possesses useful traits. In this case it is retained as parental material.

Table 2 give an example of the performance of breeding material recently developed for stress environments. Tadmor and Zanbaka were obtained from single spikes collected from the black-seeded landrace Arabi Aswad in two farmer’s fields south and north of Raqqa, in the north-east of Syria, respectively. The two lines have been under testing in farmers’ fields since 1991 and 1992, respectively, both with and without fertilizer and Table 2 summarizes the data from the area where the two cultivars are better adapted; trials were conducted without fertilizer application and under very dry conditions, as indicated by the yield levels. At yield levels below 1.5 t ha-’ Tadmor and Zanbaka have an average yield advantage of about 22 and 24% respectively. Their yield advantage over Arabi Aswad is consistent in the Raqqa province except at yield levels below 300 kg ha-‘, but less consistent in the Hassaque province. Although these two cultivars have not been released, farmers who were given small seed samples for testing in 1990 have multiplied the seed; they have sold part of their seed to their neighbors, and the area planted with these two cultivars is progressively expanding. This example show that the potential of plant breeding for stress environments has probably been grossly underestimated.

4. Conclusion

Breeding for stress environments is possible provided it is conducted with strategies and methodologies that little have in common with those used in breeding for favourable environments. Adaptation over time can be improved by breeding for specific adaptation to a given type of stress environment. This can be achieved by taking advantage of the temporal variability of stress environments, which permits exposure of the same breeding material to variable combinations of stresses over a (relatively) short period. We are aware that this is fundamentally different from the modem trend of plant breeding towards broad adaptation over space. The difference represents the contrasting interests of

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Table 2. Gram yield (kg ha-’ in 11 locations in northern Syria of Tadmor and Zanbaka (only 8 locations), two barley cultivars selected from the black-seeded syrian landrace Arabi Aswad. The data are from trials conducted in farmers’ fields without fertilizer

Year

1991

1992

1993

1994

Mean % increase over

Arabi Aswad

Location (Province)

Shurkrak (Raqqa) Al Ayouj (Raqqa) Beer Asi (Raqqa)

Bahman (Raqqa) Masadeih (Hassake)

Bahman (Raqqa) Shurkrak (Raqqa)

Balunan (Raqqa) Al Wastah (Raqqa)

Tell Hamzeh (Hassake) Al Hamar (Hassake)

Arabi Aswad

220 260 180

640 1350

792 666

360 560

812 1100

631 (78Oa)

Tadmor

130 270 170

940 1600

1176 1268

575 570

876 1000

780 23.6

Zanbaka

1100 1330

1132 916

530 650

1250 650

945 22.4

a The mean in parenthesis is calculated from the locations i in common with Zanbaka.

farmers and seed companies. Farmers are interested in cultivars which are consistently superior on their farm, regardless of how they perform at other locations or in other countries. Seed companies however, want to market as much seed of as few cultivars as possible. Breeders have been breeding, perhaps unconsciously, more for seed companies and for their personal prestige than for farmers. The two objectives coincide when selection and target environments are similar, but this approach has bypassed millions of small farmers in difficult environments.

References

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drought as a challenge for the plant breeder

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