Agro-morphological characterization of Mauritanian Sorghum ''Sorghum Bicolor (L.) Moench'' accessions and selection for their tolerance to water stress

Agro-morphological characterization of Mauritanian Sorghum ''Sorghum Bicolor (L.) Moench'' accessions and selection for their tolerance to water stress | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Agro-morphological characterization of Mauritanian Sorghum ''Sorghum Bicolor (L.) Moench'' accessions and selection for their tolerance to water stress Fatimata Amadou SECK, Med Aballah Med Mahmoud, Soukeina El Moctar, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6931390/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Mauritania is a Sahelian country highly exposed to climate change. Its territory is subject to successive variations in agricultural production caused by several factors, including low and irregular rainfall; deteriorating climatic conditions, and widespread desertification. In addition to these phenomena, which limit agricultural production in Mauritania, yields could fall further as a result of global warming and climate change, which aggravate inappropriate agricultural practices such as over-exploitation of the land, insufficient irrigation, and the advance of the desert. Drought is one of the major constraints that considerably affects the growth and development of plants and limits crop productivity by inducing osmotic stress. It is in this context that this study is being carried out on a set of local accessions of Mauritanian sorghum (Sorghum bicolor) to explore the phenotypic variability of this heritage and to characterize agro-morphologically this resource under water stress. Morphological, agronomic, and phenological parameters were studied during the project. Analysis of variance showed a highly significant effect of varieties on all morphological parameters. The Rhaye (Sidi nielbe) and Nienikou accessions are the earliest, with a heading period of 45 days, while the Nébané and Bechne Aarre varieties are the latest, with a heading period of around 80 days. The Nieniko, Leghvere, Rhaye (Sidi nielbe), and coumbe Nday ecotypes are the best in terms of yield parameters. The Taghalit lhamra, Taghalit lbeyda, Ghilé, Ras louche, and Beyke ecotypes performed similarly under rainfed and irrigated conditions in terms of vegetative growth. Sorgho bicolor local (Sorghum bicolor) ecotypes water stress agro-morphology Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 1. Introduction Plants are exposed to different types of abiotic stress that unbalance cellular homeostasis and cause changes at different levels in plants: morphological, physiological, and molecular Bian et al (2017). These modifications have a negative influence on the different phenological phases of the plant, such as survival, biomass production, and grain yield Boyer (1982). Agricultural production in several regions of the world is affected by abiotic stresses caused by global warming. Drought is one of the major stresses that considerably affects plant growth and development and limits crop productivity by affecting its capacity to absorb nutrients from the soil and the mobilization and transport of nutrients Yu et al (2015) and Sarshad et al (2021). In sub-Saharan Africa, drought is often associated with very high temperatures, the combined effect of which considerably reduces crop productivity Hale et al (1987), particularly in rain-fed agricultural systems. These stresses are set to worsen in the coming years, with several climate models predicting increases in surface temperatures and drought episodes between now and Cambridge, (2007), raising further concerns about global food security Nelson et al (2009). Hence the need for drought-adapted plants to improve crop breeding for water stress tolerance Vinocur et al (2005). Mauritania is one of the Sahel countries most affected by periods of drought. The country was hit by repeated droughts in the 1970s and 1980s as a result of climate change. The area of arable land exposed to at least one drought per year will increase from 6% in 2000 to 10% in 2080, and the range of probability of annual exposure of arable land to drought will widen from 0.3–19% in 2000 to 0.6–36% in 2080. Agricultural production in Mauritania is essentially rainfed food production. The dominant staple crops are cereals, especially sorghum, as well as rice, maize, cowpea, and millet McCann (2015). Mauritania is subject to strong seasonal and annual variations in rainfall as well as recurrent droughts, which are major problems for agricultural production Sissoko et al (2011), Ozeret al (2014). A national action program for adaptation to climate change in Mauritania (2004) has shown that the drop in rainfall has led to a massive reduction in water resources and vegetation, aggravating land degradation and desertification, which in turn has led to the loss of arable land and a reduction in agricultural production, as well as the loss of grazing land and the depletion of livestock. This has led to an increase in poverty in rural communities, resulting in a mass exodus to urban centers. While only 27% of Mauritania's population was urban in 1980, this rate has more than doubled to 55% in 2019 (World Development Indicators, 2019). In developing countries and semi-arid and arid tropical regions, sorghum is a major staple crop for more than half a billion people. It provides protein-rich, fiber-rich, and gluten-free nutrition Assefa et al (2010) Albouchi et al (2000). In addition to human nutrition, sorghum is also used as a source of feedstock for bioethanol production Mathur et al (2017), even though sorghum is considered to be a drought-tolerant crop and remains productive under low-input conditions, water deficit affects its capacity to absorb nutrients from the soil and the mobilization and transport of nutrients Chaves et al (2002), Jafar et al (2004) The main abiotic stress facing sorghum in production areas is water stress Queiroz et al (2019). Genetic improvement for drought tolerance has proved to be the most cost-effective approach to improving agricultural productivity. However, this requires a broad genetic base and extensive information on available genetic resources. Thus, understanding plant responses to drought and selecting plants for increased drought tolerance are two major objectives of the studies. Very little is known about local sorghum genetic resources in Mauritania. It is in this context that we undertook this study on a set of local sorghum accessions from four Mauritanian regions, namely Hodh el Chargui, Hodh el Gharbi, Assaba, and Guidimagha, with the aim of : To explore phenotypic variability in all accessions. Agro-morphological characterization of this local plant genetic resource. To study the behavior of these local accessions about water stress. 2. Materials and methods 2.1. Plant material: The trial involved a collection of local ecotypes from the 4 regions of Mauritania, namely: Hodh el Chargui (H-C), Hodh el Gharbi (H-G), Assaba, and Guidimagha. The final list of ecotypes tested included 15 sorghum ecotypes Table 1. Table 1: List of plant materials tested 2.2. Setting up the trial : To protect the crops, the trial began with the installation of a wire fence, reinforced with barbed wire, followed by soil preparation and the installation of a drip irrigation system. Sowing was then carried out according to the predefined experimental setup. 2.3. Experimental set- up: The experimental set-up consisted of two blocks: irrigated and rain-fed blocks. Each variety is represented by a line of 20 plants with two replicates for each treatment (Figure 1). 2.4. Crop management : 2.4.1. Soil tillage l: A disc plow is used to plow the soil to a depth of 40 cm, followed by offsetting to break up the large clods and leveling to prepare the seedbed and prevent water stagnation. 2.4.2. Fertili zation : Fertilisation is limited to a base fertilizer in the form of organic manure (manure) at a rate of 5T/ha to simulate farmers' cropping conditions. 2.4.3. Irrigation : To prevent irregular rainfall and ensure the success of the crops for characterization data, we opted to irrigate one of the blocks. A drip irrigation system was chosen to save water and minimize weed growth. The second block was run under rainfed stress to get closer to the farmers' actual growing conditions. 2.5. Crop monitoring and maintenance : After the trial was set up, crops were regularly monitored and maintained. Monitoring and maintenance included irrigation, weeding, hoeing, ridging, phytosanitary treatment where necessary, and covering the ears to protect them from granivorous birds. 2.6. Data collection and processing : Data collection sheets were drawn up by the experimental protocol and used to collect the data. Four plants per ecotype and block were randomly selected and marked to monitor the parameters studied. Parameters studied : The characterization of the local ecotypes tested focused on a set of parameters that can be subdivided into three types, namely growth parameters, phenological parameters, and yield parameters. 2.6.1. Growth parameters : Monitoring and growth measurements concerned the following parameters : Number of leaves (NbrL), length of the third Leaf (LTl), width of the third Leaf (WTL), Plant height (Ph), number of tillers (NbrT), and length of internodes (L. In). These parameters were monitored and evaluated during the vegetative growth phase, up to the start of heading and flowering. 2.6.2. Phenological parameters : Phenological parameters are represented by the duration of heading (D. heading), calculated as the number of days between the sowing date and the date of 50% heading. 2.6.3. Yield parameters : The grain yield of the ecotypes studied was assessed using the parameters panicle length (pa.L), panicle diameter (paDi), panicle weight (PaW), and 1000-seed weight (P1000g). 2.7. Data processing : All the data were analyzed using SPSS version 22 software : A descriptive analysis was carried out to determine the minima, maxima, means, standard deviations, and variances of the various parameters studied. An analysis of variance (5%) was carried out to assess the effects of treatment (irrigated-pluvial) and variety (ecotype) on the variation in the parameters studied. A comparison of the averages of the different ecotypes tested was carried out, as well as a correlation analysis of the different parameters studied. 3. RESULTS 3.1. Growth parameters 3.1.1. Descriptive analysis The results of the descriptive analysis for irrigated and rainfed vegetative growth parameters are presented in Table 2 . Table 2 Descriptive analysis results for growth parameters for 36 sorghum ecotypes grown under irrigated and rainfed conditions. Parameter N Beach Minimum Maximum Average Standard deviation Variance Statistics Statistics Statistics Statistics Statistics Error std. Statistics Statistics Number of leaves ( NbrL ) 288 18,0 ,0 18,0 10,547 ,1232 2,0912 4,373 Leaf width (LW cm) 288 12,0 ,0 12,0 7,411 ,1094 1,8573 3,449 Leaf length (Ll cm) 288 98,0 ,0 98,0 64,530 ,8287 14,0643 197,803 Plant height (Ph cm) 288 360,0 ,0 360,0 98,250 5,3017 89,9724 8095,024 Length of internodes (L. In cm) 288 30,0 ,0 30,0 9,755 ,5156 8,7493 76,550 D.In cm 288 19,0 ,0 19,0 5,833 ,3254 5,5216 30,488 NbrT 288 5,0 ,0 5,0 ,372 ,0506 ,8579 ,736 The descriptive analysis shows a wide variability within the heritage studied, with ranges varying from 5 for the number of tillers to 360 for plant height. The leaf length and plant height parameters show the greatest variability, with standard deviations of 14.06 cm and 89.9 cm and a mean of 64.53 cm and 98.25 cm, with a minimum of 0 and a maximum of 98 cm and 360 cm respectively. However, the number of leaves and leaf width parameters showed low variability with standard deviations of 2.091 and 1.857 cm and a mean of 10.547 and 7.411 cm; a minimum of 0 and a maximum of 18 and 12 respectively. This wide variability predicts the possibility of selection within the plant material studied. 3.1.2. Analysis of variance for growth parameters The results of the analysis of variance are presented in Table 3 . Table 3 Analysis of variance results for growth parameters Source of variation Dependent variable Sum of type III squares ddl Medium square F Meaning Treatment Number of leaves (NbrL) 25,383 1 25,383 13,821 ,000 Leaf width (LW cm) 67,570 1 67,570 45,690 ,000 Leaf length (Ll cm) 6109,730 1 6109,730 57,283 ,000 Plant height (Ph cm) 1746580,500 1 1746580,500 1793,221 ,000 Length of internodes (L. In cm) 13250,563 1 13250,563 1496,779 ,000 D.In cm 4449,389 1 4449,389 1232,929 ,000 NbrT 39,753 1 39,753 86,954 ,000 Variety Number of leaves (NbrL) 566,523 35 16,186 8,814 ,000 Leaf width (LW cm) 502,461 35 14,356 9,707 ,000 Leaf length (Ll cm) 17758,405 35 507,383 4,757 ,000 Plant height (Ph cm) 207455,000 35 5927,286 6,086 ,000 Length of internodes (L. In cm) 4131,773 35 118,051 13,335 ,000 D.In cm 2033,000 35 58,086 16,096 ,000 NbrT 36,372 35 1,039 2,273 ,000 Treatment * Variety Number of leaves (NbrL) 266,523 35 7,615 4,146 ,000 Leaf width (LW cm) 100,523 35 2,872 1,942 ,002 Leaf length (Ll cm) 9862,926 35 281,798 2,642 ,000 Plant height (Ph cm) 158854,500 35 4538,700 4,660 ,000 Length of internodes (L. In cm) 2675,468 35 76,442 8,635 ,000 D.In cm 1488,111 35 42,517 11,782 ,000 NbrT 36,372 35 1,039 2,273 ,000 The analysis of variance shows highly significant effects (p ˂ 0.01) and an interaction between the treatment (irrigated-pluvial) and the variety (ecotype) on all the parameters studied. This translates into a variable behavior of the ecotypes, for the parameters studied, according to the growing conditions, and confirms the possibility of selection within the plant material in question. Table 3 : Analysis of variance results for growth parameters 3.1.3. Averages of parameters studied Only 18 of the 36 accessions were analyzed for the parameters studied. This choice was due to the very large volume of data recovered after the analysis, and to better represent, interpret, and draw the right conclusions from the results, we chose to work with the best-performing accessions. Number of leaves The average values for the number of leaves are shown in Fig. 2 . Figure 2 shows that the Ras lmouche ecotype recorded significantly more leaves (14) in irrigated and (13) in rainfed conditions, followed by Fella Bodjedou (13) in irrigated and (12) and Bechne laajlané which recorded (13) in irrigated and rainfed conditions, and Taghalit lbeyda, Rhaye, Ghilé, and Beyke have several leaves of (11) but in rainfed Ghilé and Beyke (12) Bechne Gadiaba recorded the same performance (11) and Nebane is the least performing (9) leaves in irrigated and (10) in rainfed. Leaf length The mean values of leaf lengths are shown in Fig. 3 . Figure 3 shows that the ecotypes Moussa Sidi recorded significantly the longest leaves in both irrigated and rainfed with a value of 82cm and 80cm respectively followed by Bechna Gadiaba, which recorded a non-significant difference with sidi moussa in irrigated (83cm) but significant in rainfed (73cm) Leghvere, Taghalit lbeyda and recorded significantly higher leaf lengths in rainfed than in irrigated (67cm, 70cm) respectively. Leaf width The average values of leaf widths are shown in Fig. 4 . Figure 4 shows that the accessions Bechne laajlané, Bechne gadiaba, and Ras lmouche recorded the same performance for this parameter in irrigated and rainfed conditions, with 9cm, 9cm, and 10cm respectively. In addition, Moussa sidi and CE151 recorded the broadest leaves in irrigated conditions (8cm and 8cm). Plant height at heading Average plant height values are shown in Fig. 5 . Figure 5 Plant height measurements show that only 11 ecotypes were able to reach heading under rainfed conditions. Of these ecotypes, Ghile was significantly taller at 140cm, followed by Taghalit lhamra and Taghalit (126cm), then Djabi wemras (98cm), Thaghalit lbeyda (96cm) and Bechne Aarre (90cm). Ghilé and Taghalit lhamra as well as Nebané (96cm) in rainfed conditions. In irrigated conditions, Rhaye (209cm), Taghalit (210cm), and Beyke (211cm) had the longest plants. Number of tillers The average values for the number of tillers are shown in Fig. 6 . These results show that none of the varieties produced tillers under rainfed conditions. Some accessions such as Taghalit lbeyda, Ghilé, and Taghalit lhamra as well as Nebané did not give tillers even under irrigated conditions; and Rhaye gave more tillers than the others with a significantly higher number (4 tillers): Table 4 Correlations between phenological parameters and yield NF LF LaF HP NF Pearson correlation 1 ,163 * ,498** 0,47** Sig (bilateral) 0 0 0 0 N 572 572 572 572 LF Pearson correlation ,163 * 1 0,394** 0,411** Sig (bilateral) 0 0 0 0 N 572 572 572 572 LaF Pearson correlation ,498** 0,394** 1 ,446 ** Sig (bilateral) 0,034 0 0 0 N 572 572 572 572 HP Pearson correlation 0,47** 0,411** ,446 ** 1 Sig (bilateral) 0 0 0 0 N 572 572 572 572 This analysis makes it possible to reflect a linear relationship between two continuous variables, with the correlation coefficient varying between − 1 and + 1, 0 reflecting a null relationship between the two variables, a negative value (negative correlation) meaning that when one of the variables increases, the other decreases; while a positive value (positive correlation) indicates that the two variables vary together in the same direction. The results in this table show highly significant positive correlations between leaf number, leaf length, leaf width, and plant height (Table 4 ). 3.2. Phenological and yield parameters Given that, almost all the ecotypes did not reach the end of their cycle under rain-fed conditions because of the scarcity of rain during the rainy season in Rosso (cumulative rainfall of less than 100 mm), the phenological and yield parameters will only concern the irrigated block. 3.2.1. Descriptive analysis for phenological and yield parameters The results of the descriptive analysis for phenological and yield parameters for irrigated sorghum are shown in Table 5 . Table 5 Descriptive analysis results for phenological and yield parameters N Beach Minimum Maximum Average Standard deviation Variance Statistics Statistics Statistics Statistics Statistics Error std. Statistics Statistics Time to heading (days) 144 53,0 46,0 99,0 74,660 1,4211 17,0533 290,813 Lpa (cm) 144 29,0 8,0 37,0 17,552 ,5387 6,4639 41,782 Dipa (cm) 144 27,0 3,0 30,0 10,948 ,4973 5,9672 35,607 Ppa (g) 144 251,0 5,0 256,0 49,028 2,9381 35,2571 1243,062 P1000g (g) 144 45,30 18,70 64,00 31,46 ,8913 10,69 114,413 Descriptive analysis shows a wide range of variability within the heritage studied, with ranges varying from 27 cm for panicle diameter to 251 g for panicle weight. The parameters duration to heading and panicle weight showed greater variability, with respective standard deviations of 17.05 cm and 35.25 g. This wide variability predicts the possibility of selection for these parameters within the plant material studied. 3.2.2. Analysis of variance for phenological and yield parameters The results of the analysis of variance are shown in Table 6 below : Table 6 Analysis of variance results for phenological and yield parameters Source Dependent variable Sum of type III squares ddl Medium square F Meaning Variety Time to heading (days) 40859,576 35 1167,416 173,486 ,000 PaL(cm) 5461,922 35 156,055 32,858 ,000 PaDI (cm) 4734,172 35 135,262 40,841 ,000 PaW (g) 155005,889 35 4428,740 21,022 ,000 P1000g (g) 14739,982 35 421,142 28,057 ,000 The analysis of variance shows highly significant effects (p ˂ 0.01) of the variety (ecotype) on all the parameters studied. This shows a variable behavior of the ecotypes for the parameters studied and confirms the possibility of selection within the plant material in question. 3.2.3. Averages of parameters studied Time to heading Average heading times are shown in Fig. 7 . These results show that the Rhaye (Sidi Nielbe) and Nienikou varieties are the earliest, with a heading period of 45 days, while the Nébané and Bechne Aarre varieties are the latest, with a heading period of around 80 days. Panicle length Average panicle lengths are shown in Fig. 8 . The results in this figure show that the MoussaSidi ecotype has the longest panicle (29cm), followed by Coumba Nday (24cm) and Rhayé (Sidi nielbé) (22cm) have the longest panicles. Thaghalit and Taghalit lbayda have the shortest panicles (11 cm). Panicle diameter Average panicle diameters are shown in Fig. 9 . The results in this figure show that the Bechne laajlané (17g), Nieniko (16g), and Leghvere (18g) ecotypes have the thickest panicles. Panicle weight Average values for panicle weights are shown in Fig. 10 . The results in this figure show that the same ecotypes Nieniko (61g), Leghvere (66g), and coumbe Nday (69g) are the best in terms of panicle weight. Weight of 1000 seeds The average weights of 1000 seeds are shown in Fig. 11 . The results in this figure show the same trend for the ecotypes, Bechne Gadiaba, Coumbé Nday recorded the heaviest seeds with (43g) and leghver significantly better is a panicle weight of (57g). 3.2.4. Correlation between phenological parameters and yield The correlations between the parameters are shown in Table 7 . Table 7 Correlations between phenological parameters and yield Time to heading (days) PaL (cm) PaDI (cm) PaW (g) P1000g (g) Time to heading (days) Pearson correlation 1 -,338 ** ,177 * ,190 * ,399 ** Sig (bilateral) ,000 ,034 ,022 ,000 N 144 144 144 144 144 PaL (cm) Pearson correlation -,338 ** 1 -,049 ,003 ,217 ** Sig (bilateral) ,000 ,562 ,971 ,009 N 144 144 144 144 144 PaI (cm) Pearson correlation ,177 * -,049 1 ,659 ** ,439 ** Sig (bilateral) ,034 ,562 ,000 ,000 N 144 144 144 144 144 PaW (g) Pearson correlation ,190 * ,003 ,659 ** 1 ,511 ** Sig (bilateral) ,022 ,971 ,000 ,000 N 144 144 144 144 144 P1000g (g) Pearson correlation ,399 ** ,217 ** ,439 ** ,511 ** 1 Sig (bilateral) ,000 ,009 ,000 ,000 N 144 144 144 144 144 **. The correlation is significant at the 0.01 level (two-tailed). *. The correlation is significant at the 0.05 level (two-tailed). These results show highly significant positive correlations between panicle diameter, panicle weight, and 1000-seed weight: i.e. as panicle diameter increases panicle weight increases, and 1000-seed weight increases. Table 6 also shows that there is a highly significant correlation between the duration of heading and panicle length. 4. DISCUSSION Lack of water is a limiting factor for plant growth, particularly in arid and semi-arid regions Reiahi et al (2013) The morphological and physiological behavior of a given plant depends on the species or variety, the duration and severity of the drought and the time of its application Morizet et al (1984). Mauritania is located in West Africa in the Saharan desert. It has an arid climate with average annual temperatures of between 21°C and 30°C and total annual rainfall ranging from barely 20 mm on the north coast to 400 mm in the center-south, which has a Sahelian climate CIA World (2020). Crops in Mauritania are mainly rain-fed, and yields are highly dependent on the availability of rainwater. However, agricultural areas are facing greater uncertainty and variability in weather conditions as a result of climate change Sissoko et al (2011), Ozeret al (2014). In response to rising greenhouse gas concentrations, the air temperature in Mauritania is expected to increase by 2.0°C to 4.5°C by 2080 compared with the year 1876 (World Development Indicators, 2019). Several analytical models used to predict the percentage increase in drought indicate that the area of arable land exposed to at least one drought per year will increase by 6–10% between 2000 and 2080 (CIA World, 2020). Given the increase in drought in recent years and population growth, which is expected to exceed 4.7 million in 2020 based on an annual population growth rate of 2.8% World Bank (2020); what is the purpose of this study to select drought-tolerant and productive accessions? Water stress, explained by soil water deficit, is the main abiotic stress seriously affecting crop yields worldwide. Water deficit considerably delays floral initiation and affects panicle development and the appearance of new leaves Ndlovu et al (2021); because it reduces photosynthesis, chlorophyll content, photosynthate translocation, and soil nutrient uptake, resulting in reduced yield quantity and Assefa et al (2010), Kapanigowd an et al (2013) and Sehgal et al (2018). In this experiment, the analysis of the variance of the variables studied showed highly significant differences between ecotypes for the morphological traits studied, which is in agreement with the results of Reiahi et al (2013). The quantitative parameters assessed showed variability between the accessions studied (Table 2 ). The number of leaves per plant (NF) varied from 9 to 14 cm for irrigated and 9 to 13 cm for rainfed. Leaf length varied from 69 to 80 cm for irrigated and 60 to 70 cm for rainfed. Leaf width varies from 6 to 9 cm for irrigated and 5 to 10 cm for rainfed. Analysis of plant height showed that only 11 ecotypes were able to reach heading under rainfed conditions, ranging from 100 to 200 cm for irrigated and 22 to 140 cm for rainfed. The number of tillers obtained varied between 0 and 4 per plant. Our results are higher than those obtained by Allam et al (2018) and lower than those of Koffi et al (2011) but are consistent with those observed by House (1987), who reported that the importance of these parameters varies according to the variety and good water supply. In addition, the accessions have a cycle (sowing - number of days to 50% flowering) that varies from 46 days for the earliest to 99 days for the latest. These results differ from those found by Koffi et al (2011): the earliest flowered at 66 days after sowing and the latest at 119 days. About panicle length and diameter, the results obtained show that these vary, respectively, from 11.25 to 29.87 cm and from 5 to 18.75 cm. These results are higher than those found by Rahal et al (2013) on a genotype originating from Senegal, 'Sergane', with panicles 21.15 cm long and 9.40 cm wide. The results are also consistent with House's (1987) statement that some sorghum panicles can reach 25 cm or more in length and 20 cm or more in width. In addition, Sawadogo et al (2014), found that the main panicles of some varieties are long and wide ranging from 20.7 cm to 51.3 cm and 20 to 23.3 cm, respectively. Panicle weights ranged from 20g to 69g. The weight of 1000 seeds obtained varies from 18 to 55 g. According to Rahal et al (2004) and House (1987), the weight of 1000 seeds can vary from 60 to 85 g for improved varieties. Our values are lower than those of House (1987); but higher than those found by Allam et al (2018) and also those of Koffi et al (2011). In our experiment, we found that there was a significant effect of water stress on yield parameters, as almost all the ecotypes did not reach the end of their rainfed cycle due to the scarcity of rainfall (cumulative rainfall of less than 100 mm). It is in this context that Lal et al (1996), Saccardy et al (1996), and Foyer et al (1998) have shown that if dry sequences do not exceed 10 days, photosynthetic capacity is not affected, so yield can be little affected and recorded in quantities close to the controls. These results are similar to those of Falalou et al (2005) on two cowpea varieties. More specifically, the results of this work show that there is great diversity between the accessions for the parameters studied, as different behaviors of the accessions were observed. For example, for growth parameters, it was observed that some accessions performed better in irrigated than in rainfed conditions; others performed equally well in the treatments, such as Taghalit lhamra, Taghalit lbeyda, Ghilé, Ras lmouch, and Beyke, and others performed poorly in both treatments. The Rhaye (Sidi Nielbe) and Nienikou varieties are the earliest, with a heading period of 45 days, while the Nébané and Bechne Aarre varieties are the latest, with a heading period of 80 days. In terms of panicle length, Moussa Sidi, Coumba Nday, and Rhayé (Sidi nielbé) have the longest panicles, while Thaghalit and Taghalit lbayda have the shortest. The Bechne laajlané, Nieniko, and Leghvere ecotypes have the thickest panicles. The results in this figure show that the Nieniko, Leghvere, and coumbe Nday ecotypes have the highest panicle weight. The ecotypes, Bechne Gadiaba, Coumbé Nday recorded the heaviest seeds with and leghver significantly better in panicle weight. 5. CONCLUSION In conclusion, the agro-morphological characterization of the different accessions from the regions of Hodh el Chargui, Hodh el Gharbi, Assaba, and Guidimagha showed that local sorghum accessions display a high degree of agro-morphological variability, reflecting genetic variability. This diversity seems to ensure that local accessions have the potential to adapt to variable growing conditions, such as water stress, and more generally to climate change. Analysis of the variance in agro-morphological parameters showed a highly significant effect of water stress on the various parameters studied. This analysis also showed a highly significant effect of the accession on the variability of the parameters, which gives an idea of the significantly variable behavior of these accessions about water stress and the possibility of using these resources for water stress tolerance. The Taghalit lhamra, Taghalit lbeyda, Ghilé, Ras lmouch, and Beyke ecotypes performed similarly under rainfed and irrigated conditions in terms of vegetative growth, and can therefore be used as fodder crops since they manage to produce biomass despite the stress. On the other hand, the Rhaye (Sidi nielbe) and Nienikou ecotypes are the earliest with a heading period of 45 days, and the Nieniko, Leghvere, Rhaye (Sidi nielbe), and coumbe Nday ecotypes are the best in terms of yield parameters. These accessions can be used by farmers when conditions are favorable for cultivation, as they have a short cycle and yield well. Specifically, the results of this work show that: Local accessions show a wide variability in the agro-morphological parameters studied. This reflects a richness that can be explored in varietal improvement. This study should be supplemented by other parameters: Carry out physiological studies. The phenological and yield factors that were predicted in this study could not be achieved because the stress applied was rather severe. Introduce other parameters such as percentage recovery, abscisic acid levels, and other physiological parameters. - Extended to other accessions from different regions of Mauritania where sorghum is grown. Declarations Author Contributions F.A.S wrote the paper. S.M.M.M, and Z.T developed conceptual ideas, designed the study and examined the document. M.M conducted statistical analysis. Z.T, contributed to the analysis of Data .M.M and Z.T revise the manuscript. Funding This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Competing interests The authors declare no conflict of interest Consent to Publish declaration: not applicable . Déclaration de consentement à participer : non applicable Ethics declaration: not applicable . References Albouchi A., Sebei H., Mezni M. Y. & EL Aouni M. H., 2000. Influence of the duration of deficient water supply on biomass production, transpiring surface, and stomatal density of Acacia cyanophylla. Annales de l'INRGREF. 4 : 138- 61p. Allam, Abdelkader, Aïssa Tirichine, Habib Madani and Wiam Benlamoudi. 2018. Morphological variability of sorghum (Sorghum bicolor L. Moench), grown in the Oued Righ valley (South-East Algeria). Lebanese Scientific Journal, 19(1): 10-18. Assefa Y, Staggenborg SA, Prasad VPV (2010) Sorghum water requirement and responses to water stress: a review. Crop Management 9(1):1-11. Bian, YW; Deng, X.; Yan, X.; Zhou, JX; Yuan, LL; Yan, YM Integrated proteomic analysis of roots and leaves of Brachypodium distachyon reveals a synergistic network in response to water stress and recovery. Sci. Rep. 2017, 7, 46183. Boyer, JS Productivity and the factory environment. Sciences 1982, 218, 443-448. CIA World Factbook, "Mauritania," 2020. Available online at https://www.cia.gov/library/publications/the-world-factbook/geos/ mr.html [Accessed: 29-Jun-2020]. Chaves, M.M.; Pereira, J.S.; Maroco, J.; Rodriques, M.L.; Ricardo, C.P.P.; Osorio, M.L. Carvatho, I.; Faria, T. and Pinheiro, C.; 2002. How plants cope with water stress in the field photosynthesis and growth ? Ann. Bot. 89: 907- Falalou H., Dicko MH, Zombré G, Traoré AS, Guinko S. 2005. Adaptive response of two cowpea varieties to water stress. Cahiers Agricultures; 14 (6): 651 - 567. Foyer, C.H. ; Valadier, M.H. ; Migge, A. and Becker, T.W. ; 1998. Drought-induced effects on nitrate reductase activity and mRNA and on the coordination of nitrogen and carbon metabolism in maize leaves. Plant Physiology, 117: 283- 292. IPCC. Summary for Policymakers. 7-22 (Cambridge, 2007). Hale, MG, Orcutt, DM and Thompson, LK Plant physiology under stress (Wiley, New York, 1987). House, L. R. 1987. Manual for sorghum breeding. Second edition, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Andhra Pradesh, India. 229 pp. Impa SM, Perumal R, Bean SR, Sunoj VSJ, Jagadish SVK (2019) Water deficit and heat stress-induced alterations in grain physicochemical characteristics and micronutrient composition of field-grown grain sorghum. J Cereal Sci 86:124-131. Islamic Republic of Mauritania, "National Adaptation Programme of Action to Climate Change," Nouakchott, Mauritania, 2004. Jafar MS, Nourmohammadi G, Maleki A (2004) Effect of water deficit on seedlings, seedlings and compatible solutes of forage Sorghum cv. Alimentation rapide. In: Proceedings of the 4th International Congress of Agricultural Sciences Brisbane, Austria Kapanigowda MH, Perumal R, Djanaguiraman M, Aiken RM, Tesso T, Prasad PVV, Little CR (2013) Genotypic variation in sorghum [ Sorghum bicolor (L.) Moench] exotic germplasm collections for drought and disease tolerance. Springer plus. Koffi, K. Germain, C., Akanvou, L., Akanvou, R., Zoro, B. I. A., Kouakou C. K. and N'da H. A. 2011. Morphological diversity of sorghum (Sorghum bicolor L. Moench) grown in northern Côte d'Ivoire. Revue Ivoirienne des Sciences et Technologie, 17: 125-142. K. Sissoko, H. van Keulen, J. Verhagen, V. Tekken, and A. Battaglini, "Agriculture, Livelihoods and Climate Change in the West African Sahel," Reg. Environ. Chang, vol. 11, no. 1, pp. 119-125, 2011. 11 Lal, A. and Edwards, G.E. ; 1996. Analysis of inhibition of photosynthesis under water stress in the C4 species Amaranthus cruentus and Zea mays : electron transport, CO2 fixation and carboxylation capacity. Functional Plant Biology, 23: 403-412 Mathur S, Umakanth AV, Tonapi VA, Sharma R, Sharma MK (2017) Sweet sorghum as a biofuel feedstock: recent advances and available resources. Biotechnol Biofuels 10:146. McCann T, Krause D, Sanguansri P (2015) Sorghum-new gluten-free ingredient and applications. Aust Food 67(6):24-26 Morizet, J.; Robelin, M.; Baucher, G.; 1984. Results of 18 years of lysimetric observations in the Limagne climate. Il. Étude des relations entre l'eau et la production végétale. Agronomie, 4: 407-416. Ndlovu E, van Staden J, Maphosa M (2021) Morpho-physiological effects of combined moisture, heat and stress on Sorghum bicolor [Moench (L.)] and its acclimatisation mechanisms. Plant stress. Nelson, GC et al. Climate change. Impact on agriculture and costs of adaptation. 32 (International Food Policy Research Institute, Washington, DC, 2009). P. Ozer, Y. C. Hountondji, J. Gassani, B. Djaby, and D. L. F, "Évolution récente des extrêmes pluviométriques en Mauritanie (1933- 2010)," XXVIIeme Colloq. Association Int. Climatol, pp. 394-400, 2014. 12 Queiroz MS, Oliveira CE, Steiner F, Zuffo AM, Zoz T, Vendruscolo EP, Silva MV, Mello B, Cabra R, Menis FT (2019) Drought stress on seed germination and early growth of maize and sorghum. J Agric Sci 11(2):310-318. Rahal-Bouziane, H., Mossab, K., Khelid, M., Kharsi, M. and Hamdi S. 2004. Promising results for a summer cereal from the Adrar oases: Sorghum sp. INRAA, Recherche agronomique, 14:57-64. Rahal-Bouziane, H., Semiani, Y., Yahiaoui, S., Oumata, S., Kharsi, M., Nait, Merzoug, S. and Djeddou, R. 2013. Characterization of some traditional Sorghum (Sorghum bicolor L.) genotypes under Mitidja conditions (Algeria). INRAA, Recherche agronomique, 26: 47-58. Reiahi N, Farahbakhsh H (2013) Effects of ascorbate and water stress on germination and growth of sorghum seedlings. Int J Agron Plant Prod 4(5):901-910 Sarshad A, Talei D, Torabi M, Rafiei F, Nejatkhah P (2021) Morphological and biochemical responses of Sorghum bicolor (L.) Moench under water stress. SN Appl Sci. https://doi.org/10.1007/s42452-020-03977-4 Saccardy K, Cornic G, Brulfert J, Reyss A. 1996. Effect of drought stress on net CO2 uptake in Zea leaves. Planta, 199: 589-595. Sawadogo, N., Nebie, B., Kiebre, M., Kando, P. B., Nanema, R. K., Traore, R. E., Naoura, G., Sawadogo, M. and Zongo, J. D. 2014. Agromorphological characterization of sweet grain sorghums (Sorghum bicolor (L.) Moench) from Burkina Faso. International Journal of Biological and Chemical Sciences, 8(5): 2183-2197. Sehgal A, Sita K, Siddique KHM, Kumar R, Bhogireddy S, Varshney RK, HanumanthaRao B, Nair RM, Prasad PVV, Nayyar H (2018) Effects of drought or/and heat stress on seed filling in food crops: impacts on biochemistry, seed yields and nutritional quality. Front Plant Sci 9:1705. Vinocur, B. & Altman, (2005) A. Recent advances in engineering plant tolerance to abiotic stress: achievements and limitations. Current. Avis. Biotechnol. 16 , 123-132. World Bank, "World Bank Open Data," 2019. Available online: https://data.worldbank.org [Accessed on: 31-Jan-2020]. World Bank, "World Development Indicators," 2019. Available online: https://databank.worldbank.org/source/worlddevelopment-indicators [Accessed on: 13-Nov-2020]. Yu SM, Lo SF, Ho THD (2015) Source-sink communication: regulated by cross-signalling of hormones, nutrients and stress. Trends Plant Sci 20(12):844-857. https://doi.org/10.1016/j.tplants.2015.10.009 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6931390","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":478143871,"identity":"96e7e2ca-4eaa-425c-b257-163649d319de","order_by":0,"name":"Fatimata Amadou SECK","email":"","orcid":"","institution":"Mohammed-V–Agdal University","correspondingAuthor":false,"prefix":"","firstName":"Fatimata","middleName":"Amadou","lastName":"SECK","suffix":""},{"id":478143872,"identity":"0733e485-8f43-447f-a332-29f42bd02a41","order_by":1,"name":"Med Aballah Med Mahmoud","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA1UlEQVRIiWNgGAWjYFAC5gYJIMnPxpB8gIGxASRwgJAWRrAWyTaGtASIFrYEIrU0MOQYEKeFXyKx8daNisMSfOw53yR+7rCRY2DjfYBXi+SMxGbrnDOHJdh43m6T7D2TZszAxm6AV4vBjcQ26dy2w3VsErnbJHjbDic2yLfhdxhMiwSbRM4zyb8gLWxsxGthk+YlRotkz0OQX9KBfnlmbC3blmbMRkgLP3vywds5FdYS8u3JD2++bbOR4yekBRmwgCKIgQQNwJTygRTVo2AUjIJRMHIAAKdcQLUeYu4HAAAAAElFTkSuQmCC","orcid":"","institution":"UR-UR-Genetic Resources and Environment, Higher Institute of Technological Education of Rosso","correspondingAuthor":true,"prefix":"","firstName":"Med","middleName":"Aballah Med","lastName":"Mahmoud","suffix":""},{"id":478143874,"identity":"e1e0329a-542f-4008-a171-58c037e57b4d","order_by":2,"name":"Soukeina El Moctar","email":"","orcid":"","institution":"UR-UR-Genetic Resources and Environment, Higher Institute of Technological Education of Rosso","correspondingAuthor":false,"prefix":"","firstName":"Soukeina","middleName":"El","lastName":"Moctar","suffix":""},{"id":478143878,"identity":"14521026-0b55-4e1e-87cc-a1895f813da8","order_by":3,"name":"Zine el Abidine TRIQUI","email":"","orcid":"","institution":"Mohammed-V–Agdal University","correspondingAuthor":false,"prefix":"","firstName":"Zine","middleName":"el Abidine","lastName":"TRIQUI","suffix":""}],"badges":[],"createdAt":"2025-06-19 12:53:18","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6931390/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6931390/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":86170208,"identity":"0aa5278e-0254-4eb1-9a51-5c8673086752","added_by":"auto","created_at":"2025-07-07 14:17:45","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":8348,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eExperimental set-up using complete randomized blocks\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6931390/v1/7a229838a773263771a4666e.png"},{"id":86170212,"identity":"a9936589-45c1-443b-aa63-01798f2192f1","added_by":"auto","created_at":"2025-07-07 14:17:45","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":51339,"visible":true,"origin":"","legend":"\u003cp\u003eAverage leaf number values for irrigated and rainfed crops\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6931390/v1/669f27828d7daf9f62908216.png"},{"id":86169533,"identity":"c65d6233-ebf1-400c-91df-6642509248a3","added_by":"auto","created_at":"2025-07-07 14:09:45","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":53410,"visible":true,"origin":"","legend":"\u003cp\u003eAverage leaf length values for irrigated and rainfed crops\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6931390/v1/e8dccf66de2a271fe0dd1d87.png"},{"id":86170206,"identity":"1a9a01a0-0c41-4135-ade8-36092166d482","added_by":"auto","created_at":"2025-07-07 14:17:45","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":57031,"visible":true,"origin":"","legend":"\u003cp\u003eAverage leaf width values for irrigated and rainfed crops\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-6931390/v1/56b7a004082fe20e974a0a50.png"},{"id":86171072,"identity":"0fee18b5-4faf-4406-8145-d3073318a3bb","added_by":"auto","created_at":"2025-07-07 14:25:45","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":51297,"visible":true,"origin":"","legend":"\u003cp\u003eaverage plant height values for irrigated and rainfed crops\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-6931390/v1/b7a1d19daa9a63089e2acdbc.png"},{"id":86170210,"identity":"b1719c57-c401-4751-8bbb-ffe384a4fa85","added_by":"auto","created_at":"2025-07-07 14:17:45","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":44581,"visible":true,"origin":"","legend":"\u003cp\u003eAverage number of tillers per plant in irrigated and rainfed systems\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-6931390/v1/768776c4807795bdbec75fd4.png"},{"id":86171071,"identity":"3053ee36-ea63-4e03-9377-cb85803c4978","added_by":"auto","created_at":"2025-07-07 14:25:45","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":55383,"visible":true,"origin":"","legend":"\u003cp\u003eAverage heading times for irrigated crops.\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-6931390/v1/44da76551877ba8f5a25ff3f.png"},{"id":86169547,"identity":"623eb007-fba8-4d9b-bed0-16c908a7220a","added_by":"auto","created_at":"2025-07-07 14:09:45","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":43940,"visible":true,"origin":"","legend":"\u003cp\u003eAverage panicle length in irrigated conditions.\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-6931390/v1/ada3f1948ef7c65488c35c21.png"},{"id":86171568,"identity":"f5ed8992-1057-4c6a-ac08-18a2ec27780b","added_by":"auto","created_at":"2025-07-07 14:33:45","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":49620,"visible":true,"origin":"","legend":"\u003cp\u003eAverage panicle diameters under irrigated conditions.\u003c/p\u003e","description":"","filename":"9.png","url":"https://assets-eu.researchsquare.com/files/rs-6931390/v1/d3fe9d1c8ba4657fefdc27e6.png"},{"id":86169559,"identity":"1d176aaa-68dc-41b3-ae5f-6654f9f742c9","added_by":"auto","created_at":"2025-07-07 14:09:46","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":51027,"visible":true,"origin":"","legend":"\u003cp\u003eAverage panicle weights under irrigated conditions\u003c/p\u003e","description":"","filename":"10.png","url":"https://assets-eu.researchsquare.com/files/rs-6931390/v1/d3bf8a534acfa7d076f6d13a.png"},{"id":86171074,"identity":"6d2506ba-6f1a-4c96-a3ce-35c0def40e14","added_by":"auto","created_at":"2025-07-07 14:25:45","extension":"png","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":44475,"visible":true,"origin":"","legend":"\u003cp\u003eAverage weights of 1000 seeds under irrigated conditions.\u003c/p\u003e","description":"","filename":"11.png","url":"https://assets-eu.researchsquare.com/files/rs-6931390/v1/3b7795613b16f079bfa9ee6e.png"},{"id":99315225,"identity":"0f6cab08-3646-446d-8ff5-a9618a06629b","added_by":"auto","created_at":"2025-12-31 16:26:39","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1816934,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6931390/v1/27d74f2d-5c14-45ef-8ced-d62819ed6d55.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Agro-morphological characterization of Mauritanian Sorghum ''Sorghum Bicolor (L.) Moench'' accessions and selection for their tolerance to water stress","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003ePlants are exposed to different types of abiotic stress that unbalance cellular homeostasis and cause changes at different levels in plants: morphological, physiological, and molecular Bian et al (2017). These modifications have a negative influence on the different phenological phases of the plant, such as survival, biomass production, and grain yield Boyer (1982). Agricultural production in several regions of the world is affected by abiotic stresses caused by global warming. Drought is one of the major stresses that considerably affects plant growth and development and limits crop productivity by affecting its capacity to absorb nutrients from the soil and the mobilization and transport of nutrients Yu et al (2015) and Sarshad et al (2021).\u003c/p\u003e \u003cp\u003eIn sub-Saharan Africa, drought is often associated with very high temperatures, the combined effect of which considerably reduces crop productivity Hale et al (1987), particularly in rain-fed agricultural systems. These stresses are set to worsen in the coming years, with several climate models predicting increases in surface temperatures and drought episodes between now and Cambridge, (2007), raising further concerns about global food security Nelson et al (2009). Hence the need for drought-adapted plants to improve crop breeding for water stress tolerance Vinocur et al (2005).\u003c/p\u003e \u003cp\u003eMauritania is one of the Sahel countries most affected by periods of drought. The country was hit by repeated droughts in the 1970s and 1980s as a result of climate change. The area of arable land exposed to at least one drought per year will increase from 6% in 2000 to 10% in 2080, and the range of probability of annual exposure of arable land to drought will widen from 0.3\u0026ndash;19% in 2000 to 0.6\u0026ndash;36% in 2080.\u003c/p\u003e \u003cp\u003eAgricultural production in Mauritania is essentially rainfed food production. The dominant staple crops are cereals, especially sorghum, as well as rice, maize, cowpea, and millet McCann (2015). Mauritania is subject to strong seasonal and annual variations in rainfall as well as recurrent droughts, which are major problems for agricultural production Sissoko et al (2011), Ozeret al (2014). A national action program for adaptation to climate change in Mauritania (2004) has shown that the drop in rainfall has led to a massive reduction in water resources and vegetation, aggravating land degradation and desertification, which in turn has led to the loss of arable land and a reduction in agricultural production, as well as the loss of grazing land and the depletion of livestock. This has led to an increase in poverty in rural communities, resulting in a mass exodus to urban centers. While only 27% of Mauritania's population was urban in 1980, this rate has more than doubled to 55% in 2019 (World Development Indicators, 2019). In developing countries and semi-arid and arid tropical regions, sorghum is a major staple crop for more than half a billion people. It provides protein-rich, fiber-rich, and gluten-free nutrition Assefa et al (2010) Albouchi et al (2000). In addition to human nutrition, sorghum is also used as a source of feedstock for bioethanol production Mathur et al (2017), even though sorghum is considered to be a drought-tolerant crop and remains productive under low-input conditions, water deficit affects its capacity to absorb nutrients from the soil and the mobilization and transport of nutrients Chaves et al (2002), Jafar et al (2004) The main abiotic stress facing sorghum in production areas is water stress Queiroz et al (2019).\u003c/p\u003e \u003cp\u003eGenetic improvement for drought tolerance has proved to be the most cost-effective approach to improving agricultural productivity. However, this requires a broad genetic base and extensive information on available genetic resources. Thus, understanding plant responses to drought and selecting plants for increased drought tolerance are two major objectives of the studies.\u003c/p\u003e \u003cp\u003eVery little is known about local sorghum genetic resources in Mauritania. It is in this context that we undertook this study on a set of local sorghum accessions from four Mauritanian regions, namely Hodh el Chargui, Hodh el Gharbi, Assaba, and Guidimagha, with the aim of :\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eTo explore phenotypic variability in all accessions.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eAgro-morphological characterization of this local plant genetic resource.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eTo study the behavior of these local accessions about water stress.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cp\u003e\u003cstrong\u003e2.1.\u0026nbsp;Plant material:\u0026nbsp;\u003c/strong\u003eThe trial involved a collection of local ecotypes from the 4 regions of Mauritania, namely: Hodh el Chargui (H-C), Hodh el Gharbi (H-G), Assaba, and Guidimagha. The final list of ecotypes tested included 15 sorghum ecotypes\u0026nbsp;Table 1.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 1:\u0026nbsp;\u003cstrong\u003eList of plant materials tested\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cimg width=\"604\" height=\"506\" src=\"data:image/emf;base64,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\" alt=\"image\"\u003e\u003c/p\u003e\n\u003cp id=\"_Toc30447635\"\u003e\u003cstrong\u003e2.2.\u0026nbsp;Setting up the trial\u003c/strong\u003e\u003cstrong\u003e:\u0026nbsp;\u003c/strong\u003eTo protect the crops, the trial began with the installation of a wire fence, reinforced with barbed wire, followed by soil preparation and the installation of a drip irrigation system. Sowing was then carried out according to the predefined experimental setup.\u0026nbsp;\u003c/p\u003e\n\u003cp id=\"_Toc30447636\"\u003e\u003cstrong\u003e2.3.\u0026nbsp;Experimental set-\u003c/strong\u003e\u003cstrong\u003eup:\u003c/strong\u003e The experimental set-up consisted of two blocks: irrigated and rain-fed blocks. Each variety is represented by a line of 20 plants with two replicates for each treatment (Figure 1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.4.\u0026nbsp;Crop management\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.4.1.\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Soil tillage\u003c/strong\u003e l: A disc plow is used to plow the soil to a depth of 40 cm, followed by offsetting to break up the large clods and leveling to prepare the seedbed and prevent water stagnation.\u003c/p\u003e\n\u003cp id=\"_Toc30447640\"\u003e\u003cstrong\u003e2.4.2.\u0026nbsp; \u0026nbsp; \u0026nbsp; Fertili\u003c/strong\u003e\u003cstrong\u003ezation\u003c/strong\u003e: Fertilisation is limited to a base fertilizer in the form of organic manure (manure) at a rate of 5T/ha to simulate farmers\u0026apos; cropping conditions.\u003c/p\u003e\n\u003cp id=\"_Toc30447641\"\u003e\u003cstrong\u003e2.4.3.\u0026nbsp; \u0026nbsp; \u0026nbsp; Irrigation\u003c/strong\u003e: To prevent irregular rainfall and ensure the success of the crops for characterization data, we opted to irrigate one of the blocks. A drip irrigation system was chosen to save water and minimize weed growth. The second block was run under rainfed stress to get closer to the farmers\u0026apos; actual growing conditions.\u003c/p\u003e\n\u003cp id=\"_Toc30447642\"\u003e\u003cstrong\u003e2.5.\u0026nbsp;Crop monitoring and maintenance\u003c/strong\u003e\u003cstrong\u003e:\u0026nbsp;\u003c/strong\u003eAfter the trial was set up, crops were regularly monitored and maintained. Monitoring and maintenance included irrigation, weeding, hoeing, ridging, phytosanitary treatment where necessary, and covering the ears to protect them from granivorous birds.\u0026nbsp;\u003c/p\u003e\n\u003cp id=\"_Toc30447643\"\u003e\u003cstrong\u003e2.6.\u0026nbsp;Data collection and processing\u003c/strong\u003e\u003cstrong\u003e:\u0026nbsp;\u003c/strong\u003eData collection sheets were drawn up by the experimental protocol and used to collect the data. Four plants per ecotype and block were randomly selected and marked to monitor the parameters studied. \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp id=\"_Toc30447644\"\u003e\u003cstrong\u003eParameters studied\u003c/strong\u003e\u003cstrong\u003e:\u0026nbsp;\u003c/strong\u003eThe characterization of the local ecotypes tested focused on a set of parameters that can be subdivided into three types, namely growth parameters, phenological parameters, and yield parameters.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.6.1.\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Growth parameters :\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMonitoring and growth measurements concerned the following parameters :\u003c/p\u003e\n\u003cp\u003eNumber of leaves (NbrL), length of the third Leaf (LTl), width of the third Leaf (WTL),\u003c/p\u003e\n\u003cp\u003ePlant height (Ph), number of tillers (NbrT), and length of internodes (L. In). These parameters were monitored and evaluated during the vegetative growth phase, up to the start of heading and flowering.\u0026nbsp;\u003c/p\u003e\n\u003cp id=\"_Toc30447646\"\u003e\u003cstrong\u003e2.6.2.\u0026nbsp; \u0026nbsp; \u0026nbsp; Phenological parameters\u003c/strong\u003e\u003cstrong\u003e:\u003c/strong\u003e Phenological parameters are represented by the duration of heading (D. heading), calculated as the number of days between the sowing date and the date of 50% heading. \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n\u003cp id=\"_Toc30447647\"\u003e\u003cstrong\u003e2.6.3.\u0026nbsp; \u0026nbsp; \u0026nbsp; Yield parameters\u003c/strong\u003e: The grain yield of the ecotypes studied was assessed using the parameters panicle length (pa.L), panicle diameter (paDi), panicle weight (PaW), and 1000-seed weight (P1000g). \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp id=\"_Toc30447648\"\u003e\u003cstrong\u003e2.7.\u0026nbsp;Data processing\u003c/strong\u003e\u003cstrong\u003e:\u0026nbsp;\u003c/strong\u003eAll the data were analyzed using SPSS version 22 software :\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eA descriptive analysis was carried out to determine the minima, maxima, means, standard deviations, and variances of the various parameters studied.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAn analysis of variance (5%) was carried out to assess the effects of treatment (irrigated-pluvial) and variety (ecotype) on the variation in the parameters studied.\u003c/p\u003e\n\u003cp\u003eA comparison of the averages of the different ecotypes tested was carried out, as well as a correlation analysis of the different parameters studied. \u0026nbsp; \u0026nbsp;\u003c/p\u003e"},{"header":"3. RESULTS","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Growth parameters\u003c/h2\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003e3.1.1. Descriptive analysis\u003c/h2\u003e \u003cp\u003eThe results of the descriptive analysis for irrigated and rainfed vegetative growth parameters are presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDescriptive analysis results for growth parameters for 36 sorghum ecotypes grown under irrigated and rainfed conditions.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eParameter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBeach\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMinimum\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMaximum\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eAverage\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eStandard deviation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eVariance\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStatistics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStatistics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eStatistics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eStatistics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eStatistics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eError std.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eStatistics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eStatistics\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNumber of leaves (\u003c/b\u003eNbrL\u003cb\u003e)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e288\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e18,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10,547\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e,1232\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2,0912\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e4,373\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLeaf width (LW cm)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e288\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e12,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7,411\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e,1094\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1,8573\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3,449\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLeaf length (Ll cm)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e288\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e98,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e98,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e64,530\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e,8287\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e14,0643\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e197,803\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePlant height (Ph cm)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e288\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e360,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e360,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e98,250\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5,3017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e89,9724\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e8095,024\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLength of internodes (L. In cm)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e288\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e30,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9,755\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e,5156\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e8,7493\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e76,550\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eD.In cm\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e288\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e19,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5,833\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e,3254\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5,5216\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e30,488\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNbrT\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e288\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e,372\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e,0506\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e,8579\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e,736\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe descriptive analysis shows a wide variability within the heritage studied, with ranges varying from 5 for the number of tillers to 360 for plant height. The leaf length and plant height parameters show the greatest variability, with standard deviations of 14.06 cm and 89.9 cm and a mean of 64.53 cm and 98.25 cm, with a minimum of 0 and a maximum of 98 cm and 360 cm respectively. However, the number of leaves and leaf width parameters showed low variability with standard deviations of 2.091 and 1.857 cm and a mean of 10.547 and 7.411 cm; a minimum of 0 and a maximum of 18 and 12 respectively. This wide variability predicts the possibility of selection within the plant material studied.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003e3.1.2. Analysis of variance for growth parameters\u003c/h2\u003e \u003cp\u003eThe results of the analysis of variance are presented in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAnalysis of variance results for growth parameters\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSource of variation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDependent variable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSum of type III squares\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eddl\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMedium square\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eMeaning\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"6\" rowspan=\"7\"\u003e \u003cp\u003e\u003cb\u003eTreatment\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber of leaves (NbrL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25,383\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e25,383\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e13,821\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e,000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLeaf width (LW cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e67,570\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e67,570\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e45,690\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e,000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLeaf length (Ll cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6109,730\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6109,730\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e57,283\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e,000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePlant height (Ph cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1746580,500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1746580,500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1793,221\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e,000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLength of internodes (L. In cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13250,563\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e13250,563\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1496,779\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e,000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eD.In cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4449,389\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4449,389\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1232,929\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e,000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNbrT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e39,753\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e39,753\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e86,954\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e,000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"6\" rowspan=\"7\"\u003e \u003cp\u003e\u003cb\u003eVariety\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber of leaves (NbrL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e566,523\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e16,186\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8,814\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e,000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLeaf width (LW cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e502,461\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e14,356\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e9,707\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e,000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLeaf length (Ll cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17758,405\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e507,383\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4,757\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e,000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePlant height (Ph cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e207455,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5927,286\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e6,086\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e,000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLength of internodes (L. In cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4131,773\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e118,051\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e13,335\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e,000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eD.In cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2033,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e58,086\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e16,096\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e,000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNbrT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e36,372\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1,039\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2,273\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e,000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"6\" rowspan=\"7\"\u003e \u003cp\u003e\u003cb\u003eTreatment * Variety\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber of leaves (NbrL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e266,523\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7,615\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4,146\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e,000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLeaf width (LW cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e100,523\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2,872\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1,942\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e,002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLeaf length (Ll cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9862,926\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e281,798\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2,642\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e,000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePlant height (Ph cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e158854,500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4538,700\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4,660\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e,000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLength of internodes (L. In cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2675,468\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e76,442\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8,635\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e,000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eD.In cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1488,111\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e42,517\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e11,782\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e,000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNbrT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e36,372\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1,039\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2,273\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e,000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe analysis of variance shows highly significant effects (p ˂ 0.01) and an interaction between the treatment (irrigated-pluvial) and the variety (ecotype) on all the parameters studied. This translates into a variable behavior of the ecotypes, for the parameters studied, according to the growing conditions, and confirms the possibility of selection within the plant material in question.\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e: Analysis of variance results for growth parameters\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003e3.1.3. Averages of parameters studied\u003c/h2\u003e \u003cp\u003eOnly 18 of the 36 accessions were analyzed for the parameters studied. This choice was due to the very large volume of data recovered after the analysis, and to better represent, interpret, and draw the right conclusions from the results, we chose to work with the best-performing accessions.\u003c/p\u003e \u003cp\u003e \u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003eNumber of leaves\u003c/span\u003e \u003c/p\u003e \u003cp\u003eThe average values for the number of leaves are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows that the Ras lmouche ecotype recorded significantly more leaves (14) in irrigated and (13) in rainfed conditions, followed by Fella Bodjedou (13) in irrigated and (12) and Bechne laajlan\u0026eacute; which recorded (13) in irrigated and rainfed conditions, and Taghalit lbeyda, Rhaye, Ghil\u0026eacute;, and Beyke have several leaves of (11) but in rainfed Ghil\u0026eacute; and Beyke (12) Bechne Gadiaba recorded the same performance (11) and Nebane is the least performing (9) leaves in irrigated and (10) in rainfed.\u003c/p\u003e \u003cp\u003e \u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003eLeaf length\u003c/span\u003e \u003c/p\u003e \u003cp\u003eThe mean values of leaf lengths are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows that the ecotypes Moussa Sidi recorded significantly the longest leaves in both irrigated and rainfed with a value of 82cm and 80cm respectively followed by Bechna Gadiaba, which recorded a non-significant difference with sidi moussa in irrigated (83cm) but significant in rainfed (73cm) Leghvere, Taghalit lbeyda and recorded significantly higher leaf lengths in rainfed than in irrigated (67cm, 70cm) respectively.\u003c/p\u003e \u003cp\u003e \u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003eLeaf width\u003c/span\u003e \u003c/p\u003e \u003cp\u003eThe average values of leaf widths are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e shows that the accessions Bechne laajlan\u0026eacute;, Bechne gadiaba, and Ras lmouche recorded the same performance for this parameter in irrigated and rainfed conditions, with 9cm, 9cm, and 10cm respectively. In addition, Moussa sidi and CE151 recorded the broadest leaves in irrigated conditions (8cm and 8cm).\u003c/p\u003e \u003cp\u003e \u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003ePlant height at heading\u003c/span\u003e \u003c/p\u003e \u003cp\u003eAverage plant height values are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e Plant height measurements show that only 11 ecotypes were able to reach heading under rainfed conditions. Of these ecotypes, Ghile was significantly taller at 140cm, followed by Taghalit lhamra and Taghalit (126cm), then Djabi wemras (98cm), Thaghalit lbeyda (96cm) and Bechne Aarre (90cm). Ghil\u0026eacute; and Taghalit lhamra as well as Neban\u0026eacute; (96cm) in rainfed conditions. In irrigated conditions, Rhaye (209cm), Taghalit (210cm), and Beyke (211cm) had the longest plants.\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003e \u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003eNumber of tillers\u003c/span\u003e \u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eThe average values for the number of tillers are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThese results show that none of the varieties produced tillers under rainfed conditions. Some accessions such as Taghalit lbeyda, Ghil\u0026eacute;, and Taghalit lhamra as well as Neban\u0026eacute; did not give tillers even under irrigated conditions; and Rhaye gave more tillers than the others with a significantly higher number (4 tillers):\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCorrelations between phenological parameters and yield\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLaF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eHP\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eNF\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePearson correlation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e,163\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e,498**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0,47**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSig (bilateral)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e572\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e572\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e572\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e572\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eLF\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePearson correlation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e,163\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0,394**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0,411**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSig (bilateral)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e572\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e572\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e572\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e572\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eLaF\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePearson correlation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e,498**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0,394**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e,446\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSig (bilateral)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0,034\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e572\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e572\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e572\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e572\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eHP\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePearson correlation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0,47**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0,411**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e,446\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSig (bilateral)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e572\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e572\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e572\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e572\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThis analysis makes it possible to reflect a linear relationship between two continuous variables, with the correlation coefficient varying between \u0026minus;\u0026thinsp;1 and +\u0026thinsp;1, 0 reflecting a null relationship between the two variables, a negative value (negative correlation) meaning that when one of the variables increases, the other decreases; while a positive value (positive correlation) indicates that the two variables vary together in the same direction. The results in this table show highly significant positive correlations between leaf number, leaf length, leaf width, and plant height (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Phenological and yield parameters\u003c/h2\u003e \u003cp\u003eGiven that, almost all the ecotypes did not reach the end of their cycle under rain-fed conditions because of the scarcity of rain during the rainy season in Rosso (cumulative rainfall of less than 100 mm), the phenological and yield parameters will only concern the irrigated block.\u003c/p\u003e \u003cdiv id=\"Sec12\" class=\"Section3\"\u003e \u003ch2\u003e3.2.1. Descriptive analysis for phenological and yield parameters\u003c/h2\u003e \u003cp\u003eThe results of the descriptive analysis for phenological and yield parameters for irrigated sorghum are shown in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDescriptive analysis results for phenological and yield parameters\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBeach\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMinimum\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMaximum\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eAverage\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eStandard deviation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eVariance\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStatistics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStatistics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eStatistics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eStatistics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eStatistics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eError std.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eStatistics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eStatistics\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTime to heading (days)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e53,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e46,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e99,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e74,660\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1,4211\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e17,0533\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e290,813\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLpa (cm)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e37,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e17,552\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e,5387\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e6,4639\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e41,782\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDipa (cm)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e27,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e30,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e10,948\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e,4973\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e5,9672\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e35,607\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePpa (g)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e251,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e256,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e49,028\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2,9381\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e35,2571\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1243,062\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eP1000g (g)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e45,30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e18,70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e64,00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e31,46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e,8913\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e10,69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e114,413\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eDescriptive analysis shows a wide range of variability within the heritage studied, with ranges varying from 27 cm for panicle diameter to 251 g for panicle weight.\u003c/p\u003e \u003cp\u003eThe parameters duration to heading and panicle weight showed greater variability, with respective standard deviations of 17.05 cm and 35.25 g. This wide variability predicts the possibility of selection for these parameters within the plant material studied.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section3\"\u003e \u003ch2\u003e3.2.2. Analysis of variance for phenological and yield parameters\u003c/h2\u003e \u003cp\u003eThe results of the analysis of variance are shown in Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e6\u003c/span\u003e below :\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAnalysis of variance results for phenological and yield parameters\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSource\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDependent variable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSum of type III squares\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eddl\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMedium square\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eMeaning\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e\u003cb\u003eVariety\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTime to heading (days)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e40859,576\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1167,416\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e173,486\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e,000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePaL(cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5461,922\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e156,055\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e32,858\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e,000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePaDI (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4734,172\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e135,262\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e40,841\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e,000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePaW (g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e155005,889\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4428,740\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e21,022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e,000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eP1000g (g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14739,982\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e421,142\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e28,057\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e,000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe analysis of variance shows highly significant effects (p ˂ 0.01) of the variety (ecotype) on all the parameters studied. This shows a variable behavior of the ecotypes for the parameters studied and confirms the possibility of selection within the plant material in question.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section3\"\u003e \u003ch2\u003e3.2.3. Averages of parameters studied\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003e \u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003eTime to heading\u003c/span\u003e \u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003eAverage heading times are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThese results show that the Rhaye (Sidi Nielbe) and Nienikou varieties are the earliest, with a heading period of 45 days, while the N\u0026eacute;ban\u0026eacute; and Bechne Aarre varieties are the latest, with a heading period of around 80 days.\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003e \u003cb\u003ePanicle length\u003c/b\u003e \u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eAverage panicle lengths are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe results in this figure show that the MoussaSidi ecotype has the longest panicle (29cm), followed by Coumba Nday (24cm) and Rhay\u0026eacute; (Sidi nielb\u0026eacute;) (22cm) have the longest panicles. Thaghalit and Taghalit lbayda have the shortest panicles (11 cm).\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003e \u003cb\u003ePanicle diameter\u003c/b\u003e \u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eAverage panicle diameters are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe results in this figure show that the Bechne laajlan\u0026eacute; (17g), Nieniko (16g), and Leghvere (18g) ecotypes have the thickest panicles.\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003e \u003cb\u003ePanicle weight\u003c/b\u003e \u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eAverage values for panicle weights are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe results in this figure show that the same ecotypes Nieniko (61g), Leghvere (66g), and coumbe Nday (69g) are the best in terms of panicle weight.\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003e \u003cb\u003eWeight of 1000 seeds\u003c/b\u003e \u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eThe average weights of 1000 seeds are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e11\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe results in this figure show the same trend for the ecotypes, Bechne Gadiaba, Coumb\u0026eacute; Nday recorded the heaviest seeds with (43g) and leghver significantly better is a panicle weight of (57g).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section3\"\u003e \u003ch2\u003e3.2.4. Correlation between phenological parameters and yield\u003c/h2\u003e \u003cp\u003eThe correlations between the parameters are shown in Table\u0026nbsp;\u003cspan refid=\"Tab9\" class=\"InternalRef\"\u003e7\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCorrelations between phenological parameters and yield\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTime to heading (days)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePaL (cm)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePaDI (cm)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePaW (g)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eP1000g (g)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eTime to heading (days)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePearson correlation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-,338\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e,177\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e,190\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e,399\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSig (bilateral)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e,034\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e,022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e,000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e144\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003ePaL (cm)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePearson correlation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-,338\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-,049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e,003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e,217\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSig (bilateral)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e,562\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e,971\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e,009\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e144\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003ePaI (cm)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePearson correlation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e,177\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-,049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e,659\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e,439\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSig (bilateral)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e,034\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e,562\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e,000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e144\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003ePaW (g)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePearson correlation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e,190\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e,003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e,659\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e,511\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSig (bilateral)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e,022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e,971\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e,000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e144\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eP1000g (g)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePearson correlation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e,399\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e,217\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e,439\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e,511\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSig (bilateral)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e,009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e144\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e**. The correlation is significant at the 0.01 level (two-tailed).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e*. The correlation is significant at the 0.05 level (two-tailed).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThese results show highly significant positive correlations between panicle diameter, panicle weight, and 1000-seed weight: i.e. as panicle diameter increases panicle weight increases, and 1000-seed weight increases. Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e6\u003c/span\u003e also shows that there is a highly significant correlation between the duration of heading and panicle length.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"4. DISCUSSION","content":"\u003cp\u003eLack of water is a limiting factor for plant growth, particularly in arid and semi-arid regions Reiahi et al (2013) The morphological and physiological behavior of a given plant depends on the species or variety, the duration and severity of the drought and the time of its application Morizet et al (1984). Mauritania is located in West Africa in the Saharan desert. It has an arid climate with average annual temperatures of between 21\u0026deg;C and 30\u0026deg;C and total annual rainfall ranging from barely 20 mm on the north coast to 400 mm in the center-south, which has a Sahelian climate CIA World (2020). Crops in Mauritania are mainly rain-fed, and yields are highly dependent on the availability of rainwater. However, agricultural areas are facing greater uncertainty and variability in weather conditions as a result of climate change Sissoko et al (2011), Ozeret al (2014). In response to rising greenhouse gas concentrations, the air temperature in Mauritania is expected to increase by 2.0\u0026deg;C to 4.5\u0026deg;C by 2080 compared with the year 1876 (World Development Indicators, 2019). Several analytical models used to predict the percentage increase in drought indicate that the area of arable land exposed to at least one drought per year will increase by 6\u0026ndash;10% between 2000 and 2080 (CIA World, 2020). Given the increase in drought in recent years and population growth, which is expected to exceed 4.7\u0026nbsp;million in 2020 based on an annual population growth rate of 2.8% World Bank (2020); what is the purpose of this study to select drought-tolerant and productive accessions? Water stress, explained by soil water deficit, is the main abiotic stress seriously affecting crop yields worldwide. Water deficit considerably delays floral initiation and affects panicle development and the appearance of new leaves Ndlovu et al (2021); because it reduces photosynthesis, chlorophyll content, photosynthate translocation, and soil nutrient uptake, resulting in reduced yield quantity and Assefa et al (2010), Kapanigowd an et al (2013) and Sehgal et al (2018). In this experiment, the analysis of the variance of the variables studied showed highly significant differences between ecotypes for the morphological traits studied, which is in agreement with the results of Reiahi et al (2013). The quantitative parameters assessed showed variability between the accessions studied (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The number of leaves per plant (NF) varied from 9 to 14 cm for irrigated and 9 to 13 cm for rainfed. Leaf length varied from 69 to 80 cm for irrigated and 60 to 70 cm for rainfed. Leaf width varies from 6 to 9 cm for irrigated and 5 to 10 cm for rainfed. Analysis of plant height showed that only 11 ecotypes were able to reach heading under rainfed conditions, ranging from 100 to 200 cm for irrigated and 22 to 140 cm for rainfed. The number of tillers obtained varied between 0 and 4 per plant. Our results are higher than those obtained by Allam et al (2018) and lower than those of Koffi et al (2011) but are consistent with those observed by House (1987), who reported that the importance of these parameters varies according to the variety and good water supply. In addition, the accessions have a cycle (sowing - number of days to 50% flowering) that varies from 46 days for the earliest to 99 days for the latest. These results differ from those found by Koffi et al (2011): the earliest flowered at 66 days after sowing and the latest at 119 days. About panicle length and diameter, the results obtained show that these vary, respectively, from 11.25 to 29.87 cm and from 5 to 18.75 cm. These results are higher than those found by Rahal et al (2013) on a genotype originating from Senegal, 'Sergane', with panicles 21.15 cm long and 9.40 cm wide. The results are also consistent with House's (1987) statement that some sorghum panicles can reach 25 cm or more in length and 20 cm or more in width. In addition, Sawadogo et al (2014), found that the main panicles of some varieties are long and wide ranging from 20.7 cm to 51.3 cm and 20 to 23.3 cm, respectively. Panicle weights ranged from 20g to 69g. The weight of 1000 seeds obtained varies from 18 to 55 g. According to Rahal et al (2004) and House (1987), the weight of 1000 seeds can vary from 60 to 85 g for improved varieties. Our values are lower than those of House (1987); but higher than those found by Allam et al (2018) and also those of Koffi et al (2011). In our experiment, we found that there was a significant effect of water stress on yield parameters, as almost all the ecotypes did not reach the end of their rainfed cycle due to the scarcity of rainfall (cumulative rainfall of less than 100 mm). It is in this context that Lal et al (1996), Saccardy et al (1996), and Foyer et al (1998) have shown that if dry sequences do not exceed 10 days, photosynthetic capacity is not affected, so yield can be little affected and recorded in quantities close to the controls. These results are similar to those of Falalou et al (2005) on two cowpea varieties.\u003c/p\u003e \u003cp\u003eMore specifically, the results of this work show that there is great diversity between the accessions for the parameters studied, as different behaviors of the accessions were observed. For example, for growth parameters, it was observed that some accessions performed better in irrigated than in rainfed conditions; others performed equally well in the treatments, such as Taghalit lhamra, Taghalit lbeyda, Ghil\u0026eacute;, Ras lmouch, and Beyke, and others performed poorly in both treatments. The Rhaye (Sidi Nielbe) and Nienikou varieties are the earliest, with a heading period of 45 days, while the N\u0026eacute;ban\u0026eacute; and Bechne Aarre varieties are the latest, with a heading period of 80 days. In terms of panicle length, Moussa Sidi, Coumba Nday, and Rhay\u0026eacute; (Sidi nielb\u0026eacute;) have the longest panicles, while Thaghalit and Taghalit lbayda have the shortest. The Bechne laajlan\u0026eacute;, Nieniko, and Leghvere ecotypes have the thickest panicles. The results in this figure show that the Nieniko, Leghvere, and coumbe Nday ecotypes have the highest panicle weight. The ecotypes, Bechne Gadiaba, Coumb\u0026eacute; Nday recorded the heaviest seeds with and leghver significantly better in panicle weight.\u003c/p\u003e"},{"header":"5. CONCLUSION","content":"\u003cp\u003eIn conclusion, the agro-morphological characterization of the different accessions from the regions of Hodh el Chargui, Hodh el Gharbi, Assaba, and Guidimagha showed that local sorghum accessions display a high degree of agro-morphological variability, reflecting genetic variability. This diversity seems to ensure that local accessions have the potential to adapt to variable growing conditions, such as water stress, and more generally to climate change. Analysis of the variance in agro-morphological parameters showed a highly significant effect of water stress on the various parameters studied. This analysis also showed a highly significant effect of the accession on the variability of the parameters, which gives an idea of the significantly variable behavior of these accessions about water stress and the possibility of using these resources for water stress tolerance. The Taghalit lhamra, Taghalit lbeyda, Ghil\u0026eacute;, Ras lmouch, and Beyke ecotypes performed similarly under rainfed and irrigated conditions in terms of vegetative growth, and can therefore be used as fodder crops since they manage to produce biomass despite the stress. On the other hand, the Rhaye (Sidi nielbe) and Nienikou ecotypes are the earliest with a heading period of 45 days, and the Nieniko, Leghvere, Rhaye (Sidi nielbe), and coumbe Nday ecotypes are the best in terms of yield parameters. These accessions can be used by farmers when conditions are favorable for cultivation, as they have a short cycle and yield well. Specifically, the results of this work show that: Local accessions show a wide variability in the agro-morphological parameters studied. This reflects a richness that can be explored in varietal improvement.\u003c/p\u003e \u003cp\u003eThis study should be supplemented by other parameters:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eCarry out physiological studies.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eThe phenological and yield factors that were predicted in this study could not be achieved because the stress applied was rather severe.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eIntroduce other parameters such as percentage recovery, abscisic acid levels, and other physiological parameters.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003e- Extended to other accessions from different regions of Mauritania where sorghum is grown.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e F.A.S wrote the paper. S.M.M.M, and Z.T developed conceptual ideas, designed the study and examined the document. M.M conducted statistical analysis. Z.T, contributed to the analysis of Data .M.M and Z.T revise the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003eThis research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003eThe authors declare no conflict of interest\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Publish declaration:\u0026nbsp;\u003c/strong\u003enot applicable\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eD\u0026eacute;claration de consentement \u0026agrave; participer\u0026nbsp;\u003c/strong\u003e: non applicable\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics declaration:\u0026nbsp;\u003c/strong\u003enot applicable\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAlbouchi A., Sebei H., Mezni M. Y. \u0026amp; EL Aouni M. H., 2000. Influence of the duration of deficient water supply on biomass production, transpiring surface, and stomatal density of Acacia cyanophylla. Annales de l\u0026apos;INRGREF. 4 : 138- 61p.\u003c/li\u003e\n\u003cli\u003eAllam, Abdelkader, A\u0026iuml;ssa Tirichine, Habib Madani and Wiam Benlamoudi. 2018. Morphological variability of sorghum (Sorghum bicolor L. Moench), grown in the Oued Righ valley (South-East Algeria). Lebanese Scientific Journal, 19(1): 10-18.\u003c/li\u003e\n\u003cli\u003eAssefa Y, Staggenborg SA, Prasad VPV (2010) Sorghum water requirement and responses to water stress: a review. Crop Management 9(1):1-11. \u003c/li\u003e\n\u003cli\u003eBian, YW; Deng, X.; Yan, X.; Zhou, JX; Yuan, LL; Yan, YM Integrated proteomic analysis of roots and leaves of Brachypodium distachyon reveals a synergistic network in response to water stress and recovery. Sci. Rep. 2017, 7, 46183.\u003c/li\u003e\n\u003cli\u003eBoyer, JS Productivity and the factory environment. Sciences 1982, 218, 443-448. \u003c/li\u003e\n\u003cli\u003eCIA World Factbook, \u0026quot;Mauritania,\u0026quot; 2020. Available online at https://www.cia.gov/library/publications/the-world-factbook/geos/ mr.html [Accessed: 29-Jun-2020].\u003c/li\u003e\n\u003cli\u003eChaves, M.M.; Pereira, J.S.; Maroco, J.; Rodriques, M.L.; Ricardo, C.P.P.; Osorio, M.L. Carvatho, I.; Faria, T. and Pinheiro, C.; 2002. How plants cope with water stress in the field photosynthesis and growth ? Ann. Bot. 89: 907-\u003c/li\u003e\n\u003cli\u003eFalalou H., Dicko MH, Zombr\u0026eacute; G, Traor\u0026eacute; AS, Guinko S. 2005. Adaptive response of two cowpea varieties to water stress. Cahiers Agricultures; 14 (6): 651 - 567.\u003c/li\u003e\n\u003cli\u003eFoyer, C.H. ; Valadier, M.H. ; Migge, A. and Becker, T.W. ; 1998. Drought-induced effects on nitrate reductase activity and mRNA and on the coordination of nitrogen and carbon metabolism in maize leaves. Plant Physiology, 117: 283- 292.\u003c/li\u003e\n\u003cli\u003eIPCC. Summary for Policymakers. 7-22 (Cambridge, 2007).\u003c/li\u003e\n\u003cli\u003eHale, MG, Orcutt, DM and Thompson, LK Plant physiology under stress (Wiley, New York, 1987).\u003c/li\u003e\n\u003cli\u003eHouse, L. R. 1987. Manual for sorghum breeding. Second edition, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Andhra Pradesh, India. 229 pp.\u003c/li\u003e\n\u003cli\u003eImpa SM, Perumal R, Bean SR, Sunoj VSJ, Jagadish SVK (2019) Water deficit and heat stress-induced alterations in grain physicochemical characteristics and micronutrient composition of field-grown grain sorghum. J Cereal Sci 86:124-131.\u003c/li\u003e\n\u003cli\u003eIslamic Republic of Mauritania, \u0026quot;National Adaptation Programme of Action to Climate Change,\u0026quot; Nouakchott, Mauritania, 2004.\u003c/li\u003e\n\u003cli\u003eJafar MS, Nourmohammadi G, Maleki A (2004) Effect of water deficit on seedlings, seedlings and compatible solutes of forage Sorghum cv. Alimentation rapide. In: Proceedings of the 4th International Congress of Agricultural Sciences Brisbane, Austria\u003c/li\u003e\n\u003cli\u003eKapanigowda MH, Perumal R, Djanaguiraman M, Aiken RM, Tesso T, Prasad PVV, Little CR (2013) Genotypic variation in sorghum [ Sorghum bicolor (L.) Moench] exotic germplasm collections for drought and disease tolerance. Springer plus.\u003c/li\u003e\n\u003cli\u003eKoffi, K. Germain, C., Akanvou, L., Akanvou, R., Zoro, B. I. A., Kouakou C. K. and N\u0026apos;da H. A. 2011. Morphological diversity of sorghum (Sorghum bicolor L. Moench) grown in northern C\u0026ocirc;te d\u0026apos;Ivoire. Revue Ivoirienne des Sciences et Technologie, 17: 125-142. \u003c/li\u003e\n\u003cli\u003eK. Sissoko, H. van Keulen, J. Verhagen, V. Tekken, and A. Battaglini, \u0026quot;Agriculture, Livelihoods and Climate Change in the West African Sahel,\u0026quot; Reg. Environ. Chang, vol. 11, no. 1, pp. 119-125, 2011. 11\u003c/li\u003e\n\u003cli\u003eLal, A. and Edwards, G.E. ; 1996. Analysis of inhibition of photosynthesis under water stress in the C4 species Amaranthus cruentus and Zea mays : electron transport, CO2 fixation and carboxylation capacity. Functional Plant Biology, 23: 403-412\u003c/li\u003e\n\u003cli\u003eMathur S, Umakanth AV, Tonapi VA, Sharma R, Sharma MK (2017) Sweet sorghum as a biofuel feedstock: recent advances and available resources. Biotechnol Biofuels 10:146.\u003c/li\u003e\n\u003cli\u003eMcCann T, Krause D, Sanguansri P (2015) Sorghum-new gluten-free ingredient and applications. Aust Food 67(6):24-26\u003c/li\u003e\n\u003cli\u003eMorizet, J.; Robelin, M.; Baucher, G.; 1984. Results of 18 years of lysimetric observations in the Limagne climate. Il. \u0026Eacute;tude des relations entre l\u0026apos;eau et la production v\u0026eacute;g\u0026eacute;tale. Agronomie, 4: 407-416.\u003c/li\u003e\n\u003cli\u003eNdlovu E, van Staden J, Maphosa M (2021) Morpho-physiological effects of combined moisture, heat and stress on Sorghum bicolor [Moench (L.)] and its acclimatisation mechanisms. Plant stress.\u003c/li\u003e\n\u003cli\u003eNelson, GC et al. Climate change. Impact on agriculture and costs of adaptation. 32 (International Food Policy Research Institute, Washington, DC, 2009).\u003c/li\u003e\n\u003cli\u003eP. Ozer, Y. C. Hountondji, J. Gassani, B. Djaby, and D. L. F, \u0026quot;\u0026Eacute;volution r\u0026eacute;cente des extr\u0026ecirc;mes pluviom\u0026eacute;triques en Mauritanie (1933- 2010),\u0026quot; XXVIIeme Colloq. Association Int. Climatol, pp. 394-400, 2014. 12\u003c/li\u003e\n\u003cli\u003eQueiroz MS, Oliveira CE, Steiner F, Zuffo AM, Zoz T, Vendruscolo EP, Silva MV, Mello B, Cabra R, Menis FT (2019) Drought stress on seed germination and early growth of maize and sorghum. J Agric Sci 11(2):310-318.\u003c/li\u003e\n\u003cli\u003eRahal-Bouziane, H., Mossab, K., Khelid, M., Kharsi, M. and Hamdi S. 2004. Promising results for a summer cereal from the Adrar oases: Sorghum sp. INRAA, Recherche agronomique, 14:57-64.\u003c/li\u003e\n\u003cli\u003eRahal-Bouziane, H., Semiani, Y., Yahiaoui, S., Oumata, S., Kharsi, M., Nait, Merzoug, S. and Djeddou, R. 2013. Characterization of some traditional Sorghum (Sorghum bicolor L.) genotypes under Mitidja conditions (Algeria). INRAA, Recherche agronomique, 26: 47-58.\u003c/li\u003e\n\u003cli\u003eReiahi N, Farahbakhsh H (2013) Effects of ascorbate and water stress on germination and growth of sorghum seedlings. Int J Agron Plant Prod 4(5):901-910\u003c/li\u003e\n\u003cli\u003eSarshad A, Talei D, Torabi M, Rafiei F, Nejatkhah P (2021) Morphological and biochemical responses of Sorghum bicolor (L.) Moench under water stress. SN Appl Sci. https://doi.org/10.1007/s42452-020-03977-4\u003c/li\u003e\n\u003cli\u003eSaccardy K, Cornic G, Brulfert J, Reyss A. 1996. Effect of drought stress on net CO2 uptake in Zea leaves. Planta, 199: 589-595.\u003c/li\u003e\n\u003cli\u003eSawadogo, N., Nebie, B., Kiebre, M., Kando, P. B., Nanema, R. K., Traore, R. E., Naoura, G., Sawadogo, M. and Zongo, J. D. 2014. Agromorphological characterization of sweet grain sorghums (Sorghum bicolor (L.) Moench) from Burkina Faso. International Journal of Biological and Chemical Sciences, 8(5): 2183-2197.\u003c/li\u003e\n\u003cli\u003eSehgal A, Sita K, Siddique KHM, Kumar R, Bhogireddy S, Varshney RK, HanumanthaRao B, Nair RM, Prasad PVV, Nayyar H (2018) Effects of drought or/and heat stress on seed filling in food crops: impacts on biochemistry, seed yields and nutritional quality. Front Plant Sci 9:1705.\u003c/li\u003e\n\u003cli\u003eVinocur, B. \u0026amp; Altman, (2005) A. Recent advances in engineering plant tolerance to abiotic stress: achievements and limitations. Current. Avis. Biotechnol. 16 , 123-132.\u003c/li\u003e\n\u003cli\u003eWorld Bank, \u0026quot;World Bank Open Data,\u0026quot; 2019. Available online: https://data.worldbank.org [Accessed on: 31-Jan-2020]. \u003c/li\u003e\n\u003cli\u003eWorld Bank, \u0026quot;World Development Indicators,\u0026quot; 2019. Available online: https://databank.worldbank.org/source/worlddevelopment-indicators [Accessed on: 13-Nov-2020].\u003c/li\u003e\n\u003cli\u003eYu SM, Lo SF, Ho THD (2015) Source-sink communication: regulated by cross-signalling of hormones, nutrients and stress. Trends Plant Sci 20(12):844-857. https://doi.org/10.1016/j.tplants.2015.10.009\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Sorgho bicolor local, (Sorghum bicolor), ecotypes, water stress, agro-morphology","lastPublishedDoi":"10.21203/rs.3.rs-6931390/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6931390/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eMauritania is a Sahelian country highly exposed to climate change. Its territory is subject to successive variations in agricultural production caused by several factors, including low and irregular rainfall; deteriorating climatic conditions, and widespread desertification. In addition to these phenomena, which limit agricultural production in Mauritania, yields could fall further as a result of global warming and climate change, which aggravate inappropriate agricultural practices such as over-exploitation of the land, insufficient irrigation, and the advance of the desert. Drought is one of the major constraints that considerably affects the growth and development of plants and limits crop productivity by inducing osmotic stress. It is in this context that this study is being carried out on a set of local accessions of Mauritanian sorghum \u003cem\u003e(Sorghum bicolor)\u003c/em\u003e to explore the phenotypic variability of this heritage and to characterize agro-morphologically this resource under water stress. Morphological, agronomic, and phenological parameters were studied during the project. Analysis of variance showed a highly significant effect of varieties on all morphological parameters. The Rhaye (Sidi nielbe) and Nienikou accessions are the earliest, with a heading period of 45 days, while the N\u0026eacute;ban\u0026eacute; and Bechne Aarre varieties are the latest, with a heading period of around 80 days. The Nieniko, Leghvere, Rhaye (Sidi nielbe), and coumbe Nday ecotypes are the best in terms of yield parameters. The Taghalit lhamra, Taghalit lbeyda, Ghil\u0026eacute;, Ras louche, and Beyke ecotypes performed similarly under rainfed and irrigated conditions in terms of vegetative growth.\u003c/p\u003e","manuscriptTitle":"Agro-morphological characterization of Mauritanian Sorghum ''Sorghum Bicolor (L.) Moench'' accessions and selection for their tolerance to water stress","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-07 14:09:40","doi":"10.21203/rs.3.rs-6931390/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b0517219-e97f-4715-a34b-3cc6750c2add","owner":[],"postedDate":"July 7th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-12-29T04:53:43+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-07 14:09:40","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6931390","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6931390","identity":"rs-6931390","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}