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 AJPS  Vol.11 No.10 , October 2020
Induced Resistance to Striga hermonthica in Sorghum by Gamma Irradiation
Abstract: Striga species affect the potential productivity of cereals in sub-Saharian Africa due to the lack of durable Striga-resistance in host crops. This study aimed at inducing the new source of resistance in sorghum using gamma irradiation. Dry seeds of three Sorghum varieties; Grinkan, ICV1049 and Sariaso14 were gamma-irradiated with 200 Gy, 300 Gy, 400 Gy and 500 Gy. Screening strategies involved a 2-year field and greenhouse experiments, where mutant Sorghum families, their parents and resistant control were artificially infected with Striga hermonthica seeds. Field screenings revealed induced genetic variability among them, forty families significantly reduced the number of emerged Striga plants or showed good Sorghum grain yield performance despite the infection by S. hermonthica ecotype from Burkina Faso. The induced putative resistant mutants were identified across the four applied gamma-irradiation doses. Greenhouse experiment confirmed Striga resistance in seven mutant Sorghum families leading to no emergence of Burkina’s S. hermonthica ecotype along with high resistance index (RI) and low Striga damage score. Among them, two mutants SA38M5 and IC47M5 withstood S. hermonthica ecotype from Sudan. The induced mutants will be evaluated for the release to farmers for commercial production. Further studies are ongoing on confirmed mutants to highlight their Striga resistance mechanisms and explore the potential of pyramiding different mechanisms to produce durable resistance to S. hermonthica in sorghum.

1. Introduction

Sorghum (Sorghum bicolor (L.) Moench), the fifth most important cereal crop grown in the world; is one of the world’s leading cereal crops, providing food, feed, fiber, fuel, and chemical/biofuels feedstocks [1]. It is a staple food crop for millions of farmers in African semi-arid tropics [2]. In Burkina Faso, sorghum covers about 45% of total cultivated land and is the first cereal in terms of production and cultivated by more than 71% of farm households in rain-fed conditions [3]. However, sorghum production is highly affected by one of the major biotic constraints, Striga hermonthica occurring in almost all cultivated areas [4]. S. hermonthica remains the most feared weed by producers because it has a strong negative effect in descending order on the productivity of sorghum (Sorghum bicolor (L.) Moench), Pearl Millet (Pennisetum glaucum (L.) R.Br.), Maize (Zea mays L.) and upland Rice (Orysa sativa L.) in infested fields.

Several control measures were recommended such as agronomical techniques and chemical control [5]. However, none of these options individually proved fully effective and they were applied when at least 75% of damage occurred during the underground growth of Striga [6]. Integrated management strategies with host plant resistance should be one of the viable solutions [7] because the use of resistant genotype seeds does not require additional technique and farming inputs. Seven Striga-resistant Sorghum varieties with effective field resistance were reported, including SRN39, IS9830, Framida, 555, Dobbs, Serena and N13 [8]. Among them, 555, Framida, IS9830 and SRN39 were classified as low germination stimulators [8] to Striga while N13 has both mechanical barriers [9] as a post-germination Striga resistance mechanism [10] that affects Striga seedbank in the soil. Unfortunately, these resistant Sorghum varieties are generally landraces with low yielding and/or are not adapted to Striga-infested areas [7].

Consequently, there is a need to investigate other technologies as mutagenesis that may induce genetic variability in farmers’ preferred varieties to integrate some emerged resistance to the parasite Striga in agronomically adapted varieties. The use of induced mutation has been widely accepted by breeders as a tool for crop improvement over spontaneous mutations that occur very slowly [11] at a very low rate. The mutation induction can be carried out using chemical or physical mutagens [12]. Among both strategies, physical mutagenesis is the most common [13] as more than 89% of the mutant varieties in the world were created with physical mutagens (gamma ray, X-ray, neutrons), of which 60% were generated using gamma rays [14]. A number of beneficial traits such as dwarfing, early flowering, high protein digestibility, and high lysine generated by mutation induction have been widely used in sorghum breeding [15].

This study aimed at creating genetic variability in farmers’ preferred Sorghum varieties through induced mutation and selecting of mutants endowed with Striga-resistance to ensure sustainable grain Sorghum production in infested fields.

2. Material and Methods

2.1. Genetic Material

Farmer surveys were conducted in five administrative regions of which the geographical limits are 1) Boucle du Mouhoun (11˚41'40"N - 13˚43'42"N and 2˚2'5"W - 4˚4'7"W); 2) Hauts Bassins (10˚40'39"N - 11˚41'40"N and 3˚3'6"W - 5˚5'8"W); 3) Centre Ouest (11˚41'40"N - 12˚42'41"N and 2˚2'5"W - 3˚3'6"W); 4) Centre Est (10˚55'30"N - 11˚56'40"N and 00˚26'30"W - 00˚34'40"W) and; 5) Est (10˚40'39"N - 12˚42'41"N and 00˚0'3"W - 02˚1'59"E) of Burkina Faso, where Sorghum is widely grown. Seeds of twenty-six famers’ preferred landraces and improved varieties of sorghum were collected. They were then screened for Striga-resistance in pots artificially Striga-infested [5]. No variety had an acceptable level of Striga-resistance (data not presented). Based on farmers’ preference and varietal purity, three Sorghum varieties; Sariaso14, Grinkan and ICSV1049 with preferred white grains, agronomic and commercial values were chosen for mutagenesis induction and seeds were provided by the national breeding programme. Sorghum varieties ICV1049 and Grinkan have a cycle length of 120 days (from the sowing to the grain maturity) while that of Sariaso14 is 115 days. The varieties ICV1049 and Sariaso14 are grown in areas with annual rainfall of 600 - 900 mm compared to 800 - 1000 mm for Grinkan. Seeds of Striga hermonthica ecotype from Burkina Faso, harvested during September to October 2016 from farmers’ Sorghum fields located in Kouaré village (Eastern region of Burkina Faso) with a germination capacity of 75% were used for artificial Striga-infestation of field and greenhouse experiments. The seeds of Striga hermonthica ecotype from Sudan with a germination capacity of 75% were only used for glasshouse screenings.

2.2. Generating of Mutagenized Sorghum Populations and Selecting of Putative Mutants

Dry seeds of Sorghum varieties were irradiated at four selected doses: 200, 300, 400 and 500 Gy from the Center for the Application of Isotope and Radiation Technology, National Nuclear EnergyAgency (BATAN, in Jakarta, Indonesia). The irradiated seeds (M1) and controls (parental lines) were sown in the INERA’s experimental field (Burkina Faso). Self-pollinated M1 panicles were harvested and planted as M2 panicle-to row. M2 plants were selected and advanced to M3/M4 families using pedigree selection method based on phenotypic variation and improved agronomic traits compared to that of the parent plants.

Two-year rain-fed field experiments were conducted on sandy-loam, tropical ferruginous soil at Kouaré research station (11˚95'03"N and 0˚30'58"E) located in the Eastern Sudan-savannah area of Burkina Faso to select putative Striga resistant mutants. Six hundred ninety-nine (699-M3/M4) and 221 (M4/M5) mutant lines (Table 1) were phenotyped for their resistance to Striga in 2017 and in 2018, respectively. Each genotype (putative mutant or parent) was sown on a row of 8 m long. The distance between rows was 1m and the hills within a single row were spaced by 0.80 m (11 hills per row). Each planting hill was artificially infested with 5 × 103 S. hermonthica seeds [5]. The blocks and replications were spaced by 1 m. The experimental design was an alpha lattice design with three replications.

Sorghum was planted on 15 July in 2017 and on 12 July in 2018 and harvested on 18 and 20 November, respectively. Sorghum seedlings were thinned at 14 days after the sowing to leave one plant per hill. Mineral fertilizers, NPK (12-24-12) and urea ((CO)2NH2) with 46% N were applied on 21 days after the planting (DAP) and 45 DAP, respectively. Two hoeings were carried out 21 and 35 DAP and the weeds, except Striga plants were manually pulled out during the rest of Sorghum cycle. The self-pollination by bagging of sorghum plants was carried out at heading time. Rainfall recorded during the Sorghum growth period in 2017 and in 2018 was 440.8 mm and 525.6 mm in 24 rain events for both years.

Field screening aimed at identifying Sorghum mutant lines which delayed Striga emergence and/or reduced the emerged Striga number along with high yielding. Five quantitative traits were therefore used to phenotype sorghum accessions. From each planting hill within a single row (family), number of Striga plants emerged 70 and 100 DAP were recorded in 2017; in addition to days to

Table 1. Number of sorghum mutant lines screened to Striga hermonthica in rain-fed fields, in 2017 and 2018.

*: lines led to delayed emergence of high number of Striga plants or high mortality of Striga seedlings in 2017.

the first Striga emergence (DFSE), days to grain Sorghum maturity (DSMa) and grain sorghum weight per panicle (GrWP) in 2018. From infested hills, Striga-infected Sorghum plant rates (SISPR) at 70 DAP (SISPR70) and 100 DAP (SISPR100) were derived.

2.3. Verification of Striga-Resistance in Sorghum Mutants under Pot Screening in Greenhouse Conditions

Pot experiments were performed to verify the Striga-resistance of forty mutant lines (M4-M6) selected in field conditions. Among them, 22, 5, 7 and 6 lines were generated from irradiations of 200, 300, 400 and 500 Gy respectively (Table 2). They were compared to a Striga-resistant reference control (Sorghum variety Framida) and their parents in the greenhouse of the Plant Breeding and Genetic Laboratory (PBGL) of the Joint FAO/IAEA Division, Seibersdorf, Austria. Greenhouse conditions included the temperature of 25˚C - 28˚C, 60% relative humidity and 16/8 h (light/dark) photoperiod during July-October of the year.

Each genotype was planted in two sets of plastic pots (11 cm diameter × 12 cm height): no Striga-infested versus Striga infested mixture of 900 g of soil-sand (1 v/1v) with 0.5 mg of Striga seeds/pot. The bottom of the pot was covered by filter paper to avoid run-off of Striga seeds during watering. For Striga seed conditioning, the pots were watered every 3 days for 10 days and then two Sorghum seeds were sown per pot. Sorghum seedlings were thinned to one plant at 14 DAP. The experimental design was completely randomized design with four replications (pots) for each accession. The pots were watered every three days without any additional treatment. Data were collected in individual pot 95, 118 and 140 DAP in both sets. Sorghum plant height was measured in both sets while emerged Striga plant number and height and, Striga damage score as the rate burned leaves in infested set and reduction in plant growth relative to the negative (non-infested) control-5 of [16] were recorded. From these variables, Striga resistance index [17] and reduction percentage of Sorghum plant growth [18] were derived as follows:

Table 2. Putative Sorghum mutant lines screened to Striga hermonthica in greenhouse conditions.

Resistance index ( R I ) = Height of infested sorghum plant Height of uninfested sorghum plant

Sorghum plant growth reduction ( G R % ) = X Y X 100 ; where X is Striga-free plant height (average of 4 plants) and Y is Striga-infested plant height.

The numbers of Striga plants emerged 95 DAP were not significantly different to that counted at 118 and 140 DAP. Therefore, only the average number of Striga plants emerged 95 DAP were presented.

2.4. Response of Putative Resistant Sorghum Mutants to Sudan’s Striga hermonthica Ecotype

Five putative mutants (SA38M5, IC83M5, IC47M5, GK715M4, GK629M4) identified in the field and verified in glasshouse were tested for their reaction to Striga hermonthica ecotype from Sudan. The experimental design and artificial Striga-infection of each genotype (mutants and parents) were as described above for pot-experiment in the glasshouse of the PBGL.

2.5. Statistical Analysis

Statistical analyses were carried out using Statistical Analysis 1 System (SAS, 9.1, 2 Institute, Cary, NC) and Rx64 3. 5.2. ANOVA was performed and means were separated using Newman Keuls Multiple Range test and differences were considered significant at 5% threshold (SAS, 9.1, 2 Institute, Cary, NC). The software Rx64 3. 5.2 was used to cluster Sorghum mutant families and establish Pearson correlation between Striga resistance parameters. The trend curve of plant height means of sorghum mutant lines at 95, 118 and 140 DAP under Striga infection versus no infection was also performed with Rx64 3. 5.2. Hierarchical clustering of mutant sorghum lines according to their Striga resistance was also performed (Rx64 3. 5.2) by treating each of three variables namely Striga resistance index, emerged Striga plants and Striga damage as a separate cluster. It repeatedly identified the two clusters that were closest together, and then merged the two most similar clusters. This iterative process continued until all the clusters are merged together.

3. Results

3.1. Screening of Mutant Populations for Resistance to Striga-Infection under Field Conditions

Within the mutagenized Sorghum populations (699) screened to Striga during the cropping season 2017, 144, 163, 133 and 259 mutant lines were generated from seeds irradiated with gamma rays at 200, 300, 400 and 500 Gy, respectively. In the first round of screening in 2017, Sorghum plants with a Striga-infestation level ranging from 0 to less than or equal to five emerged Striga plants per sorghum planting hill were selected for a second round of screening in similar conditions. These observations resulted in the selecting of a total of 221 Striga putative resistant mutant lines of which, 80, 55, 25 and 61 mutant lines were generated from irradiations of 200 Gy, 300 Gy, 400 Gy and 500 Gy respectively. Analysis of variance for the Striga resistance traits observed in 2018, ranked Sorghum mutants into clusters. Coefficient of variation values indicated a moderate variation (20% - 30%) between clusters for days to the first Striga emergence (DFSE) counted in Sariaso14 and ICSV1049 derived mutant lines. Conversely, there was a large variation (38% - 85%) between clusters for the Striga-infected Sorghum plants at 70 DAP (SISPR70) and at 100 DAP (SISPR100) for all mutant lines. A significant difference between the different clusters (P < 0.0001) is observed for each trait, which reveals genetic diversity between the individual Sorghum plants that make up these clusters. Sariaso14 mutant lines were classified into three clusters for the traits SISPR70, SISPR100 and DFSE. At 70 DAP, 92 sensitive lines were discriminated with 26% - 69% infected plants and 32 out of 149 lines were not infected by Striga compared to nine non-attacked lines at 100 DAP to the end of Sorghum growth phase. Grinkan mutant lines were subdivided into four clusters, 14 lines were Striga-free at 70 DAP against 10 lines at 100 DAP to Sorghum harvest time. ICSV1049 mutants were also ranked into four clusters. Seven and five mutant lines with the lowest rate of Striga-infection were recorded at 70 DAP (0% - 8%) and 100 DAP (0% - 17%), respectively. Only two mutant lines were not parasitized until Sorghum harvest time (Table 3).

Table 3. Frequency of Sorghum lines segregating for Striga hermonthica resistance observed in rain-fed field conditions.

SISPR70: Striga-infected Sorghum plant rate 70 DAP; SISPR100: Striga-infected Sorghum plant rate 100 DAP; DFSE: Days to first Striga emergence: DSMa; days to Sorghum maturity: GrWP: grain sorghum weight (g) per panicle.

Regarding both variables of DSMa and GrWP, coefficient of variation values revealed high variation between clusters only for Sorghum grain/panicle for Sariaso14 mutants (40%) and Grinkan mutants (36%). ANOVA showed significant differences (P < 0.0001) between clusters of mutants within the same Sorghum variety (Table 1). The 120-day cycle length of ICSV1049 and Grinkan varieties was significantly reduced with seven ICSV1049 mutants (106 - 112 days), three Grinkan mutants (105 - 109 days) and two Grinkan mutants (94 - 97 days) while the cycle length of Sariaso14 (115 days) was highly reduced with 13 mutants (92 - 100 days). Grain Sorghum weights per panicle of mutants were ranked into four clusters. The most yielding mutants were 80 lines of Sariaso14 mutants (97 g grain/panicle), 5 lines of Grinkan mutants (79 - 104 g grain/panicle) and one ICSV1049 mutant (Table 3).

3.2. Response of Sorghum Mutant Lines to Striga Infection under Glasshouse Conditions

No Striga emergence occurred in pots planted with the known resistant Framida and eight mutant lines (GK715M4, GK220M5, GK225M5, IC83M5, IC47M5, IC17M6, SA38M5 and SA188M6) (Table 4). These mutant lines displayed weaker Striga damage (P < 0.0001) with significantly high resistance index (P < 0.0001) compared to the susceptible parent varieties. The reaction of sorghum plants to all Striga plants attached to their root system (emerged or buried in the soil) showed that four mutants; SA38M5, GK715M4, IC47M5 and IC83M5 scored Striga damage of less than 40%. Count of Striga plant number at 95 DAP with 14 mutant lines is not significantly different from that of the known resistant control Framida. The average height of Striga plants varied between 0.2 cm and 28 cm. The highest Striga plant height was recorded in the pot of the parent Sariaso14 (P < 0.0001), which is similar to that measured in pots of the parent ICSV1049 and 17 of the mutant lines (Table 4).

Table 4. Response of mutant Sorghum lines to the infection of Striga hermonthica ecotype from Burkina Faso 95 DAP under greenhouse conditions at PBGL, Seibersdorf.

Values are means ± standard error. Means with the same letter are not statistically different.

Striga damage was positively correlated to the number (r = 0.1, P = 0.49) and the height (r = 0.31, P < 0.04) of emerged Striga plants, showing that Striga damage was more significant when Striga number and/or plant height increase (Figure 1). Positive significant correlation between Striga number and plant height (r = 0.55, P < 0.0001) was also revealed. These three Striga variables evolved in the same direction while resistance index (RI) evolved in the opposite. Striga resistance index was negatively and significantly correlated to damage (%) (r = −044, P = 0.002), emerged plant number (r = −0.64, P < 0.0001) and plant height (r = −0.58, P < 0.0001) of Striga. Resistance index therefore decreases when the other three Striga variables increase (Figure 1).

The trend curve of the height of Striga-infected Sorghum plants was compared to that of non-infected plants (Figure 2). The average of non-infected plant height was 67.87 cm, 71.06 cm and 78.89 cm against 51.22 cm, 55.56 cm and 56.4 cm for Striga-infected plant height at 95, 118 and 140 DAP, respectively. The trend curves showed that non-infested Sorghum plants continued to grow in height (Figure 2(A)) while infested plants reached their maximum height (Figure 2(B)) at 140 DAP. Striga-infection therefore reduced Sorghum plant height about 24.5%, 21.81% and 28.5% at 95, 118 and 140 DAP, respectively. Figure 3 shows that the biomass of the parent Sariaso14 was highly reduced by Striga attack compared to the mutant line SA38M5.

3.3. Hierarchical Clustering of Sorghum Mutant Lines According to Their Striga Resistance

The hierarchical clustering reveals that the three descriptive variables, Striga resistance index, emerged plants and damage, significantly discriminated three clusters among the screened Sorghum genotypes. The first cluster involved 14 mutant families which, did not induce Striga emergence leading to high resistance index and weak Striga damage. The second cluster consisted of 21 mutant lines and two parents (ICSV1049 and Grinkan) that showed high resistance index

Figure 1. Distribution of Striga variables in Plan 1 - 2 revealed from principal component analysis with 40 sorghum mutant lines screened under pot conditions.

Figure 2. Reducing effect of Striga-infection on sorghum plant height. (A) Trend of sorghum height under non-infested pots; (B) Trend of sorghum height under infested pots.

Figure 3. Plant vigour of Sariaso14 parent (A) and a mutant, SA38M5 (B) in Striga-infected pots (+) versus in non-infected pots (−), 95 days after planting (DAP).

and high Striga damage and the third cluster gathered six mutant lines and the parent Sariaso14 which displayed low resistance index and high damage rate (Figure 4).

3.4. Response of Five Sorghum Mutants Resistant to the Burkina Striga Ecotype to Another African Ecotype from Sudan

ANOVA showed significant differences between Sorghum genotypes for the number of emerged Striga plants (P < 0.006), percentage of Striga damage on Sorghum plants (P < 0.0001) and Striga resistance index (P < 0.0001) when infected by S. hermonthica ecotype from Sudan (Table 5). No Striga emergence was recorded at 95 DAP with three Sorghum mutants; SA38M5, GK715M4 and IC47M5 and the resistant control (Framida). Striga resistance index was highest

Figure 4. Hierarchical clustering of Sorghum mutant lines according to the resistance index, damage and emerged plant number of Striga hermonthica.

Table 5. Response of mutant sorghum lines to the infection of Sudan’s Striga hermonthica ectype, 95 DAP in greenhouse conditions at PBGL, Seibersdorf.

Values are means ± standard error. Means with the same letter are not statistically different in the same column.

with the plants of these four Sorghum genotypes. However, plant syndrome rating which reflects the damage caused to the Sorghum plant in reaction to Striga infection revealed only SA38M5 and IC47M5 are considered resistant (Table 5).

4. Discussion

Field screenings highlighted a strong genetic heterogeneity between screened mutant lines. The phenotypic types showed significant variation for the five qualitative traits. Mutant lines were therefore ranked into three or four clusters with respects to each of the measured variables. The large difference between the minima and maxima for all quantitative traits showed that there is a great diversity within the clusters discriminated. The high coefficients of variation (CV > 30%) revealed high genetic variability for the traits Striga-infected Sorghum plant rate 70 and 100 DAP (SISPR70 and SISPR100) within the mutant lines and grain sorghum weight (g) per panicle (GrWP) for Sariaso14 and Grinkan mutants. On the other hand, the low coefficients of variation indicate low genetic variability for the trait days to Sorghum maturity (DSMa). Sorghum mutant lines selected from field experiment as putative Striga-resistant were generated from the four doses of gamma irradiation (200, 300, 400 and 500 Gy). These results suggest that the development of Striga-resistant Sorghum mutant lines is not influenced by the irradiation dose of gamma rays. They also suggest that induced mutation using gamma irradiation is a powerful tool for creating genetic variability in order to exploit newly emerging traits to improve the agronomic characteristics of crops [19].

The differences in Striga emergence delay observed with the mutant lines showed that some mutant lines were endowed with some potential genetic that influences the time of Striga seed germination whereas others did not allow it. No Striga emergence in host plot was explained as the inhibition of germ tube exo-enzymes by host root exudates and the synthesis of phyto-alexins that would block the emission of Striga germ tube [20]. Late Striga emergence may be due to a hypersensitive host response that delays the development of parasite in the soil [21].

With regards to Striga infection on Sorghum growth, seven mutants (SA38M5, SA188M6, GK715M4, GK225M5, IC47M5, IC83M5 and IC17M6) recorded low damage scores (4 - 5) coupled with a high resistance index. They can therefore be considered as resistant mutant lines according to [20] who qualified Striga-resistance as the capacity for the host plant to prevent Striga attachment and seedling development and well-yielding compared to the sensitive plant. On the other hand, high resistance index was observed with four mutants GK220M5, GK251M5, GK629M4 and SA251M5 of which biomass was affected by Striga attack. These last four mutant lines growing better than others Striga-infected lines could be considered as tolerant. [22] defined Striga tolerance as the capacity of host plant to maintain biomass and grain yield compared to the sensitive plant under the same level of Striga-infection. The screening of five mutants to Striga hermonthica ecotype of Sudan showed that three mutants SA38M5, GK715M4 and IC47M5 did not allow for the emergence of Striga plants. These mutants could be recommended as resistant Sorghum to the parasite in Burkina Faso and Sudan. No Striga emergence doesn’t mean no Striga attacks. Indeed, these three mutants showed severe attack symptoms although no Striga plants emerged in pot. This could be explained by the fact that a large number of Striga seedlings are attached to their roots and then cause significant damages to the host. These mutants are therefore not completely immune to the two Striga ecotypes but are endowed with form of mechanism of resistance that allows them to escape from the parasite. The chlorosis or burnt leaves observed on Striga-infected mutant plants have been reported by [23] who emphasized that sensitive Striga infected sorghum displays disease and symptoms including severe stunting, leaf chlorosis, necrosis and desiccation which lead ultimately to pre-mature wilting. The reducing effect of Striga-infection on mutant plant height about 22% - 28% (95 - 140 DAP) may be due to the attachment of Striga seedlings on the host root system that results in the reducing of host plant height by taking the substantial amount of nutrients from the host plant [24]. [25] further explained that Striga infection on sorghum significantly affects its photosynthesis which reduces the host crop growth. Striga attack actively influences host transcription to foster parasitism by either up-regulating host genes associated with nutrient supply or by down-regulating defence-related genes [26]. Resistance trait reduces the number of successful attachments and, the reproductive output of the parasite accordingly [27]. However, the deleterious effects of Striga parasitism on resistant cultivar growth, morphology and yield are complex and are not always related [28].

The positive correlation between damage, emerged plant number and plant height of Striga revealed that these three variables may be measured simultaneously for the selection of Sorghum mutants for Striga-resistance. The strong negative correlation between Striga resistance index and the three parameters including Striga damage, emerged plant number and plant height indicated that the higher the resistance index, the lower Striga number, plant height and damage. This correlation indicated that the selection of Sorghum mutants with a higher resistance index results in reduced Striga number, plant height and damage.

Averaged over results recorded in field and greenhouse experiments, three mutant Sorghum lines SA38M5, IC47M5 and GK715M4 are the most promising to withstand the obligate root parasite S. hermonthica. Multi-site and multi-season field tests are needed to highlight the stability of the traits Striga-resistance and yielding of sorghum mutants in terms of reduced Striga number and yield components to multivariate agro-ecological conditions because of the eventual existence of local Striga strains. Mutation breeding enabled to generate genes of interest and identify Striga resistance sources that may be exploited through conventional plant breeding programs. However, further studies including microscopic bioassays and histological analysis should be done to understand the resistance mechanisms of those mutants. Genotyping studies would allow marker assisted breeding with the prospect to pyramid resistance genes into the most framers’ preferred Sorghum variety from each agro-ecological area for more sustainable Striga resistance.

Acknowledgements

The authors are grateful to Joint FAO/IAEA Division for Nuclear Techniques in Food and Agriculture NACA CRP D25005 and the TC department of the IAEA for supporting Sorghum mutation breeding in Burkina Faso (BKF 5013 & BKF5019) and for providing with fellowship training to M. Minimassom Philippe NIKIEMA at the PBGL, Seibersdorf. Authors are also thankful to the “Institut de l’Environnement et de Recherches Agricoles (INERA)” of Burkina Faso for providing with the infrastructure allowing to carry out some experiments and WASCAL for providing WASCAL BLOC award for data collection and analysis to M. NIKIEMA. The authors are also grateful to PrSoeranto Human from the Center for the Application of Isotope and Radiation Technology, National Nuclear Energy Agency (BATAN, in Jakarta, Indonesia) for agreeing to irradiate seeds of our sorghum varieties with gamma rays.

Cite this paper: Nikièma, M. , Yonli, D. , Rabefiraisana, H. , Ali, A. , Ouédraogo, N. , Traoré, H. , Yanogo, H. , Dao, K. , Sawadogo, M. , Jankuloski, L. , Ivan, I. and Abdelbagi, M. (2020) Induced Resistance to Striga hermonthica in Sorghum by Gamma Irradiation. American Journal of Plant Sciences, 11, 1545-1561. doi: 10.4236/ajps.2020.1110112.
References

[1]   Kresovich, S., Barbazuk, B., Bedell, J.A., Borrell, A., Buell, C.R. et al. (2005) Toward Sequencing the Sorghum Genome. A U.S. National Science Foundation-Sponsored Workshop Report. Journal of Plant Physiology, 138, 1898-1902.
https://doi.org/10.1104/pp.105.065136

[2]   Ng’uni, D., Geleta, M., Johansson, E., Fatih, M. and Bryngelsson, T. (2011) Characterization of the Southern African Sorghum Varieties for Mineral Contents: Prospects for Breeding for Grain Mineral Dense Lines. African Journal of Food Science, 5, 436-445.

[3]   Vom Brocke, K., Trouche, G., Weltzienb, E., Barro-Kondombo, C.P., Gozéd, E. and Chantereau, J. (2010) Participatory Variety Development for Sorghum in Burkina Faso: Farmers’ Selection and Farmers’ Criteria. Field Crops Research, 119, 183-194.
https://doi.org/10.1016/j.fcr.2010.07.005

[4]   Boussim, I.J., Yonli, D., Guinko, S. and Sallé, G. (2011) Etat d’infestation, connaissance endogène et approche systématique des espèces du genre Striga au Burkina Faso. International Journal of Biological and Chemical Sciences, 4, 1374-1386.
https://doi.org/10.4314/ijbcs.v5i4.4

[5]   Marley, P.S., Ahmed, S.M., Shebayan, J.A.Y. and Lagoke, S.T.O. (1999) Isolation of Fusarium oxysporum with Potential for Biocontrol of the Witchweed (Striga hermonthica) in the Nigerian Savanna. Biological Control and Technology, 9, 139-163.
https://doi.org/10.1080/09583159929749

[6]   Parker, C. and Riches, C.R. (1993) Parasitic Weeds of the World: Biology and Control. CAB International, Wallingford, 332. https://doi.org/10.1007/BF02862335

[7]   Ejeta, G. (2007) Breeding for Striga Resistance in Sorghum: Exploitation of an Intricate Host-Parasite Biology. Crop Science, 47, 216-227.
https://doi.org/10.2135/cropsci2007.04.0011IPBS

[8]   Mohamed, A.H., Housley, T.L. and Ejeta, G. (2010) an in Vitro Technique for Studying Specific Striga Resistance Mechanisms in Sorghum. African Journal of Agricultural Research, 5, 1868-1875.

[9]   Mohamed, A., Ali, R., Elhassan, O., Suliman, E., Mugoya, C., Masiga, C.W., Elhusien, A. and Hash, C.T. (2014) First Products of DNA Marker-Assisted Selection in Sorghum Released for Cultivation by Farmers in Sub-Saharan Africa. Journal of Plant Science & Molecular Breeding, 3, 2050-2389.
https://doi.org/10.7243/2050-2389-3-3

[10]   Haussmann, B.I.G., Hess, D.E., Welz, H.G. and Geiger, H.H. (2000) Improved Methodologies for Breeding Striga-Resistant Sorghums. Field Crops Res, 66, 195-211.
https://doi.org/10.1016/S0378-4290(00)00076-9

[11]   Wang, Z.H., Zhang, X.C. and Jia, Y.L. (2017) Development and Characterization of Rice Mutants for Functional Genomic Studies and Breeding. In: Tomlekova, N.B., Kozgar, M.I. and Wani, M.R., Eds., Mutagenesis: Exploring Novel Genes and Pathways, Wageningen Academic Publishers, Wageningen, 307-332.

[12]   Taheri, S., Abdullah, T.L., Jain, S.M., Sahebi, M. and Azizi, P. (2017) TILLING, High-Resolution Melting (HRM), and Next-Generation Sequencing (NGS) Techniques in Plant Mutation Breeding. Molcular Breeding, 37, Article No. 40.
https://doi.org/10.1007/s11032-017-0643-7

[13]   Song H.S. and Kang, S.Y. (2003) Application of Natural Variation and Induced Mutation in Breeding and Functional Genomics: Papers for International Symposium; Current Status and Future of Plant Mutation Breeding. Korean Journal of Breeding Science, 35, 24-34.

[14]   Kharkwal, M.C., Pandey, R.N. and Pawar, S.E. (2004) Mutation Breeding for Crop Improvement. In: Jain, H.K. and Kharwal, M.C., Ed., Plant Breeding, Springer, Dordrecht, 601-645.
https://doi.org/10.1007/978-94-007-1040-5_26

[15]   Oria, M.P., Hamaker, B.R., Axtell, J.D. and Huang, C.P. (2000) A Highly Digestible Sorghum Mutant Cultivar Exhibits a Unique Folded Structure of Endosperm Protein Bodies. Proceedings of the National Academy of Sciences of the United States of America, 97, 5065-5070. https://doi.org/10.1073/pnas.080076297

[16]   Sangaré, S., Menkir, A., Ofori, K. and Gracen, V. (2018). Combining Ability for Grain Yield, Agronomic Traits and Striga Hermonthica Resistance of Yellow Endosperm Maize. Journal of Plant Genetics and Breeding, 2, 107.

[17]   Menkir, A. and Meseka, S.K. (2019) Genetic Improvement in Resistance to Striga in Tropical Maize Hybrids. Crop Science, 59, 2484-2497.
https://doi.org/10.2135/cropsci2018.12.0749

[18]   Akomolafe, G.F., Terna, T.P. and Okogbaa, J.I. (2018) Occurrence and Growth Inhibitory Activity of Striga hermonthica (Delile) Benth on Sorghum bicolor (L.) Moench in Lafia, Nigeria. Nigerian Journal of Basic and Applied Sciences, 26, 65-69.
https://doi.org/10.4314/njbas.v26i1.7

[19]   Chen, J.P., Zou, G.H. and Xin, Z.G. (2019) Development of a Pedigreed Sorghum Mutant Library. In: Zhao, Z.Y., Dahlberg, J., Eds., Sorghum, Methods in Molecular Biology, Humana Press, New York, 61-73.
https://doi.org/10.1007/978-1-4939-9039-9_5

[20]   Ejeta, G. and Butler, L.G. (1993) Host-Parasite Interactions throughout the Striga Life Cycle, and Their Contributions to Striga Resistance. African Crop Science Journal, 1, 75-80.
https://doi.org/10.4314/acsj.v1i2.69889

[21]   Mohamed, A., Housley, T.L., Ellicott, A. and Ejeta, G. (2003) Hypersensitive Response to Striga Infection in Sorghum. Crop Science, 43, 1320-1324.
https://doi.org/10.2135/cropsci2003.1320

[22]   Rodenburg, J., Bastiaans, L., Weltzien, E. and Hess, D.E. (2005) How Can Field Selection for Striga Resistance and Tolerance in Sorghum Be Improved? Field Crops Research, 93, 34-50.
https://doi.org/10.1016/j.fcr.2004.09.004

[23]   Van Ast, A. (2006) the Influence of Time and Severity of Striga Infection on the Sorghum Bicolor—Striga hermonthica Association. PhD Thesis, Wageningen University, Wageningen, 154 p.

[24]   Frost, D.L., Gurney, A.L., Press, M.C. and Scholes, J. (2008) Striga hermonthica Reduces Photosynthesis in Sorghum: The Importance of Stomatal Limitations and a Potential Role for ABA? Plant, Cell & Environment, 20, 483-492.
https://doi.org/10.1046/j.1365-3040.1997.d01-87.x

[25]   Gurney, A.L., Press, M.C. and Ransom, J.K. (1995) the Parasitic Angiosperm Striga hermonthica Can Reduce Photosynthesis of Its Sorghum and Maize Hosts in the Field. Journal of Experimental Botany, 46, 1817-1823.
https://doi.org/10.1093/jxb/46.12.1817

[26]   Spallek, T., Mutuku, M. and Shirasu, K. (2013) The Genus Striga: A Witch Profile. Molecular Plant Pathology, 14, 861-869. https://doi.org/10.1111/mpp.12058

[27]   Rodenburg, J., Bastiaans, L. and Kropff, M.J. (2006) Characterization of Host Tolerance to Striga hermonthica. Euphytica, 147, 353-365.
https://doi.org/10.1007/s10681-005-9030-2

[28]   Rodenburg, J., Bastiaans, L., Kropff, M.J. and Van Ast, A. (2006b) Effects of Host Plant Genotype and Seed Bank Density on Striga Reproduction. Weed Research, 46, 251-263.
https://doi.org/10.1111/j.1365-3180.2006.00506.x

 
 
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