performance of maize inbred lines and their hybrids under varying drought stress conditions in mali

International Journal of Material and Mechanical Engineering (IJMME) Volume 3 Issue 2, May 2014 www.ijm-me.org DOI: 10.14355/ijmme.2014.0302.01

Performance of Maize Inbred Lines and Their Hybrids Under Varying Drought Stress Conditions in Mali Coulibaly Mamadou Mory*1, Essie Blay2, Vernon Gracen3, The Charles4, Niaba Teme5

CRRA Sotuba maizeprogramme IER BP 262 Bamako Mali *[email protected]; [email protected]; [email protected]; [email protected]; [email protected] Received 17 September, 2013; Revised 10 November, 2013; Accepted 20 January, 2014; Published 18 May, 2014 © 2014 Science and Engineering Publishing Company Abstract

Recurrent drought is one of the major constraints to maize production in West Africa. It can be devastating if it occurs for a long period, especially during flowering. Hybrid maize varieties that are tolerant to drought are not available. Therefore, many farmers in Mali have not yet adopted hybrid maize varieties. In this study, maize inbreds and hybrids were evaluated for their tolerance to drought and the gene effects conditioning performance under both drought and no drought conditions were studied to identify hybrids tolerant to drought stress that could be released. The association of inbred root characteristics and tolerance to drought was also evaluated.

Hybrids generated from crosses between thirteen inbred lines were evaluated for drought tolerance. Seventy-eight hybrids and two checks were evaluated under water stress and non-water stress conditions across four environments during the off-season of 2010. The seventy-eight hybrids were obtained from a diallel cross of thirteen parents. The test sites included: Farako (10°50’00’’ North 6°51’0’’ West), Sotuba (12°39’47’’North 7°54’50’’ West) and Yanfolila (11°11’0’’ North 8°9’0’’). Two planting dates were used to create two different environments at Farako. The experiment consisted of a split-plot with water regime as the main plot and hybrids as the sub plots. The water regime consisted of a well watered plot where irrigation was supplied through-out the plant cycle and a drought imposed plot where irrigation was stopped 40 days after planting for 20 days. The sub-plots consisted of the 78 hybrids and checks arranged in an alpha lattice with two replications. Water stress increased anthesis-silking interval resulting in reduced grain yield. Hybrid V841-73/9071 had the lowest grain yield reduction (35.3%) due to water stress, followed by CML 505/1368 (41.9%). Line 9071 has good root weight and good root number under stress while line1368exhibited good root number, good root length and good root weight under stress. The following

Genotypes9071/CML442; CML442/TZ COMP3-C2-S2, 87036/CML442, CML505/1368, V481-73/CML442, C11O-5/9071, J-16-1/TZ COMP3-C2-S2 and CML444/87036 performed well under both well watered and water stress conditions. The inbreds 9071 and CML442 exhibited the highest frequency of appearance as parents among the best hybrids both under well watered and water stress conditions demonstrating their superior SCA with some of the other parental inbreds studied here.

Keywords

Water Stress; Diallel; Root System; Combining Ability

Introduction

Global climate change is occurring and we need to better understand its impact on ecosystems and society (Christianet al. 2006). Africa is particularly vulnerable to climatic variability as its economies are largely based on weather-sensitive agro-pastoral production systems. The devastating effects of the various prolonged droughts have demonstrated this vulnerability in the 20th century. (Christian et al. 2006).

Agriculture is the engine of the Malian economy, contributing up to 45% of the Gross Domestic Product (GDP) (EUCORD 2008a). However, the performance of the sector is subject to the fluctuating climatic conditions. Good cropping seasons are often followed by bad ones, and a year of food surplus may be followed by a year of food shortage. Mali experiences food shortage one out of 2 cropping seasons (EUCORD 2008a).

Maize is a major staple food crop in West and Central Africa (WCA), providing about 15% of the total caloric

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intake of rural and urban consumers (Badu-Apraku et al. 2011a). Recurrent drought and low-N soils severely constrain maize production in the savanna zones of WCA. Annual maize yield loss due to drought is estimated to be 15% and losses may be much higher in the marginal areas where the annual rainfall is below 500 mm and soils are sandy or shallow (Edmeades et al. 1995). Grain yield losses are greater if the stress coincides with the most drought-sensitive stages of crop growth, such as flowering and grain filling. When drought stress coincides with flowering, it can reduce grain yield by 56% and, at grain filling, by 68% (Barker 2005). Maize yield can be reduced by as much as 90% if drought stress occurs between a few days before tassel emergence and the beginning of grain filling (Ne Smith and Ritchie, 1992). Yield reduction of 62% relative to the well-watered treatments occurred under induced moisture stress from about tassel-emergence to the end of the crop cycle of maize (Badu-Apraku et al., 2005).

The average maize grain yield in Mali is low (2 tha-1). Although many major constraints contribute to this low yield (poor soil fertility, drought, Striga, insects and diseases), drought accounts for more yield loss than any other stress factor (Badu-Apraku et al. 2005). An evaluation of hybrids demonstrated the positive impact of drought tolerant hybrids to about 200 Malian smallholder farmers in 2008 (EUCORD 2008). The vast majority of the farmers preferred hybrids because of their good quality of the seed, superior rates of germination, drought tolerance, and grain yield (EUCORD 2008). The development of high yielding hybrids tolerant to drought would increase grain production for resource poor farmers throughout the country.

Materials and Methods

Materials

1) Soil

Experiments were conducted at three sites, Sotuba, Yanfolila, Farako. Soil samples were taken at each site. Sample depths were 0-25 cm and 25-40 cm. Two samples were taken for each depth. All samples were analyzed at the Sotuba Laboratoire “Sol Eau Plante “(LSEP) for the determination soil texture and water holding capacity as follows

Water holding capacity = (PF3 – PF4.2) x e x da where: da =: density. Clay density = 1.2 and sand density = 1.4PF3 = Wilting point 3 PF4.2 = wilting point 4.2e = Soil thickness (sample depth)

2) Irrigation

Drip irrigation was used at Sotuba while trickle irrigation was used at Farako and Yanfolila. At Sotuba, drip irrigation pipes were installed between two rows, and the plot was irrigated every two days. The amount of water per irrigation was estimated at 300 m3 with a water meter. At Farako and Yanfolila, trickle irrigation (gravity irrigation using plastic pipes) and surface irrigation was used, respectively. The frequency of irrigation was two times per week for one hour and thirty minutes.

3) Plant Materials

Six of the thirteen lines used in this study originated from CIMMYT Zimbabwe, 5 lines were obtained from IITA and 2 lines were obtained from IRAD, Cameroon through the WACCI breeding programme (Table 1).The lines include of 9071 which is a temperate line, N28, converted to tropical adaptation, 87036 which is a mid altitude adapted line, and Tuxpeño derived lines such as P43SRC9F5100-1-8, Ku1403X1368, and 1368.

TABLE 1. INBRED LINES PARENT, THEIR NAME, PEDIGREE AND ORIGIN

N° NAME CODE NAME PEDIGREE ORIGIN

1 CML 444 C 135-31 CML 444-B CIMMYT (ZIMBABWE)

2 CML 505 351 1/6

[ENT320:92SEW2-77/[DMRESR-

W]EARLYSEL#1-2-4-B/CML386]-B-11-3-B-2-#-B*4

CIMMYT (ZIMBABWE)

3 P43SRC9FS100-1--

8

SAMI 09A3314

P43SRC9FS100-1-1-8#1-B1-13-B1-B-B-B-B-B TUXPEÑO

BACKGROUND IITA IBADAN

4 EXP1 24 EXP1 24 BULSR/TZB WACCI(IRAD CAMEROON)

5 C110-55 C110-55

[TS6CIF238-1-3-3-1-2-#-BB/[EV7992#/EV8449-

SR]CIF2-334-1(OSUI)-10-7(1)-X-X-X-2-BB-1]-1-1-2-1-

1-B*6

CIMMYT (ZIMBABWE)

6 87036 87036 TZMSR/BULSRMID ALTITUDE LINE

WACCI(IRAD CAMEROON)

7 J-16-1 J-16-1 ZM523-16-2-1-1-B*4 CIMMYT (ZIMBABWE)

8 V481-73 CZLO718 [SC/CML204//FR812]-X-30-2-3-2-1-BBB

CIMMYT (ZIMBABWE)

9 1368 TZL4 POP 21 SRTUXPEÑO BACKGROUND WACCI(IITA)

10 9071 TZL 25 N 28 CONVERTED WACCI(IITA)

11 CML442 316-7 CML442-B CIMMYT ZIMBABWE

12 TZL-

COMP3-C2-S2

SAMI 09A3337

TZL-COMP3-C2-S2-34-4-1-2-B-B-B-B-B-B IITA (IBADAN)

13 (KU1403X1368)-

SAMI 09A3310

(KU1403X1368)-7-2-1-1-B-BTUXPEÑO

BACKGROUND IITA (IBADAN)

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International Journal of Material and Mechanical Engineering (IJMME) Volume 3 Issue 2, May 2014 www.ijm-me.org

Methods

1) Study of Root Characteristics of the inbreds (Pot experiment)

Each inbred was planted in six pots, and subjected to two different water regimes (water stress and no stress). The pot diameter was 28 cm with a depth of 18 cm. Potting medium was 50% sand and 50% clay. One liter of water was applied per pot every 2 days. For three pots, water was withheld 15 days after planting for 15 days to create water stress. The remaining 3 pots were watered throughout the experiment. Data were collected on 3 plants for each genotype. Root system and other data for the two water regimes were taken just after the 15 days water stress. Characteristics including number of lateral roots, root length, root weight, leaf weight, and leaf length were evaluated.

2) F1 Hybrids Evaluation

The seventy-eight hybrids from diallel crosses among the thirteen inbred lines described above and two (2) checks (1 OPV and 1 hybrid) were evaluated. Seed of direct and reciprocal crosses were bulked to increase the quantity of F1 seed to be evaluated.

3) Experimental Sites

Three sites were used for F1 evaluation. These were Sotuba (12°39’47’’North 7°54’50’’ West), in central Mali, Farako (10°50’00’’ North 6°51’0’’ West) in southern Mali and Yanfolila (11°11’0’’ North 8°9’0’’ West) in southwestern Mali. Sotuba and Farako are Regional Centers for Agronomic Research (CRRA). The trial at Yanfolila, situated in Sikasso CRRA was conducted in cooperation with a local farmer.

4) Experimental Conditions

The experimental sites were plowed with a tractor. The trials were hand planted. The experimental unit consisted of a one row/plot, 5m long and 0.80m between rows. Fertilization consisted of two applications. The first application was done at emergence with 18 % of nitrogen, 46 % of P205. The second application, 15 days after the first one, was 50 kgha-1 of urea.

5) Experimental Design

The experiment was a split plot design. The main plot was water regime and the sub plots were hybrids. Two water regimes were used, irrigation throughout the growing season, and a “drought

plot” where irrigation was stopped 40 days after planting for 20 days. The sub-plots consisted of genotypes arranged in alpha lattice with 2 replications.

At Farako, two planting dates were used in order to increase the number of testing environments.

6) Data Collected

Data collected consisted of:

- Number of days from planting to 50% anthesis, and 50% silking and ASI was calculated -Ear weight consisting of the weight of all ears of the plot.

Grain yield was estimated using the following formula:

Grain yield (Kg ha-1) = fresh ear weight (kg plot-1) x (100-MC) x 0.8 x 10000/ (100-15) x Area harvested plot1

Where:

MC = moisture content of grain at harvest (%)0.8 = Shelling percentage1 hectare = 10.000 m2

Statistical Analysis

Individual analyses of variance were conducted for each trial using the general Linear Mixed models: REML (Restricted Maximum Likelihood) from GENSAT with genotypes (hybrids) being considered as fixed effects, and repetitions and blocks within repetitions as random effects.

The model used was: yijk= µ + ρk + αi + dik+ βj + αβij + eijk.

yijk = Observation corresponding to ith level of main plot treatment; jth level of small plot treatment and kth block i= 1…2; j= 1…80; k= 1…2µ= The Overall mean for all experiments ρk= random effect of the kth block αi= the effect of the ith level of treatment, the whole unit treatment; a fixed effect dik=interaction of the ith treatment with kth block βj= Effect of the jth level of the subunit treatment; a fixed effect αβij= Effect of interaction between whole plot unit treatment i and subunit treatment j eijk= Residual effect

Results

Soil Analysis

Soil analysis (See appendix1) shows that Farako soil

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texture varied from silt clay sand to sand silt or silt sand. The average water holding capacity was 12.1 mm. At Sotuba, soil texture varied from silt sand to silt clay sand and water holding capacity was around 13.5 mm. Silt fine clay was dominant in Yanfolila and the average water holding capacity was about 22 mm. Water holding capacity differences were influenced by soil texture. It was noted that as the percentage of silt clay increased, the water holding capacity increased. Therefore, it was expected that Yanfolila, with better water holding capacity, would experience less drought stress.

Roots and Leaf Characteristics of the Parents in the Pots

1) ANOVA

The lines responded similarly to both moisture regimes except for root weight (Table 2). This was evidenced by the non-significant interaction effects obtained between moisture regime and genotypes (inbreds). Therefore the inbred lines exhibited similar ranking from one moisture regime to another for all tested characteristics except for root weight.

TABLE 2. MEAN SQUARES FROM ANALYSIS OF VARIANCE FOR SOME INBRED PLANT CHARACTERISTICS UNDER THE TWO MOISTURE REGIMES,

SOTUBA OFFSEASON NOVEMBER 2010

Source of variation d.f Leaf

number leaf

weight roots

length roots

number roots

weight Rep 2 25.077 69.36 25.70 34.82 31.449

Moisture regime 1 153.721 6273.35** 1822.17* 2578.88** 1333.223**

Genotypes (lines) 12 8.986* 81.30 NS 84.00** 157.70** 18.798**

Residual 2 34.731 22.73 101.20 13.42 23.198 Moisture regime x

line 12 5.638 NS 65.40 NS 33.28 NS 31.68 NS 13.747*

Residual 48 3.959 62.89 20.14 24.19 7.161 Total 77

However, significant differences were obtained among the 13 inbreds for all characteristics except for leaf weight. The effect of the 2 moisture regimes was also significant for all measured traits except for leaf number.

2) Root Weight

With no stress, the highest root weights were obtained for 9071, EXP1 24, 87036, (KU1403X1368), CML444 and CML 505 (Table 3). When lines were subjected to drought, the best root weights were obtained with 87036, 9071, KU1403X1368, 1368, J-16-1 and TZ-COMP3-C2-S2. Inbred lines which had

highest root weights under both conditions included: 87036, 9071, and (KU1403X1368). In addition, lines that exhibited the least root weight reduction due to drought were TZ-COMP3-C2-S2, 1368, 87036, P43SRC9FS100-1-1-8, J-16-1, and KU1403X1368.

TABLE 3. DROUGHT EFFECTS ON SOME ROOT CHARACTERISTICS OF THE 13 INBRED LINES NOVEMBER 2010

Lines

Roots weight Roots number Roots length No

stress water

stress water

reduction

%

No stress water

stress water

reduction%

No stress water

Stress water

Reduction

% CML 444 11.47 1 91 29.83 15.33 49 27.83 17.33 38

CML 505 11.23 0.6 95 20.83 8.33 60 21.83 9.83 55

P43SRC9FS100-1-

1-8 6.7 1 85 28 15.5 45 27.67 15.17 45

EXP1 24 13.13 1 92 26 12.17 53 18.17 12.67 30 C11O-5 4.23 0.47 89 17.33 6.83 61 20.17 7.67 62 87036 11.84 1.73 85 19.33 9.83 49 17.67 9.17 48 J-16-1 8.57 1.2 86 16.67 11 34 19.33 15.33 21

V481-73 8.2 0.53 94 15.17 3.17 79 19 5.33 72 1368 8.87 1.4 84 22 16.5 25 18 15.83 12 9071 14.47 1.63 89 37.83 14.33 62 31.33 12 62

CML442 4.72 0.57 88 16.5 4.17 75 19.17 8 58 TZ-

COMP3-C2-S2

6.17 1.2 81 24.33 15.67 36 19.5 14.83 24

(KU1403X1368) 11.83 1.6 86 24.33 15.83 35 27.5 18.33 33

MEAN 9.34 1.07 88.54 22.94 11.44 50.13 22.09 12.42 43.77

3) Root Number

With no water stress, 9071, CML444, P43SRC9FS100-1-1-8, EXP1 24, TZ-COMP3-C2-S2 and KU1403X1368 had the highest root number (Table 3). Under water stress, the best lines were 1368, KU1403X1368, TZ-COMP3-C2-S2, P43SRC9FS100-1-1-8, CML444 and 9071. Inbred lines TZ-COMP3-C2-S2, P43SRC9FS100-1-1-8, CML444, and 9071 performed well under both conditions. Lines with the lowest percent of root number reduction due to drought were 1368, J-16-1, KU1403X1368, TZ-COMP3-C2-S2, P43SRC9FS100-1-1-8, 87036 and CML444.

4) Root Length

Under stress, inbred lines with longest root length included: KU1403X1368, CML444, 1368, P43SRC9FS100-1-1-8, J-16-1, TZ comp3-C2-S2, and EXP1 24 ( Table 3).Under no water stress, inbred lines with the longest root length were: 9071, CML444, P43SRC9FS100-1-1-8, KU1403X1368, CML505, C-110-5 and TZ comp3-C2-S2.Inbred lines which performed well under both conditions

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included KU1403X1368, P43SRC9FS100-1-1-8, TZ comp3-C2-S2, and CML444.

In general drought caused significant reduction in root weight, root number and root length compared to non stress conditions. Root weight reduction ranged from 81% for TZ-COMP3-C2-S2 to 95% for CML 505. Root number reduction ranged from 25% for 1368 to 79% for V481-73. Root length reduction was 12% for 1368 and 72% for V481-73 (Table4). . Line 87036 had the best root weight followed by 9071; inbreds 1368 and KU14013 X 1368 were the best for root number, KU14013 X 1368 and CML444 for root length.

TABLE 4. SUMMARY OF THE RANKING OF ROOT CHARACTERISTICS OF THE GENOTYPE UNDER DROUGHT STRESS

Ranking Genotype Names

Root Weight Root Number Root length 1 87036 1368 (KU1403X1368) 2 9071 (KU1403X1368) CML444 3 (KU1403X1368) TZ-COMP3-C2-S2 1368

4 1368 P43SRC9FS100-1-1-8 J-16-1

5 J-16-1 CML444 P43SRC9FS100-1-1-8

6 TZ-COMP3-C2-S2 9071 TZ-COMP3-C2-S2

7 CML444 EXP1 24 EXP1 24 8 P43SRC9FS100-1-1-8 J-16-1 9071 9 EXP1 24 87036 CML505

10 CML505 CML505 87036 11 CML442 C11O-5 CML442 12 V481-73 CML442 C11O-5 13 C11O-5 V481-73 V481-73

Hybrid Performance

1) ANOVA

TABLE 5 MEAN SQUARE FROM THE ANALYSIS OF VARIANCE ACROSS STRESS AND NON- STRESS ENVIRONMENTS FOR GRAIN YIELD

Source Df Across

environment Water stress

No water stress

Rep 1 0.24 ns 2.4 ns 0.59 ns Water/stress 1 1351.93*

Entry 79 3.893** 1.16** 3.77** Water.entry 79 3.893**

Water.entry.site 3 282.645** Residual 949 (8) 1.695

Total 1271 (8) Means(t ha-1) 2.56 1.52 3.58

Lsd 0.76 0.87 1.36 Cv% 21.4 58.3 38.6

The Analysis of variance performed by moisture regime (stress and no stress) across all tested environments (Yanfolila, Sotuba Farako1 and Farako2) for all measured characteristics is shown on (Table 5). No significant environment x

genotype interactions were detected. Therefore all entries had the same relative performance from one environment to another. The effect of the water regime was highly significant indicating that the drought created was high enough to discriminate among hybrids across the two water regimes.

At Sotuba, the mean yield of the hybrids ranged from 1.6 tha-1to 3.5 tha-1 under water stress and no stress conditions, respectively (Table6), and the average yield reduction due to drought was 53.22%.

At Farako 1, the mean yield of the hybrids ranged from 2.8 tha-1 for non-water stress conditions to 1.7 tha-1 under drought stress conditions. The average grain yield reduction due to drought stress was 38.18%. In Farako 2, grain yield ranged from 2.4 tha-1 to 0.72 tha-1 for non-stress and stress conditions, respectively. The percent grain yield reduction due to water stress was 69.63%.

At Yanfolila, the mean yield of the hybrids ranged from 5.6 tha-1 to 2.0 tha-1 for non- stress and drought stress conditions, respectively. The percent grain yield reduction was 64.12%.

The least grain yield reduction was obtained at Farako 1(39.18%) while at Farako 2, drought stress was high resulting in 69.63% grain yield reduction. The highest mean grain yield under water stress was obtained at Yanfolila, 2.0 tha-1. This was probably due to the soil type which had the highest water holding capacity.

TABLE 6. GRAIN YIELD MEAN PER SITE AND PER WATER REGIME

Sites Sotuba Farako1 Farako2 Yanfolila Means No Water

Stress 3.478 2.838 2.378 5.617 3.57

Drought Stress

1.627 1.726 0.722 2.015 1.52

% Yield Reduction

53.22 39.18 69.63 64.12 56.51

Under drought conditions across all environments, grain yield of the different genotypes (entries) varied from 2.5 tha-1 (CML505/1368) to 0.69 tha-

1(EXP1 24/TZL COMP-C2-S2) Appendix 2

The best 20% of the genotypes under drought stress, (Table7) showed variation in grain yield from 2.5 tha-1 for CML 505/1368 to 1.8 tha-1for EXP124/C110-5. Thirteen (13) hybrids yielded more than 1.9 tha-1. All yielded more than 1.8. The OPV had less reduction due to drought but the yield was very low, 1.0 tha-1. The hybrid check yielded 3.5 and 1.5 under non-stressed and stress conditions. When comparing the performance of the top 20%

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genotypes under water stress to their corresponding performance under well-watered conditions, all hybrids among the 20% top showed grain yield loss equal or less than 57.2% due to drought. The hybrids 9071/CML442, CML442/TZ, 87036/CML442 and CML444/87036 had the best yields in well watered and very good yields under stress. The hybrid with the least grain yield reduction was V481-73/9071 (35.2%) but its yield with no stress was marginal. It was followed by CML 505/1368 (41.9 %) which ranked 8th out of 16 for non stress yield. The hybrid inbred line 1368 exhibited good root number, good root length and good root weight under stress. The second best

yielding hybrid under drought was V481-73/9071. Inbred 9071was selected for its good root weight and good root number under stress. Inbreds 9071 and CML442 appeared 5 and 4 times each among best hybrids (top 20%) (Figure1). This gives an indication of their superior combining ability under drought conditions. CM442 had good combining ability under drought and well-watered conditions but did not rank well for any root traits. Inbred lines 9071, CML505, 87036 and TZL Comp3-C2-S2 seemed to contribute drought tolerance in a range of crosses with CML442, CML444, and 1368 related lines but did not combine well with EXPL24, P43SR, J16-1under drought.

FIG1. FREQUENCY OF APPEARANCE OF INBRED LINES AMONG THE TOP TWENTY HIGH YIELDING UNDER WATER STRESS CONDITIONS

Under well-watered conditions across all environments, grain yield varied from 4.84 tha-

1(9071/CML442) to 1.42 tha-1(Dembanyuma, the OP check) (Appendix 3). The 20% best genotypes under well-watered conditions (Table 8) had variation in grain yield from 4.8 tha-1for 9071/CML442 to 4.3 tha-1for CML505/1368. All of the 20% best hybrids yielded more than 4Tha-1. While the hybrid check yielded 3.5 and the OP variety yielded 1.4. When comparing the performance of the top 20% genotypes under well-watered condition to their corresponding performance under drought stress conditions, all hybrids showed grain yield reductions of less than or equal to 75% due to drought but 2 had reduction of less than or equal to 65%. The hybrid with the

least grain yield reduction was CML505/1368 (41.9%) (Table 8) which also ranked as the best yielding genotype under drought stress (Table 7) but was number 16 out of 16 in yield under no stress at 4.3t/ha. Only 2 hybrids exhibited grain yield reduction of less than 50%. These were CML505/1368 (41.91%) and J-16-1/TZ COMP3- C2-S2 (48.72%) which were two of the three lowest yielding hybrids in the top 20% under well-watered conditions.

When comparing hybrid performance in the 2 water regimes, 2 hybrids were superior under drought and under no water stress. These were: 9071/CML442, CML442/TZ COMP3-C2-S2. These hybrids are recommended for further testing

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Inbred 9071 appeared in 5 crosses on the best 20% of hybrids under well-watered conditions (Figure2). This gives an indication of its general combining ability under non-water stress condition. Inbred lines CML 442 and 87036 appeared in 4 crosses each and CML 505, V481-73, and 1368 appeared 3 times each. Inbred lines 9071, CML442, 87036, and CML 505 showed superior combinability with certain lines in well-watered tests. These lines made up at least one parent in 11 of the best 12 hybrids in well-watered conditions with all 11 yielding 4.3 tha-1 and above.

TABLE 7.GRAIN YIELD OF THE TOP 20 % OF HYBRIDS UNDER DROUGHT STRESS AND THEIR CORRESPONDING PERFORMANCE UNDER NO STRESS

RANK HYBRIDS

YIELD UNDER WATER STRESS

CONDITIONSTHA-1

YIELD UNDER WELL

WATERED CONDITIONS

THA-1

REDUCTION IN GRAIN

YIELD (%)

1 CML505/1368 2.45 4.22 41.9

2 V481-73/9071 2.25 3.48 35.32

3 87036/CML442 2.20 4.56 51.58

4 J-16-1/TZ-COMP3-C2-S2 2.17 4.24 48.72

5 9071/CML442 2.16 4.84 55.31

6 87036/ TZ-COMP3-C2-S2 2.08 4.22 50.49

7 CML505/CML442 2.07 4.12 49.7

8 CML505X/9071 2.07 3.78 45.33

9 CML442/ TZ-COMP3-C2-S2 2.05 4.76 56.89

10 P43SRC9FS100-1-1-8/C11O-5 2.01 3.64 44.73

11 CML505/EXP1 24 1.97 3.99 50.57

12 CML444/87036 1.95 4.49 56.52

13 9071/(KU1403/1368) 1.90 3.90 51.29

14 C11O-5/9071 1.89 4.41 57.20

15 V481-73/CML442 1.88 4.38 57.08

16 EXP1 24/C11O-5 1.84 3.50 47.37

CHECK HYBRID 1.51 3.50 57.18

OPV 1.01 1.42 28

MEANS 1.52 3.58

MAXIMUM 2.42 4.84

MINIMUM 0.68 1.42

LSD 0.87 1.36

CV% 58.3 38.6

TABLE 8.GRAIN YIELD OF THE TOP 20 % GENOTYPE UNDER WELL WATERED AND THEIR CORRESPONDING PERFORMANCE

UNDER WATER STRESS

RANK

HYBRIDS

YIELD UNDER WELL

WATERED CONDITIO

NS tha-1

YIELD UNDER WATER STRESS

CONDITIONS tha-1

REDUCTION

IN GRAIN YIELD

(%) 1 9071/CML442 4.84 2.16 55.31

2 CML442/TZ-

COMP3-C2-S2 4.76 2.05 56.89

3 P43SRC9FS100-1-

1-8/87036 4.64 1.15 75.03

4 87036/CML442 4.56 2.20 51.58 5 CML444/87036 4.49 1.95 56.52 6 V481-73/1368 4.46 1.46 67.19

7 P43SRC9FS100-1-

1-8/9071 4.44 1.52 65.69

8 C11O-5/9071 4.41 1.89 57.20 9 V481-73/CML442 4.38 1.88 57.08

10 1368/9071 4.33 1.67 61.45 11 CML505/V481-73 4.30 1.51 64.86

12 CML505/KU1403X

1368 4.28 1.68 60.70

13 C11O-5/J-16-1 4.27 1.68 60.66

14 J-16-1/TZ-COMP3-

C2-S2 4.24 2.17 48.72

15 87036/9071 4.24 1.72 59.33 16 CML505/1368 4.22 2.45 41.91 CHECK HYBRID 3.5 1.51 57.18 OPV 1.42 1.01 28 MEANS 3.5 1.5 MAXIMUN 4.8 2.4 MINIMUM 1.42 0.68 LSD 1.36 0.78

2) Anthesis Silking Interval (ASI)

Among all crosses, V481-73/CML442, CML505/CML442, V481-73/9071 and 87036XCML442 had anthesis-silking interval values of 2; 4; 3; 2, respectively, and the highest grain yield (3 tones) for water stressed trials at Sotuba while 87036/(KU1403X1368), 9071/CML442 and J-16-1/9071 had anthesis-silking interval values 4; 7; 4 with the corresponding lowest grain yield of 1.9; at Farako 2. Water stress increased Anthesis-silking interval resulting in reduced grain yield (Figures3 and 4).

Anthesis-Silking Interval correlated negatively with grain yield under drought stress. As anthesis-silking interval increased, grain yield decreased at Sotuba 2 and Farako 2 Figure 5 and 6.

23


FIG2. FREQUENCY OF INBRED LINES APPEARANCE AMONG THE TOP TWENTY PERCENT HIGH YIELDING HYBRIDS UNDER WELL-

WATERED CONDITIONS

FIG3. HYBRIDS ANTHESIS-SILKING INTERVAL AT SOTUBA NOVEMBER OFFSEASON 2010

FIG4. HYBRIDS ANTHESIS-SILKING INTERVAL AT FARAKO NOVEMBER OFFSEASON 2010

24


FIG 5 CORRELATION BETWEEN GRAIN YIELD AND ANTHESISSILKING INTERVAL AT SOTUBA 2

FIG 6 CORRELATION BETWEEN GRAIN YIELD AND ANTHESISSILKING INTERVAL AT FARAKO 2

3) Combining Ability

GCA and SCA are important for the evaluation of an inbred line in the production of hybrid maize. These represent the characteristics of the line itself and the behavior of the line in particular hybrid combinations.

4) General Combining Ability (GCA)

The GCA of the lines under drought and no drought are presented in Table 9. Under drought stress, 6 lines exhibited positive GCA values. These included: 9071 (0.25), CML505 (0.07), TZ COMP3-C2-S2 (0.05), CML442 (0.04) 87036 (0.039) and J-16-1 (0.03). Under well-watered conditions, 7 lines showed positive GCA. These included 9071 (0.37), CML 442 (0.17), 87036 (0.16), V481-73 (0.10), 1368

(0.051) CML 444(0.05) and TZ COMP3-C2-S2 (0; 04). Four lines had positive GCA both under drought stress and non-drought stress conditions. These were: 9071, TZ COMP3-C2-S2, CML442, and 87036.

5) Specific Combining Ability (SCA)

Under water stressed conditions, the largest positive SCA was obtained with CML505/1368 which yielded well,2.5 tha-1, while under well watered conditions, the largest positive SCA was observed with CML505/(KU1403 X 1368) which had mediocre yield, 4.3 tha-1 ( Table 10)

Under drought stress, the best specific combiners were: CML505/1368, at 2.5 tha-1,P43SRC9F5-100-1-1-8/C110-5 at 2.0 tha-1, 87036/CML442 at 2.2 tha-1 and J-16-1/TZ COMP3-C2-S2 at 2.2 tha-1 Under non

25


stress conditions, the best specific combiners were CML505/ (KU1403 X 1368) with 4.3 tha-1, CML442/ TZ COMP3-C2-S2 with 4.8 tha-1, P43SRC9F5-100-1-1-8/87036 with 4.6 tha-1and C110-5/J-16-with 4.3 tha-

1. The best specific combiners under drought as estimated here were completely different from the best specific combiners under no water stress. The best specific combiner under drought, ranked 13th under no water stress, also the best specific combiner under no water stress was not among the best 20% hybrid under drought stress conditions. The hybrids 9071/CML442 and 87036/CML442

yielded 4.8tha-1 and 4.6tha-1 under no drought stress, respectively, and 2.2 tha-1 and 2.2 tha-1 under drought stress, respectively, demonstrating that they exhibited superior SCA even though the estimates did not identify this. Under drought, no other hybrid yielded more than the 2 above. In addition, the lines involved in these crosses, namely 9071, CML442, and 87036, were good combiners across the two drought gradients. It would be advisable that these two hybrids are released to farmers.

Discussion

An important objective of the present study was to examine the combining abilities of 13 inbred lines tolerant to drought under both water stressed and non-stressed environments. CML442 could be considered as a superior tester under drought and well-watered conditions and 9071 could be a tester under drought conditions. These two lines produced the highest number of superior hybrids under well-watered and water-stressed conditions. In addition, CML505 and 87036 might also be adequate testers under drought and well-watered conditions based on their GCA estimates. The best hybrids, under well-watered conditions across all test environments, were 9071/CML442 (4.84 tha-1), and CML442/TZ-COMP3-C2-S2 (4.76 tha-1). CML505/1368(2.45 tha-1) was the best hybrid under drought stress conditions across all test environments.

Drought effects were severe in soils where soil water holding capacity was low. The relative soil water holding capacities in the study areas were Yafolila>Sotuba>Farako. The hybrid with highest overall grain yield under well-watered conditions at Yanfolila was (KU1403X1368)/CML505 (8.6 tha-1) and the overall lowest yield was 0.50 tha-1 for P43SRC9FS100-1-1-8/CML442 at Farako 2. Under water-stressed conditions, the best hybrid was C110-5/EXP1 24 (3.9 tha-1) at Yanfolila and the lowest yield (0 tha-1) was recorded with P43SRC9FS100-1-1-8/1368 at Farako 2. Soil texture clearly influenced water holding capacity and affected the ability to withstand drought. This result agrees with Alastair et al. (2001) who reported that medium to fine-textured soils and those with a good aggregate structure, tend to hold more water for plant use than coarse-textured and poorly structured soils. Yanfolia (Silt fine clay) which has the best water holding capacity had the highest grain yields..

TABLE 9. GENERAL COMBINING ABILITY OF THE LINES, UNDER DROUGHT STRESS AND UNDER NORMAL CONDITION

LINES GCA OF THE LINES UNDER DROUGHT

GCA OF THE LINES UNDER NO

DROUGHT STRESS 1368 -0.05 0.051

CML442 0.04 0.17 9071 0.25 0.37

(KU1403X1368) 0 -0.33 TZ COMP3-C2-S2 0.05 0.04

CML 505 0.07 -0.08 C110-5 -0.07 -0.17

EXP1 24 -0.12 -0.29 J-16-1 0.03 -0.04

P43SRC9FS100-1-1-8 -0.16 -0.02 87036 0.039 0.16

V481-73 -0.05 0.1 CML444 -0.04 0.05

TABLE 10. SPECIFIC COMBINING ABILITY OF THE LINES UNDER DROUGHT STRESS AND UNDER NORMAL CONDITION

Best 16 positive F1

SCA of the lines

under drought

Hybrids Top 20% under no drought

SCA of the lines under no drought

CML505/1368 0.91 CML505/KU1403X1368 0.99 P43SRC9FS100-1-1-

8/C11O-5 0.72 CML442/TZ-COMP3-C2-S2 0.96

87036/CML442 0.61 P43SRC9FS100-1-1-8/87036 0.91

J-16-1/TZ-COMP3-C2-S2 0.61 C11O-5/J-16-1 0.88

V481-73/9071 0.53 CML505/EXP1 24 0.76 EXP1 24/C11O-5 0.51 V481-73/1368 0.72 CML505/EXP1 24 0.5 87036/CML442 0.71 C110-5/EXP1 24 0.5 9071/CML442 0.7

87036/ TZ-COMP3-C2-S2

0.48 CML505/V481-73 0.69

CML444/87036 0.44 CML444/87036 0.68 CML505/CML442 0.44 CML505/C110-5 0.67

CML442/ TZ-COMP3-C2-S2 0.44 J-16-1/TZ-COMP3-C2-S2 0.65

P43SRC9FS100-1-1-8/V481-73 0.44 1368/CML505 0.65

CML442/V481-73 0.37 C11O-5/9071 0.6 9071/CML442 0.35 V481-73/CML442 0.53

(KU1403/1368)/J-16-1 0.32 (KU1403X1368)/C110-5 0.53

26


The grain yield of the 20% best genotypes under drought across all environments varied from 2.5 tha-1

(CML505/1368) to 1.8 tha-1(EXP1 24/C110-5). The performance of the top 20% genotypes under drought compared to their corresponding performance under well watered condition revealed that the highest grain yield reduction was 57.2% (C110-5/9071) which is close to 60% reported in severe drought conditions (Zaidiet al 2004) and the lowest grain yield reduction was 35.3% (V481-73/9071).

Under well-watered conditions, the grain yield of the 20% best genotypes across all environments varied from 4.8 tha-1for 9071/CML442 to 4.2 tha-1for CML505/1368. The performance of genotypes compared to their corresponding performance under drought showed that the highest grain yield reduction due to drought was observed with P43SRC9FS100-1-1-8/87036(75.03%) and the lowest was observed with CML505/1368 (41.91%).

Out of the 16 highest yielding hybrids under water stress conditions, eight are also among the top 20 yielding hybrids under well-watered conditions. These are 9071/CML442, CML442/ TZCOMP3-C2-S2, 87036/CML442, CML505/1368, V841-73/CML442, C11O-5/9071, J-16-1/TZCOMP3-C2-S2 and CML444/87036. CML442 appears to be an excellent parent and combines well with 9071, V841-73 and 87036 but not with P43SR, C110-5 or EXOL24.

Yield reduction under drought represents the relative stability of hybrids from well-watered to drought conditions. Yield reduction under drought should be considered together with grain yield potential of individual hybrids grown both under stress and non-stress conditions. Certain hybrids may have high yield reduction but low yield potential. Grain yield under drought and drought reduction must be taken into consideration as criteria in screening for drought resistance (Philipp, 1996).

The largest positive and negative SCA effects were observed with (KU1403X1368)/CML 505 and CML 505/87036 hybrid, respectively, across all well-watered environments. In the water stressed condition, the largest positive and negative SCA effects were observed with 1368/CML 505 and 87036/CML 505, respectively.

Among all crosses, V481-73XCML442; CML505XCML442; V481-73X9071; and 87036XCML442 had highest yield (3 tones) with ASI values of 2; 4; 3; 2, respectively, for water stressed trials at Sotuba while

87036/(KU1403X1368); 9071XCML442; and J-16-1X9071 had highest yield (1ton) with ASI values of 4; 7; 4 ,respectively, at Farako 2. Water stress increased ASI resulting in reduced grain yield. Badu-Apraku and Oyekunle (2012) reported similar reduction in grain yield under drought stress caused by increased Anthesis-Silking Interval.

The heritability in broad sense observed for the hybrids in the water stressed conditions over four sites was 33%. This heritability is low. Philipp (1996) reported that breeding to improve genotypes for drought stress by selecting solely for grain yield is difficult because heritability for yield is low under variable environments. Thus, determining morphological and physiological characters associated with drought resistance as selection criteria would be very important.

Conclusions

Drought effects were severe where soil water holding capacity was low. The rank of water holding capacity was Yanfolila>Sotuba>Farako. Soil texture influences water holding capacity and helps plants to withstand during drought periods. This was observed at Yanfolila which had the best water holding capacity with the highest grain yields.

The best hybrids under well-watered conditions across all test environments were 9071/CML442 (4.84 tha-1), and CML442/TZ COMP3-C2-S2 (4.76 tha-1). CML505/1368(2.45 tha-1), V841-73/CML442 (2.25 tha-1) and 87036/CML442 (2.20 tha-1) were the best hybrids under drought stress conditions across all test environments.

The genotypes 9071/CML442, CML442/TZ COMP3-C2-S2, 87036/CML442, CML505/1368, V841-73/CML442, C11O-5/9071, J-16-1/TZ COMP3-C2-S2 and CML444/87036 were the best both under well-watered and water-stressed conditions. The lowest grain yield reduction due to drought was 41.91% withCML505/1368. Inbred lines 9071 and CML442 produced the largest number of superior hybrids under both well-watered and water-stress conditions. They could be used in a breeding program to produce very useful hybrids or generate new inbred lines for use in Mali or similar environments.

ACKNOWLEDGEMENT

The success of this research project was a result many minds and organizations that were both aligned and

27


allied for a common purpose. I thank AGRA (Alliance for green revolution in Africa which provided the study grant through West Africa Center for Crop Improvement (WACCI). I am grateful to WACCI for identifying me as potential doctoral candidate and offering me the much coveted WACCI scholarship. I thank CIMMYT Zimbabwe, IITA Ibadan and IRAD Cameroon Research Institute for providing the germplasm used in the study. The interlibrary loan facility of the Alfred Mann library of Cornell University (USA) allowed me to access numerous publications and volumes of literature relevant to my study area. I would like to acknowledge Dr. The Charles, PrE. Blay, Pr Vern Gracen, and Pr Eric Danquah for their guidance from the project conception phase to the finish line. Dr. Joe Devries suggested that I work on maize instead of sorghum. In working with maize, Dr. Charles. The supported me fully in connection with my field work as well as thesis write-up. I am really grateful to them. I thank Dr Niaba Teme my in country supervisor who shared his precious time for the benefit of my project. I salute the university of Accra-Legon as the umbrella institution for providing right atmosphere. I thank Dr Aboubacar Touré, Dr Issoufou Kapran my colleagues and staff at CRRA Sotuba for their support.

REFERENCES

Alastair, H.F, and Robert, K.M.H: Environment Physiology

of plants. Third edition, Academic cross ISBN:

9780122577666 P 130 - 187Arboleda-Rivera F and

Compton WA (1974) Differential response of maize (Zea

mays L.) selection in diverse selection environments.

Theoretical and Applied Genetics 44: 77-81, 2001

Badu-Apraku, B., M.A.B. Fakorede, A. Menkir, A.Y. Kamara,

and S.Dapaah. (2005): Sceening maize drought tolerance

in the Guinea savanna of West and Central Africa. Cereal

Res. Commun. 33:533-540. Doi: 10.1556/CRC.33.2005.2-

3.116, 2005

Badu-Apraku, B., Akinwale, R.O., Ajala,.S.O, Menkir, A.,

Fakorede, M.A.B., Oyekunle, M: Relationships among

traits of tropical Early maize Cultivares in contrasting

environments Agronomy Journal. Vol 103, issue 3, 2011

Badu-Apraku, B. and Oyekunle, M: Genetic analysis of grain

yield and other traits of extra-early yellow maize inbreds

and hybrid performance under contrasting environments

Field crops Research129 99-110, 2012

Barker, T., Campos, H., Cooper, M., Dolan, D., Edmeades, G.,

Habben, J., Schussler, J., Wright, D and Zinselmeier, C:

Improving Drought tolerance in maize. Plant breeding

reviews, vol 25 ISBN 0471666939, 2005

Christian, Stige. Let al: The effect of climate variation on

agro-pastoral production in Africa, 2006

Edmeades, G.O., Bänziger, S.C., Chapman, J.M. Ribaut, and

Bolaños, J. (1995). Recent advances in breeding for

drought tolerant in maize. P. 24-41. In B; Badu-Apraku et

al Relationship among traits of tropical early maize

cultivars in contrasting environments Agronomy journal

Vol 103, issue 3 ; 2011

EUCORD (2008): Mali Development of Agriculture through

Sorghum Hybrids 1050 Brussels, BELGIUM

Ne Smith, D.S., and Ritchie, J.T: Effects of soil water-deficits

during tassel emergence on development and yield

components of maize (Zea mays L.). Field crops Researsh

28:251-256, 1992

Philipp, J: Genetics of characters associated with drought

resistance in maize (Zeamays.L) Crop Science 21(3):71-75,

1996

Zaidi, P.H., Srinivasan, G., Cordova, H.S and Sanchez, C:

Gains from improvement for mid-season drought

tolerance in tropical maize. Field Crops Research 89:35-152,

2004

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APPENDIX 1.SOIL ANALYSIS

N° Laboratoire 1 2 3 4 5 6 7 8 9 10 11 12

Code 0-25cm Farako 1

25-40cm Farako1

0-25cm Farako2

25-40cm Farako2

0-25cm Sotuba1

25-40cm Sotuba1

0-25cm Sotuba2

25-40cm Sotuba2

0-25cm Yanfolila

1

25-40cm Yanfolila

1

0-25cm YanfoLila

2

25-40cm YanfoLila

2 PF(wilting point)2.5 PF(wilting point)3.0 PF(wilting point)4.2

10.13 7.75 5.21

13.89 10.70 7.89

6.99 4.37 2.93

8.13 5.17 3.06

8.19 5.22 2.99

13.13 9.65 7.55

11.71 7.99 5.34

12.63 9.24 6.62

23.48 20.48 15.78

23.85 19.26 15.65

28.89 24.50 19.15

24.85 22.56 18.37

Water holding capacity per horizon in mm 8.89 5.90 5.04 4.43 7.81 4.41 9.28 5.50 14.10 6.50 16.05 7.54

Total of Water holding capacity per soil profile

in mm 14.79 9.47 12.22 14.78 20.60 23.59

Sand %> 0.05mm Fine Silt % 0.05-

0.002mm clay % < 0.002mm

62 18 20

56 20 24

79 14 6

74 16 10

75 17 8

62 15 33

64 23 13

69 5

26

11 54 35

3 63 34

6 64 31

6 52 42

Textural class Silt Clay Sand

Silt Clay Sand Sand Silt Silt Sand Silt Sand Silt Clay

Sand Silt Sand Silt Clay Sand

Silt Fine Clay

Silt Fine Clay

Silt Fine clay Clay Silt

APPENDIX 2. GRAIN YIELD UNDER WATER STRESSED CONDITION ACROSS ALL SITES

ENTRIES YIELD tha-1 ENTRIES YIELD tha-1 CML505/X1368 2.456 CML444/J-16-1 1.513 V481-73X9071 2.252 CML505/V481-73 1.513 87036/CML442 2.209 TZL COMP-C2-S2/C11O-5 1.503

J-16-1/TZL COMP-C2-S2 2.177 87036XV481-73 1.493 9071/CML442 2.163 V481-73X1368 1.466

87036/TZL COMP-C2-S2 2.089 EXP1 24/(KU1403X1368) 1.456 CML505/CML442 2.072 C11O-5/(KU1403X1368) 1.451

CML505/9071 2.07 EXP1 24XV481-73 1.449 CML442/TZL COMP-C2-S2 2.053 CML444/X9071 1.437

P43SRC9FS100-1-1-8/C11O-5 2.014 87036X1368 1.432 CML505/XEXP1 24 1.973 CML444/CML442 1.408

CML444/87036 1.955 CML444/1368 1.382 9071/(KU1403X1368) 1.904 TZL COMP-C2-S2/9071 1.363

C11O-5X9071 1.89 87036XC11O-5 1.34 V481-73/CML442 1.883 TZL COMP-C2-S2/(KU1403X1368) 1.334 EXP1 24XC11O-5 1.842 P43SRC9FS100-1-1-8/1368 1.334

J-16-1/(KU1403X1368) 1.836 CML505/XJ-16-1 1.33 CML442/(KU1403X1368) 1.825 P43SRC9FS100-1-1-8/EXP1 24 1.322

J-16-1X9071 1.794 CML505/XC11O-5 1.311 1368/TZL COMP-C2-S2 1.788 V481-73/TZL COMP-C2-S2 1.3 87036/(KU1403X1368) 1.766 1368/CML442 1.285

CML444/(KU1403X1368) 1.726 EXP1 24/CML442 1.285 87036X9071 1.724 EXP1 24X1368 1.262

P43SRC9FS100-1-1-8/V481-73 1.718 J-16-1X1368 1.241 CML505/(KU1403X1368) 1.684 CML444/CML505 1.235

C11O-5XJ-16-1 1.68 J-16-1/CML442 1.197 1368X9071 1.67 EXP1 24XJ-16-1 1.17

EXP1 24X9071 1.665 C11O-5XV481-73 1.16 CML444/XEXP1 24 1.622 P43SRC9FS100-1-1-8/87036 1.159

CML444/C110-5 1.619 EXP1 24X87036 1.125 J-16-1XV481-73 1.616 CML505/P43SRC9FS100-1-1-8 1.115

87036XJ-16-1 1.612 V481-73/(KU1403X1368) 1.077 P43SRC9FS100-1-1-8/TZL COMP-C2-S2 1.604 Debanuyma 1.018

1368/(KU1403X1368) 1.596 CML505/X87036 0.907 P43SRC9FS100-1-1-8/J-16-1 1.57 C11O-5/CML442 0.838 CML444/TZL COMP-C2-S2 1.557 C11O-5X1368 0.812

CML444/P43SRC9FS100-1-1-8 1.552 P43SRC9FS100-1-1-8/(KU1403X1368) 0.793 P43SRC9FS100-1-1-8/9071 1.523 CML444/XV481-73 0.783

CML505/TZL COMP-C2-S2 1.522 P43SRC9FS100-1-1-8/CML442 0.69 Exp1 24XC25-9 1.519 EXP1 24/TZL COMP-C2-S2 0.685

29


APPENDIX 3. GRAIN YIELD UNDER WELL WATERED CONDITION ACROSS ALL SITES

ENTRIES YIELD tha-1 ENTRIES YIELD tha-1 9071/CML442 4.841 C11O-5/(KU1403X1368) 3.637

CML442/TZL COMP-C2-S2 4.763 CML444/(KU1403X1368) 3.629 P43SRC9FS100-1-1-8/87036 4.643 CML442/(KU1403X1368) 3.552

87036/CML442 4.563 TZL COMP-C2-S2/9071 3.529 CML444/87036 4.497 Exp1 24XC25-9 3.529 V481-73X1368 4.469 J-16-1X1368 3.527

P43SRC9FS100-1-1-8/9071 4.44 EXP1 24XC11O-5 3.5 C11O-5X9071 4.416 1368/CML442 3.489

V481-73/CML442 4.388 V481-73X9071 3.482 1368X9071 4.333 J-16-1XV481-73 3.457

CML505/V481-73 4.306 EXP1 24X9071 3.455 CML505/(KU1403X1368) 4.286 EXP1 24/(KU1403X1368) 3.452

C11O-5XJ-16-1 4.271 87036/(KU1403X1368) 3.435 J-16-1/TZL COMP-C2-S2 4.246 EXP1 24X1368 3.375

87036X9071 4.24 EXP1 24XJ-16-1 3.357 CML505/X1368 4.228 CML505/P43SRC9FS100-1-1-8 3.336

87036/TZL COMP-C2-S2 4.22 CML444/XEXP1 24 3.331 P43SRC9FS100-1-1-8/V481-73 4.152 TZL COMP-C2-S2/C11O-5 3.284

CML505/CML442 4.12 EXP1 24XV481-73 3.27 J-16-1X9071 4.075 J-16-1/CML442 3.225

CML444/J-16-1 4.059 1368/(KU1403X1368) 3.212 P43SRC9FS100-1-1-8/1368 4.043 87036XC11O-5 3.191

CML505/XC11O-5 4.033 CML444/X9071 3.181 CML444/P43SRC9FS100-1-1-8 3.998 CML444/CML505 3.143

CML505/XEXP1 24 3.992 TZL COMP-C2-S2/(KU1403X1368) 3.132 V481-73/TZL COMP-C2-S2 3.985 CML444/1368 3.063

87036XV481-73 3.984 C11O-5XV481-73 2.762 9071/(KU1403X1368) 3.909 EXP1 24X87036 2.725

EXP1 24/CML442 3.872 EXP1 24/TZL COMP-C2-S2 2.705 P43SRC9FS100-1-1-8/J-16-1 3.872 CML505/XJ-16-1 2.669 CML444/TZL COMP-C2-S2 3.864 C11O-5X1368 2.631

CML444/CML442 3.856 P43SRC9FS100-1-1-8/EXP1 24 2.558 87036XJ-16-1 3.829 CML505/TZL COMP-C2-S2 2.499 87036X1368 3.809 P43SRC9FS100-1-1-8/(KU1403X1368) 2.476

CML505/9071 3.787 V481-73/(KU1403X1368) 2.468 P43SRC9FS100-1-1-8/TZL COMP-C2-S2 3.77 P43SRC9FS100-1-1-8/CML442 2.366

1368/TZL COMP-C2-S2 3.711 C11O-5/CML442 2.234 CML444/XV481-73 3.688 J-16-1/(KU1403X1368) 2.151

P43SRC9FS100-1-1-8/C11O-5 3.644 CML505/X87036 1.956 CML444/C110-5 3.64 Debanuyma 1.427

30

performance of maize inbred lines and their hybrids under varying drought stress conditions in mali

Documents

drought conditions

nonwater stress conditions

drought tolerance

water regime

hybrids tolerant

best hybrids

good root number

good root weight