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International Research Journal of Plant Science

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Research - International Research Journal of Plant Science ( 2023) Volume 14, Issue 4

Sorghum bmr6 and bmr12 lines may provide new forage opportunities in West Africa.

Ousmane Seyni Diakite1*, Daniel K. Dzidzienyo2, Abdoul Kader M. Soulé1, Housseini Baba Haoua1, Niaba Teme1, Danquah Eric2, Tongoona Pangirayi2 and Mitchell Tuinstra3
 
1National Institute of Agronomic Research of Niger (INRAN) Niger, Niamey, West Africa
2West Africa Centre for Crop Improvement (WACCI), University of Ghana, Accra Ghana, Ghana
3Purdue University, West Lafayette, Indianapolis, USA
 
*Corresponding Author:
Ousmane Seyni Diakite, National Institute of Agronomic Research of Niger (INRAN) Niger, West Africa, Email: dseyni@wacci.ug.edu.edu, o.seyni@yahoo.fr

Received: 07-Aug-2023, Manuscript No. 110112; Editor assigned: 09-Aug-2023, Pre QC No. 110112; Reviewed: 23-Aug-2023, QC No. 110112; Revised: 25-Aug-2023, Manuscript No. 110112; Published: 30-Aug-2023, DOI: http:/dx.doi.org/10.14303/irjps.2023.26

Abstract

Sorghum stover consisting of stalks and leaves collected from production fields after grain harvest is a significant source of feed for livestock across West Africa. Improving the dry matter yield and the nutritional value of stover from locally-adapted sorghum varieties may contribute to mitigation of animal feed shortages that are common in this region. The Brown midrib (Bmr) Bmr6 and Bmr12 genes were introgressed in two Nigerien elite sorghum varieties for stover improvement. The parental lines and derived progenies were tested in replicated field trials for differences in agronomic performance including grain and stover production. The stover samples were characterized for differences in nutritional characteristics including dry matter, NDF (Neutral Detergent Fiber), ADF (Acid Detergent Fiber), ADL (Acid Detergent Lignin). Statistical analyses indicated highly significant differences among entries for grain yield, fresh stover yield, dry matter yield, and nutrients content. The Bmr genotypes performed well compared with the conventional varieties. El Mota Bmr12 produced 3.0-3.5 tonnes ha-1 for grain yield. Sepon-82 Bmr6 produced 16.5 tonnes ha-1 fresh stover yield and 16.4 tonnes ha-1 dry matter yield. The Bmr genotypes showed improved nutritional values. Promising lines were identified using the Baker’s Standard Deviation method. The introgression of the Bmr genes enhanced the nutritional values of sorghum lines for dual purpose uses for local farmers.

Keywords

Sorghum, Dual purpose, Feed, Brown midrib, Nutritional potential.

Introduction

Forage crop production plays a key role in agricultural productivity in Africa with more than 340 million tons of fibrous crop residues produced each year (Kossila et al., 1985). Sorghum is an important forage crop in the semiarid tropics, especially in drought prone areas where it is hot or dry to grow other crops (Lima et al., 2005). In Niger, cereals stover are a significant source of feed for livestock during the long and dry season, which coincides with shortage of feed for small scale farmers, particularly in the context of limited availability of natural pasture (Diakite et al., 2017).

The stover market is a growing business in Niger (Diakite et al., 2019). Improving stover production and nutritional quality might therefore constitute an additional source of income for local farmers. The CGIAR (2011) estimated that crop residues, especially stover and straw, are increasingly important commodities that significantly increase the overall value of dryland cereals. Stover markets are expanding in the drier, more densely populated areas of West Africa. Furthermore, as the demand for livestock and livestock products increases, so too does the importance of fodder and feed markets.

Crop improvement programs have been initiated in West Africa in increase forage production and quality. The FAO declared that the cereals residues are major forages and sorghum residues were qualified as a valued feed, especially if cut and dried immediately after the heads have been harvested for grain (www.fao.org). In small-scale farming systems, stover is usually harvested and dried after grain harvest. The unchopped stover is further stored and used as livestock feed. FAO (2012) reported that in tropical countries, dairy animals are primarily fed on crop residue based diets with very little green fodder/hay/silage, which may only be available for a limited time. A participatory rural appraisal conducted in 2016 in three localities in Niger revealed that milking cows, bullocks and then draught animals were the main beneficiaries of sorghum stovers (Diakité et al., 2017). However, those stovers were qualified as having low nutritional values by farmers and stover traders. Suharti et al., (2011); Veatch-Blohm, (2007) asserted that low cattle production in developing countries may be caused by inadequate nutrient supply in high-forage based rations. Moreover, Sultan et al., (2011) reported that crop residues as dry roughages from cultivated grain are rich in fiber and low in nitrogen, minerals and vitamins. Decreased nitrogen and digestibility and increased fiber and lignin contents are common in forages harvested after grain production (Sultan et al., (2011).

Several studies have reported on the digestibility of stovers. Akinola et al., (2015) affirmed that the cereal crop residues’ potential as livestock feed is enormous if appropriate methods of improving their nutritive value are used. Gerhardt et al., (1994). & Oliver et al., (2004) reported that forage sorghum digestibility can be significantly improved with the use of Bmr genes.

Sorghum constitutes an important forage crop for grazing dairy cows. Some studies have demonstrated that silage from Bmr sorghum, with or without protein supplements, significantly increases the milk production of lactating cows (Cherney et al., 1991; Oba & Allen, 1999) and animal performance. These properties make the use of Bmr sorghum for cattle feeding very attractive in many countries. A trial using Bmr sorghum for feeding dairy cows in Costa Rica, El Salvador, Nicaragua, Honduras, Guatemala, Panama and Haiti demonstrated superior feed value and contributed to the rapid spread of bmr forage sorghum throughout Central America (INTSORMIL, 2013).

In this study, the Bmr6 and Bmr12 genes were introgressed in two Nigerien elites sorghum varieties by conventional plant breeding (Oliver et al., 2005; Diakité et al., 2018). The main objective of this study was to assess the potential of the new lines for further forage opportunities in Niger. The parent lines and derived progenies were tested in replicated field trials for differences in agronomic performance and nutritional characteristics of the stover.

Materials and Method

Sorghum Genotypes

The Bmr6 and Bmr12 mutations (Porter et al., 1978); Singh et al., (2011) were crossed to open pollinated varieties El Mota and Sepon-82 from Niger to produce breeding populations. Brown midrib progeny in each population were self-pollinated and advanced by pedigree breeding to the F6 generation with selection for the Brown midrib trait. Ten Bmr12 progeny from the El Mota population (BCS1), six Bmr6 progeny from the Sepon-82 (BCS2) population, Two Bmr12 progeny from the Sepon-82 (BCS3) and six checks including the recurrent and Bmr donor parents and one local landrace variety were evaluated in field trials in 2021.

Field Trial

The field trial was conducted during the rainy season in 2021 at the INRAN research farm at Kollo, NIGER 2°18'07.8’’ East; 13°20'09.3’’ North. The experimental design was an alpha lattice with three replications. Every entry was sown on 3 rows. The row length was 3 m and the sowing density was 0.80 m between rows and 0.50 m between hills on the row (0.80 m x 0.50 m). The standard cultural practices were performed. All phenotypic data were collected on plants in the middle row. After thinning, three plants were retained in every planting hill. Grain yield, fresh stover yield, and dry stover yield were determined on the center row of every plot for every family. Stover samples (leaves + stems) of every entry were collected at maturity after the panicles were harvested for nutrient content analysis. Sorghum plants were cut at ground level, and the collected stover samples were dried for two months on shelves in a shaded areas. The stover quality analyses included dry matter, NDF (Neutral Detergent Fiber), ADF (Acid Detergent Fiber), and ADL (Acid Detergent Lignin) contents using the sequential filter bags method of the ankom technology for the last three elements (Table 1).

Table 1: Phenotypic and nutrient content variables.

Phenotypic data Nutritional data
Grain yield Dry matter
Fresh stover yield Neutral Detergent Fiber
Dry matter yield Acid Detergent Fiber
  Acid Detergent Lignin

Statistical Analysis

Analyses of Variance (ANOVA) were performed with R 3.4.1 environment for statistical computing using PBIB. test function (package ‘agricolae’) for the alpha design analysis of variance and the least significant difference (LSD) using the linear model as follow:

plant-science

Where; Yijl = value of the observed trait; ti = treatment effect and (I = 1…100); rj = replication effect and (j = 1..3); b = block within replicate effect and (j = 1…10); e = random error

Elites lines selection was performed using the Baker’s Standard Deviation for multi traits selection method (BSD). Grain, fresh stover and dry matter yields were estimated according to Mark and Todd (1986) using the below formula:

plant-science

Where plant-science is the sum of mean of the ith trait andplant-science is the phenotypic standard deviation of the ith mean

Results

Phenotypic variables

The ANOVA revealed significant variation in grain yield, fresh stover yield, and dry matter yield among the varieties (Table 2). Comparisons of performance among the Brown midrib progenies and checks indicated that the El Mota Bmr12 progenies were similar or performed slightly better than the Sepon-82 Bmr6 progenies and check genotypes for GY (Table 3). The performance of the Sepon-82 Bmr6 progenies was more competitive with the El Mota Bmr12 progenies for FSY and DSY (Table 3) with most of the Brown midrib progeny exhibiting similar performance.

Table 2: Mean squares of bmr families, parental lines and the check.

Variables SOV Df Mean Sq Pr(>F)  
Grain_Yield VAR 23 1612700 0.000 ***
Replicates 2 1556977 0.017 *
Replicates/Blocks 4 470479 0.268  
Residuals 42 349300    
Fresh stover yield VAR 23 296777572 0.000 ***
Replicates 2 457871046 0.000 ***
Replicates/Blocks 4 238716966 0.005 **
Residuals 42 55641562    
Dry matter yield VAR 23 4,2345 0.000 ***
Replicates 2 4,6522 0.014 *
Replicates/Blocks 4 5,7123 0.000 ***
Residuals 42      

Table 3 : bmr, parental lines and check performance par variable.

VAR GY (t/ha) Groups VAR FSY (t/ha) Groups VAR DMY (t/ha) Groups
El Mota bmr12‐88 3,505 a Local check 52,167 a Local 17,611 a
El Mota bmr12‐102 3,430 ab Sepon‐82 bmr6138 46,528 ab Sepon‐82 bmr6‐138 16,399 ab
El Mota bmr12‐92 3,373 ab Sepon‐82 bmr6‐201 39,722 abc El Mota bmr12‐102 12,644 abc
El Mota bmr12‐95 3,335 abc El Mota bmr12‐102 37,778 abcd EL Mota 12,593 abc
El Mota bmr12‐60 3,331 abc El Mota bmr12‐66 36,528 abcd Sepon‐82 bmr12‐210 12,338 abc
El Mota bmr12‐82 3,163 abc Sepon‐82 bmr6‐199 36,389 abcd Sepon‐82 bmr6‐199 12,009 abc
El Mota bmr12‐71 3,113 abcd El Mota bmr12‐71 34,306 abcd Sepon‐82 bmr12‐192 11,817 abcd
El Mota bmr12‐18 3,036 abcd Sepon‐82 bmr6‐145 33,944 abcd El Mota bmr12‐66 11,698 abcd
Sepon‐82 bmr6‐203 2,854 abcd Sepon‐82 bmr12‐210 33,750 abcd Sepon‐82 bmr6‐201 11,256 abcd
El Mota bmr12‐66 2,533 abcd EL Mota 33,222 abcd El Mota bmr12‐82 11,229 abcd
El Mota bmr12‐68 2,465 abcd El Mota bmr12‐18 32,222 abcd El Mota bmr12‐68 11,201 abcd
Sepon‐82 2,413 abcd Sepon‐82 bmr12‐192 32,139 abcd Sepon‐82 bmr6‐145 11,199 abcd
Sepon‐82 bmr6‐138 2,403 abcd Sepon‐82 31,528 abcde El Mota bmr12‐71 11,032 abcd
EL Mota 2,335 abcd El Mota bmr12‐82 30,139 abcde El Mota bmr12‐18 11,010 abcd
Sepon‐82 bmr6‐145 2,328 abcd El Mota bmr12‐68 29,583 abcde El Mota bmr12‐60 10,648 abcd
Sepon‐82 bmr6‐199 2,301 abcd El Mota bmr12‐95 29,444 abcde El Mota bmr12‐92 10,636 abcd
Sepon‐82 bmr12‐192 2,239 abcd El Mota bmr12‐92 28,889 abcde Sepon‐82 10,401 abcd
Local check 2,205 abcd Sepon‐82 bmr6‐172 28,583 abcde El Mota bmr12‐95 10,029 abcd
Sepon‐82 bmr12‐210 1,792 abcd El Mota bmr12‐60 28,194 abcde Sepon‐82 bmr6‐172 9,561 abcd
Sepon‐82 bmr6‐172 1,535 abcd El Mota bmr12‐88 23,056 bcde El Mota bmr12‐88 8,074 bcd
Tx630 bmr12 1,514 bcd Sepon‐82 bmr6‐203 17,417 cde Sepon‐82 bmr6‐203 5,982 cd
Sepon‐82 bmr6‐201 1,362 cd Tx630 bmr12 16,389 cde Redlan bmr6 5,465 cd
Wheatland bmr12 1,357 cd Redlan bmr6 13,722 de Tx630 bmr12 5,426 cd
Redlan bmr6 1,132 d Wheatland bmr12 6,667 e Wheatland bmr12 2,574 d

Nutrients Content

The ANOVA revealed significant variability between the varieties for dry matter and nutrient contents for ADF and ADL (Table 4) (Figure 1).

Table 4: percentage

Variables SOV DF Mean Sq Pr(>F)  
DM VAR 23 0.78665 0.000 ***
Rep 1 0.03853 0.506  
Block/Rep 1 0.32200 0.063  
Residuals 22 0.08430    
NDF VAR 23 3.1562 0.475  
Rep 1 8.3667 0.113  
Block/Rep 1 2.0301 0.424  
Residuals 22 3.0704    
ADF VAR 23 1.32975 0.006 **
Rep 1 2.21880 0.037  
Block/Rep 1 0.46803 0.319  
Residuals 22 0.45058    
ADL VAR 23 0.40244 0.002 **
Rep 1 0.00521 0.834  
Block/Rep 1 0.01950 0.685  
Residuals 22 0.11586    

Table 4: Mean squares of bmr families, parental lines and the check for their nutrient content.

plant-science-brown-midrib-progeny

Figure 1. Variation in DM, NDF, ADF, and ADL among brown midrib progeny, parental lines and check genotypes.

Elites Lines Selection

The application the Baker’s Standard Deviation for multi traits selection method was used to identify the best performing lines in each population. El Mota Bmr12-88, El Mota Bmr12-102 and El Mota Bmr12-92 were identified as the best performing lines in the El Mota population. Sepon-82 Bmr6-203 and Sepon-82 Bmr6-138 were identified as the best performing lines in the Sepon-82 population (Figure 2).

plant-science-brown-midrib-progeny

Figure 2. Identification of elites lines per population.

Discussion

The objective of this study was enhancement of locallyadapted sorghum varieties through genetic improvement of forage quality using the Bmr6 and Bmr12 mutations. Several El Mota Bmr12 and Sepon-82 Bmr6 lines were developed and identified as having outstanding productivity and nutritional quality. Acquaah (2007) reported that the backcross method of breeding is best suited to improve established cultivars that are later found to be deficient in one or two specific traits. For the case of Bmr type, Oliver et al. (2005) reported that Bmr genes were found to have negative agronomic impact on grain and stover yields in grain sorghum lines but the yield-drag can be overcome with heterosis. Furthermore, the improvement of the stover quality due to Bmr genes increases the potential value of Bmr lines and compensate grain yield-drag. In this view, the CGIAR (2011) reported that the classical target of research has been on increasing the output of grain, while the value of the stover was of secondary interest. High grain yield combined with healthy dry matter stover yields are essential breeding traits for local small-scale farmers. Camara et al. (2006) revealed that characteristics of the variety such as early maturity, less diseases and drought resistance incidences and productivity influenced sorghum and millet adoption by farmers.

In this study, the local check performed better than all the entries for the fresh stover and dry matter yields. Many of the Bmr6 and Bmr12 progenies performed similar to the local check and exhibited excellent nutritional value. High stover yield of local landraces indicates farmers’ varietal preference for varieties with high stover potential and shows the high importance of stover from cereal crops in the country. In addition, Magnan et al. (2012) reported that the importance of crop residue as feed has an implication for farmers’ cereal variety choice. On the other hand, superior varieties with low biomass yield might not be selected by farmers in areas where stover value is high. Vinutha et al. (2017) considered that the important feed traits to be considered for crop improvement should include high biomass yields of good quality forage. The results of the current study are in agreement with those authors. Several Bmr lines performed better than their parental lines in fresh and dry matter yields. Current results are in harmony with Kotasthane et al. (2015) who evaluated Bmr sorghum parental lines and their derivatives for fresh and dry biomass and found some derived lines superior to their parental lines checks. The global forage quality measured by DM, NDF, ADF, and ADL showed variability. The relative highest DM, ADF combined with the low ADL content of the Bmr varieties are in harmony with Dahlberg et al. (2012). In addition, Ouda et al., (2005); Diakite et al (2017) showed that Bmr genotypes had a better degradability and hence nutritive value than the normal genotypes. The high dry matter yields and lower lignin content of Bmr lines over the check and the parental lines confirmed the improvement accomplished. The results of the current study are in agreement with Porter et al. (1978); Strefeler & Wehner (1986) Grant et al. (1995) who suggested that the Bmr mutants of sorghum have significantly lower levels of lignin content than regular sorghum moreover Bmr silage were more digestible because of the lower lignin content.

Conclusion

Crop residues can play a strategic role in maintaining sustainable livestock production systems if high quality of stover is used for feeding. Stover from Bmr varieties can constitute a good alternative for the pressing demand for efficient stover for both quantity and quality to sustain livestock productivity in Niger and West Africa. The Baker’s Standard Deviation for multi traits selection method allowed a clear identification of the superior lines from each genetic background. The Bmr sorghum type exhibited better forage quality and their cultivation in West Africa can provide new and sustainable forage opportunities for farmers.

Acknowledgment

I am grateful to SMIL/USAID for the fundings of this work, Purdue University for proving the bmr genes sources, WACCI for the continuous support. INRAN Niger for the facilities and implication of field technicians throughout this work

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