Trends in Horticulture (2023) Volume 6 Issue 1 doi:10.24294/th.v6i1.2557 Original Research Article Screening and genotyping of groundnut (Arachis hypogea L.) inbred lines and landraces in the North Central Nigeria Olalekan Joseph Olasan1*, Celestine Uzoma Aguoru1, Lucky Osabuohien Omoigui2,3, Iwala Johnson1, Dughdugh Paul1, Solomon Soom Terseer4 1 Plant Biotechnology and Molecular Genetics Unit, Department of Botany, Federal University of Agriculture Makurdi, Makurdi 970212, Benue State, Nigeria. E-mail: olasan.olalekan@uam.edu.ng 2 Department of Plant Breeding and Seed Science, Federal University of Agriculture Makurdi, Makurdi 970212, Benue State, Nigeria. 3 International Institute of Tropical Agriculture, Ibadan 200001, Oyo State, Nigeria. 4 Department of Biological Sciences, Benue State University, Makurdi 102119, Benue State, Nigeria. ABSTRACT The study evaluated 33 accessions of groundnut in the field, consisting of 23 landraces from Nasarawa communities in Nigeria and 10 inbred lines. Assessment entailed the determination of plant survivorship, yield related parameters and pathological indices while genetic diversity study was undertaken using SSR and RAPD molecular markers. Data analysis was done on the Minitab 17.0 software. Significant variability was noted in all traits except in pod sizes, seed sizes and % infected seeds. About 33.3% of the accessions had a survival rate of ≥ 70.0% where 9/10 Inbred lines were found with overall yield (kg/ha) ranging from 4.0 ± 1.6 in Akwashiki-Doma to 516.8 ± 46.9 kg/ha in Samnut 24 × ICGV–91328. Five accessions (15.5%) had pathological indices of zero indicating no traces of any disease of any type and they included one landrace called Agric-Dazhogwa and four Inbred lines: Samnut 25 × ICGV–91317, Samnut 26 × ICGV–19324, Sam- nut 26 × ICGV–91328 and Samnut 26 × ICGV–91319. Coefficients of yield determination R2 by survivorship and patho- logical index were 50.6% and 15%, respectively. A fit model was established (Yield in kg/ha = –146 − 7.94 × Pi + 5.88 × S). Susceptibility to diseases depends on the type of variety (χ2 (32) = 127.67, P = 0.00). Yield was significantly affected by BNR@30 (F = 5.47, P = 0.025, P < 0.05) and DSV@60*RUST@60 interaction effect (F = 4.39, P = 0.044, P < 0.05). The similarity coefficient ranged from 28.57 to 100 in plant morphology. Four varieties had no amplified bands with SSR primers whereas amplified bands were present only in four landraces accessions using the RAPD primer. The dendrogram generated by molecular data gave three groups where genetic similarity ranged from 41.4 to 100.0. The Inbred lines were noted for their high survivorship, good yield and disease resistance. Samnut 24 × ICGV–91328, an inbred line, had the highest yield but was susceptible to diseases. Among the landraces, Agric-Musha, Bomboyi-Dugu and Agric-Dazhogwa were selected for high survivorship and disease resistance. The selected inbred lines and landraces are valuable genetic resources that may harbour useful traits for breeding and they should be presented to the growers based on their unique agronomic values. The highest yielding inbred lines should be improved for resistance to late leaf spot diseases while the outstanding landraces should be improved for yield. Keywords: Groundnut; Inbred Lines; Landraces; Genetic Resources; Improvement ARTICLE INFO 1. Introduction Received: 7 August 2023 Accepted: 30 August 2023 Groundnut (Arachis hypogaea L.) is an important monoecious an- Available online: 21 September 2023 nual legume in the world mainly grown for the oilseed, food and animal COPYRIGHT feed[1]. Groundnut seeds are a rich source of oil (35%–56%), protein Copyright © 2023 by author(s). (25%–30%), carbohydrates (9.5%–19.0%), minerals (P, Ca, Mg and K) Trends in Horticulture is published by En- and vitamins (E, K and B)[2]. Apart from food, groundnuts are used as Press Publisher, LLC. This work is licensed under the Creative Commons At- an important source of income since are sold in the local market as tribution-NonCommercial 4.0 International boiled and shelled roasted nuts while some are sold in the confectionery License (CC BY-NC 4.0). https://creativecommons.org/licenses/by- trade[3]. The haulms are used as livestock feed and in compost making. nc/4.0/ 103 As a legume, groundnut helps to improve soil fer- evaluating some accessions consisting of ground- tility in farming systems by fixing atmospheric ni- nut inbred lines and landraces collected from Na- trogen[3]. The crop is cultivated in more than 100 sarawa State. The outcome would help determine countries under different agro-climatic conditions the level of diversity among the accessions and se- on about 26.5 million hectares with a total produc- lect quality accessions that may be useful to grow- tion of 43.9 metric tons and productivity of 1,654 ers and breeders in the quest to achieve high kg/ha[4]. India is the second largest producer of productivity and food security in line with the UN groundnut and its oil after China followed by USA goal. The aim of the study was to evaluate ground- and Nigeria. It is cultivated on about 3.7 million nut landraces and inbred lines for their agronomic hectares with the production of 6.7 metric tons and values (yield and disease resistance) and assess the 1,810 kg/ha, respectively, during 2015–2016[5]. level of their diversity using molecular markers. In Nigeria, the land area grown to groundnut The specific objectives were to evaluate the plants annually from 2000 to 2009 increased by 2.6% but for survivorship and yield related performances; the yield declined by 3.3% over the same period undertake pathological assessment; select best per- resulting in a stagnation of production at 2.9 mil- forming lines and determine the extent of genetic lion tons[5]. Groundnut is the most important food diversity among them using RAPD and SSR mo- legume in Nigeria in terms of consumption and lecular markers. area under production[6] and is featured promi- nently in the cropping systems of the Savanna and 2. Materials and methods Forest-Savanna transitional agro-ecological zones. 2.1 Study area Its production in Nigeria has nearly tripled in the This research work was carried out at the last decade (168,200 to 420,000 metric tons in Agronomy Teaching and Research Farm, Joseph 2005) primarily due to an increase in the area under Sarwuan Tarka University Makurdi, Benue State, cultivation which increased from 184,400 ha in Nigeria. The research farm is situated along 1995 to 450,00 ha in 2005[4]. Average yields how- Gbajimba Road, just after the School Clinic. Ma- ever continue to remain below 1.0 metric tons/hec- kurdi Local Government Area has a landmass of tare which is far below the potential yield of 2–3 about 16 km in radius[9]. It lies between latitude metric tons/hectares. In West Africa, Nigeria is the 7°43’50’ N 8°32’10’ E and longitude 7.73056° N largest producer of groundnuts with a production 8.53611° E. It has a population of 300,377[10] of 3.07 million tons on about 2.4 million hectares[4] . The . mean annual temperature of the area ranges be- Despite groundnut being an important oil crop tween 22.5 ℃ and 40 ℃ but the temperature is high in Nigeria. However, groundnut production is con- throughout the year while precipitation is about strained by a lack of enough improved groundnut 1,173 mm. The rainfall pattern is from March to varieties, biotic and abiotic stresses. These are the November with variation. The vegetation type in major constraint of groundnut production in Nige- Makurdi is the Guinea Savannah. Makurdi Local ria. The low yield of groundnuts affects small-scale Government is endowed with great investment po- farmers’ livelihoods due to a reduction in house- tentials both in agro-allied and mineral resources. hold income. The use of host resistant varieties is The major occupation of the inhabitants is farming. the most effective, economical and sustainable way to control the disease[7]. Unfortunately, these re- 2.2 Sample collection sistance sources are from late maturing varieties A total of 10 inbred lines were sourced from and poor yielding varieties[8]. Identification of va- the Institute for Agricultural Research (IAR) rieties with combined agronomic qualities such as Samaru, Zaria, Nigeria. Twenty-three (23) land- yield and disease resistance to satisfy farmer’s de- races were collected from local farmers in different mands and value chains for food security and re- communities within Nasarawa State, Nigeria. Alto- gional and local markets is a big challenge. The gether, there were 33 accessions of groundnut used present study was designed to address this gap by in this study (Table 1). 104 Table 1. List of groundnut accessions (landraces and inbred lines) used for the study Accession number Accession name Accession code V1 Chika buhu-Doma CBD V2 Agric-Musha AMU V3 Agric-Agyaragu AAG V4 Agric-Alwaza AAL V5 Chika buhu-Lafia CBL V6 Agric-Kadorko AKA V7 Nada NAD–1 V8 Chika buhu CB–1 V9 Akwashiki-Obi AKO V10 Nada-Isgugu NAD–IS V11 Kpoklo-Gude KPG V12 Agric-Dazhogwa ADA V13 Samnut 25 × ICGV–91317 INBRED LINE–1 V14 Samnut 26 × ICGV–19324 INBRED LINE–2 V15 Samnut 26 × ICGV–91328 INBRED LINE–3 V16 Samnut 22 × ICGV–91324 INBRED LINE–4 V17 Samnut 23 × ICGV–91324 INBRED LINE–5 V18 Samnut 22 × ICGV–91328 INBRED LINE–6 V19 Samnut 26 × ICGV–91319 INBRED LINE–7 V20 Samnut 24 × ICGV–91317 INBRED LINE–8 V21 Samnut 25 × ICGV–91328 INBRED LINE–9 V22 Samnut 24 × ICGV–91328 INBRED LINE–10 V23 Bomboyi-Dugu BOD V24 Agric-Gidiye AGG V25 Kwaya biyu-Kpangwa KWK V26 Agric-Obi AGO V27 Akwashiki-Nene AKN V28 Agric-Dedere ADE V29 Nada-Doma NAD–D V30 Akwashiki-Doma AKD V31 Agric-Duglu AGD V32 Agric-Igbavo AGI V33 Barnada-Zaki-Biam BAZ diseases[11]. Disease incidences were calculated us- 2.3 Experimental design and planting ing standard methods[13]. Characters were assessed After land clearing, the field layout was a ran- using a standard groundnut descriptor guide[14]. domized complete block design (RCBD) with two They include survival rate, pod per plant, pod sizes, replicates and two blocks. Three seeds of each of seeds per plant, seed sizes, % diseased seeds, 100 the 33 accessions were sown as an experimental seed weight, yield per plot (g), yield (kg/ha), unit, replicated twice per block. There were 66 ex- DSV@30/60 (incidence of DSV infection at day 30 perimental units per block. A total of 132 experi- and 60), ELS@30/60 (incidence of early leaf spot mental units were evaluated. Post planting activi- disease), GNR@30/60 (incidence of groundnut ro- ties comprised weeding, fertilizer application, sette disease), LLS@60 (incidence of late leaf spot monitoring and characterization. disease at day 60), TLS@60 (incidence of Tikka 2.4 Field evaluation leaf spot at day 60) and RUST@60 (incidence of groundnut rust disease at day 60). Pathological in- Standard field procedures, guidelines and de- dex (Pi) was calculated as the average of all inci- scriptors as given by Jambunathan[11] and the Inter- dences per accession. national Crops Research Institute for the Semi- Arid Tropics[12] were used in the evaluation of the 2.5 SSR molecular studies 33 accessions of groundnut. Published charts/pic- Twelve SSR primers linked to aflatoxin re- tures were used in the identification of groundnut sistance in groundnut[13] and other reagents such as 105 PRC pre-mix were procured from Genomics Train- Dendrograms were constructed by performing ing Center and Laboratory Limited, Uyo Akwa cluster analysis using the average linkage method. Ibom State, Nigeria. They were stored in the freezer at –20 ℃ at the Molecular Biology Labor- 3. Results atory of the Department of Plant Breeding, Joseph 3.1 Description of groundnut accessions Sarwuan Tarka University Makurdi, Nigeria where the molecular aspect of this study was carried out. A quantitative description of groundnut acces- The forward sequences of selected primers are sions planted in the field is presented in Table 2. given as MP32 (F-AGTGTTGTGTGTGAAAGT- Accessions varied in their characters. Coefficients GG), PM36 (F-ACTCGCCATAGCCAACAAAC) of variation (CV) in plant counts at seedling and and PM42 (F-ACGGGCCAAGTCAAGTGAT). harvesting stages were 35.1% and 38.6%, respec- Two RAPD primers selected from the optimization tively. At both stages, the plant count ranged from process were employed in diversity studies. They 2 to 12 plants. Some accessions failed to produce were OPA–07 (F-GTCAGTGCGG) and OPA–10 pods while maximum pods of 32.5 pods were rec- (F-GGTCACCTCA). orded in some accessions giving an average of 10.40 ± 1.09 pods per plant that measured 3.27 ± 2.6 DNA extraction, amplification, and sep- 0.383 cm. Number of seeds per plant varied from aration 0.2 to 63 seeds. The maximum percentage of in- DNA extraction was done on 14-day-old seed- fected seeds was 18% (18 seeds out of 100) while lings using the CTAB method[15]. The pellet was 100 seed weight was 51.5 g per 100 seeds. Seed suspended in 100 mL of molecular grade wa- sizes had the least CV (12%) while pod sizes had ter/RNase water. The quality was checked using the highest CV (95.25). Significant variation was 0.8% Agarose gel. Polymerase Chain Reaction recorded in mean stand counts at seedling for ac- (PCR) was carried out in a Bio-Rad Thermal cycler cessions (F = 2.48, P < 0.05) where inbred line–5 under the following thermal cycler conditions for had the highest mean count while the block factor PCR reaction, such as denaturation (95 oC) in 30 was also significant (F = 10.97, P < 0.05). The sec, annealing (55–60 oC) in 30 sec, and extension same trend was observed in stand count at harvest. (72 oC). PCR products were made to run on 2.0% The mean number of pods per plant was signifi- agarose gel electrophoresis stained with ethidium cantly different at the accession level only (F = bromide for 40 min. A photographic record was ob- 11.4, P < 0.05) where inbred line–1 had the highest tained under the UV-illumination using a Bench- number of pods. The main effect plot showed five top Trans illuminator with the aid of a digital cam- major and minor peaks above the threshold that ac- era that captured all gel images. counted for the variability in pod production among the accessions (Figure 1). Significant dif- 2.7 Data analysis ferences were recorded in the number of seeds pro- Descriptive analysis was carried out using the duced per plant (F = 2.45, P < 0.05) where inbred Minitab 17.0 application. Two-way ANOVA (anal- line–1 had the highest value. The main effect plot ysis of variance) was used. The Fisher LSD method showed six major and minor peaks above the was used to separate means at a 95% confidence threshold that accounted for the variability in seed limit. The model for groundnut yield was given by production among the accessions (Figure 2). The simple linear and surface response regression 100 seed weight also varied significantly (F = 3.17, methods. A test of dependence was done using the P < 0.05) where inbred lines–1 and 10 were distinct. Chi-square method. DNA bands were scored and Pod sizes, seed sizes and % infected seeds had no converted to binary matrices for both SSR and significant differences among the accessions. RAPD gel images in a separate analysis. 106 Table 2. Description and variability assessment of characters Characters Mean ± S.E CV% Min Max F-variety P-value Pointer Stand count at harvest 8.60 ± 0.409 38.61 2.00 12.00 3.10 0.001 V17 Pod per plant 10.40 ± 1.09 85.46 0.10 32.50 11.14 0.000 V13 Pod sizes (cm) 3.27 ± 0.383 95.19 1.833 28.10 1.03 0.468 NIL Seeds per plant 15.05 ± 1.57 84.54 0.20 63.00 2.45 0.007 V13 Seed sizes (cm) 1.22 ± 0.018 12.03 1.080 2.190 0.90 0.621 NIL % Diseased seeds 6.167 ± 0.385 50.77 1.00 18.000 0.82 0.706 NIL 100 seed weight (g) 25.93 ± 1.81 56.57 0.50 51.50 3.17 0.001 V13, V22 M a in E f fe c ts P lo t fo r N u m b e r o f po d/ p la nt F itte d M e a ns V a r ie tie s R e p 30 25 20 15 10 5 0 Figure 1. Main effects plot for pod per plant. M ain Effe cts P lot for N umbe r of s e eds/ plant F itted M eans Va r ie tie s Rep 40 30 20 10 0 Figure 2. Main effects plot for seed per plant. 3.2 Plant survivorship and pathological in- 6 which performed below this threshold. The best dices accession in survival rate was inbred line–5 with Eleven out of 33 accessions representing 33.3% the value of 93.3%. Inbred line–3 and 8 recorded had a survival rate of ≥ 70.0% (Table 3). All 10 in- 86.7% each. Among the landraces, AMU and BOD bred lines were in this category except inbred line– had survival rates ≥ 70.0% while ADA had the 107 Mean Mean V1 V1 V10 V10 V11 V11 V12 V12 V13 V13 V14 V14 V15 V15 V16 V16 V17 V17 V18 V18 V19 V19 V2 V2 V20 V20 V21 V21 V22 V22 V23 V23 V24 V24 V25 V25 V26 V26 V27 V27 V28 V28 V29 V29 V3 V3 V30 V30 V31 V31 V32 V32 V33 V33 V4 V4 V5 V5 V6 V6 V7 V7 V8 V8 V9 V9 one one two two lowest score (23.3%). Variations in plant survivor- of ELS@30 while 11 (33.3%) showed symptoms. ship and pathological indices are shown in Figures Early leaf spot (ELS) was ≥ 15.0% in inbred line– 3 and 4, respectively. Analysis of pathological pa- 10 and KWK accessions where incidences were rameters showed those accessions that scored ≥ 31.3% and 30.9%, respectively. Late leaf spot 15.0% in disease incidences. At day 30, DSV dis- (LLS@60) recorded high incidences in about 10 ease was not pronounced since all accessions had accessions, the highest being 52.1% in Agric- incidences below the 15% threshold. About 20 out Duglu followed by Nada accessions. In all, 18 of 30 plant accessions (60.6%) showed no symp- (54.5%) showed symptoms of LLS@60. Five ac- toms of DSV@30 while 13 (39.45%) showed cessions (15.5%) had pathological indices of zero symptoms. The frequency of DSV symptomatic indicating no traces of any disease of any type and plants declined at day 60 since only 5 (15.2%) ac- they included one landrace (Agric-Dazhogwa) and cessions showed the symptoms of DSV@30. A to- four inbred lines–1, 2, 3, and 7. Pathological indi- tal of 22 accessions (66.7%) showed no symptoms ces (Pi) were ≥ 5 in 11 (33.3%) accessions. Table 3. Survivorship, pathological indices, and overall yield Accessions Survival rate (S) DSV30 ELS30 DSV60 LLS60 Pathological index (Pi) Yield (kg/ha) CBD 56.7 3 11 4 0 4.5 169.1 ± 29.6 AMU 73.3 0 0 3 26.5* 7.4 34.42 ± 2.92 AAG 43.3 1.5 0 1.5 12.5 3.9 35.2 ± 15.7 AAL 46.7 0 0 3 0 0.8 80.3 ± 11.0 CBL 32 0 0 1.5 10 2.9 48.75 ± 2.08 AKA 40 3 12.8 4 7.2 6.8 41.1 ± 10.8 NAD–1 50 1.5 5 4 34* 11.1 32.3 ± 5.2 CB–1 36.7 0 0 5 20* 6.3 108.4 ± 10.8 AKO 36.7 0 0 1.5 16.7* 4.6 48.5 ± 10.8 NAD–IS 53.3 0 0 4 21.6* 6.4 60.4 ± 10.1 KPG 60 3 7.9 3 0 3.5 76.8 ± 15.7 ADA 23.3 0 0 0 0 0 33.3 ± 10.7 IL–1 70 0 0 0 0 0 466.4 ± 17.8 IL–2 76.7 0 0 0 0 0 481.0 ± 126 IL–3 86.7 0 0 0 0 0 469.4 ± 19.1 IL–4 80 0 0 1.5 0 0.4 144.3 ± 16.6 IL–5 93.3 0 0 1.5 0 0.4 297 ± 22.5 IL–6 46.7 0 0 1.5 0 0.4 52.5 ± 6.7 IL–7 76.7 0 0 0 0 0 377.0 ± 27.0 IL–8 86.7 0 0 1.5 0 0.4 428.4 ± 26.1 IL–9 70 0 0 1.5 0 0.4 404.0 ± 17.0 IL–10 83.3 3.5 31.3* 1.5 0 9.1 516.8 ± 46.9 BOD 76.7 1.5 3.1 1.5 3.4 2.4 57.5 ± 6.5 AGG 43.3 1.5 12.5 4 12.5 7.6 34.4 ± 6.58 KWK 50 3.5 30.9* 5 20* 14.9 22.2 ± 2.3 AGO 56.7 0 0 1.5 11.1 3.2 51.9 ± 11.9 AKN 56.7 1.5 3.4 4 24.3* 8.3 54.8 ± 3.9 ADE 43.3 1.5 3.9 4 11.1 5.1 78.5 ± 15.7 NAD–D 56.7 1.5 0 1.5 10 3.3 74.7 ± 11.2 AKD 26.7 0 0 6 0 1.5 4.0 ± 1.6 AGD 36.7 0 0 6 52.1* 14.5 103.6 ± 6.7 AGI 56.7 0 0 3 12.5 3.9 60.2 ± 5.3 BAZ 66.7 1.5 8.3 3 20* 8.2 73.9 ± 4.9 Note: incidences ≥ 15; Pi ≥ 5 Pearson’s R (survivorship and yield) = 0.711, R2 = 50.6% Pearson’s R (pathology and yield) = –0.386, R2 = 14.9% The regression equation is Yield (kg/ha) = –146 – 7.94 × Pi + 5.8 × S F = 17.7, P = 0.000 (P < 0.05) Key: IL= inbred line 108 Figure 3. Plant survivorship plot. Figure 4. Plant pathological indices. (Pi) (R = –0.4) where the coefficient of determina- 3.3 Plant yield and regression analysis tion R2 was estimated as 15%. The model for yield Overall yield (kg/ha) ranged from 4.0 ± 1.6 in was fit and significant (F = 17.7, P < 0.05). The Akwashiki-Doma to 516.8 ± 46.9 kg/ha in inbred regression equation for yield is given as: Yield line–10. Significant variation was observed in yield (kg/ha) = –146 – 7.94 × Pi + 5.88 × S. Based on the (kg/ha) among varieties (F = 16.04, P < 0.05) and trend analysis plot (Figure 6) for yield, MAPE was between blocks (F = 5.15, P < 0.05). The top five 270.0 while MAD was 135.9. The linear trend high yielding accessions were inbred line–10 (517 model of yield is given as: Yield (kg/ha) = 149.3 + kg/ha), inbred line–2 (481 kg/ha), inbred line–3 0.165 × t. Result shows that plant susceptibility to (469 kg/ha), inbred line–1 (466 kg/ha) and inbred diseases depends on the type of variety (χ2 (32) = line–8 (428 kg/ha). The main effect plot revealed 127.67, P = 0.00) as shown in Figure 7. The ob- eight accessions (24%) whose yields were above served pathological indices were below the ex- the 150 kg/ha benchmark (Figure 5). A strong pos- pected values in all Inbred lines except in inbred itive correlation was established between yield line–10. Landraces including Agric-Alwaza, (kg/ha) and plant survivorship (S) (R = +0.711) Chikabuhu-Lafia, Kpoklo-Gude, Agric-Dazhogwa where the coefficient of determination R2 was esti- Bomboyi-Dugu, Akwashiki-Doma and Agric-Ig- mated as 50.6%. A weak negative relationship was bavo had minimal pathological indices below the established between yield and pathological indices expected values. 109 Main Effects P lot for Y ield (kg/ha) Fitted Means Varieties Rep 500 400 300 200 100 0 Figure 5. Main effects plot for yield. Trend Analysis Plot for Yield (kg/ha) Linear Trend Model Yt = 149.3 + 0.165*t Variable 500 A ctual F its 400 Accuracy Measures MA PE 270.0 MA D 135.9 MSD 26742.4 300 200 100 0 3 6 9 12 15 18 21 24 27 30 33 Inbred lines/landraces Figure 6. Trend analysis for groundnut yield. Note: F (Variety) = 16.04, P = 0.00 (P < 0.050); F (Block) = 5.15, P = 0.030 Chart of Observed and Expected Values 16 Expected Observed 14 12 10 8 6 4 2 0 Category Figure 7. Test of dependency (variety and pathology). Note: χ2 (32) = 127.67, P = 0.00 110 Mean Ptahological index V1 V10 Yield (kg/ha) V11 V12 V13 V14 V15 CBD V16V17 AMU V18 AAG V19 AAL V2V20 CBL V21 AKA V22 NAD-1 V23V24 CB-1 V25 AKO V26 NAD-IS V27V28 KPG V29 ADA V3 HYBRID-1 V30V31 HYBRID-2 V32 HYBRID-3 V33 HYBRID-4 V4V5 HYBRID-5 V6 HYBRID-6 V7 HYBRID-7 V8V9 HYBRID-8 HYBRID-9 HYBRID-10 BOD AGG KWK AGO one AKN ADE NAD-D AKD AGD AGI BAZ two 3.4 Cluster analysis 1–2. The binary plot of multiplex RAPD primers (Figure 9) revealed amplified bands in 29 varieties The 33 accessions were clustered on the basis and while 4 varieties had no bands including Nada- of plant survivorship, pathological parameters and Isgugu, inbred lines–4, 9 and 10. Amplified bands overall yield (Figure 8). Dendrogram gave two were present only in four landraces accessions in- clusters. The first clusters comprised 8 accessions cluding Agric-Musha, Chika buhu-Lafia, Chika- all of which were inbred line where inbred lines–5, buhu and Bomboyi-Dugu. The dendrogram gener- 10 and 8 were distinct accessions. Inbred line–5 ated by molecular data (Figure 10) gave three had the highest survival rate (93.3%). Inbred line– groups among the accessions whose genetic simi- 10 was the best yielding accession (517 kg/ha) larity ranged from 41.4 to 100.0. The first group while inbred line–8 also possessed high survivor- comprised four genetically distinct landraces: ship and high yield with minimal traces of diseases. Agric-Musha, Chika buhu-Lafia, Chika buhu and Similarity coefficient ranged from 28.57 to 100. Bomboyi-Dugu. In the second group, 3 out of the 4 The genomic DNA extracted from groundnut seed- clustered members were inbred lines–4, 9 and 10. lings, the product of the optimization stage and am- The third group comprised 25 accessions, a mix of plified products of the primers are shown in Plates inbred lines and landraces. Dendrogram Average Linkage, Euclidean Distance 28.57 52.38 76.19 100.00 K ADA AKOCBL NAD-1 A KAAGG AAG HYB RI D-6 A KNAGO AGI NAD-ISBA Z NAD-DK PGADE A AL BO D AMU HYB RI D-4 C BD HYB RI D-5 HYB RI D-8 HYB RI D-9 HYB RI D-7 HYB RI D-1 0 HYB R ID -3 HYB R ID -2 HYB R ID -1 AGD CB -1 AKDKW Inbred lines/landraces Figure 8. Dendrogram showing the clustering pattern among accessions. 50 7 8 11 12 5 6 7 8 7 8 11 12 5 6 7 8 50BP 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 BP OPA 07 OPA 10 SSR A SSR 5 OPA 07 OPA 10 SSR A SSR 5 Plate 1. Optimization of primers and protocols. Plate 2. Amplification by SSR, multiplex primer (V1–19). 111 Similarity coefficient Blank Blank Blank Individual Value Plot of RAPD 1.0 0.8 0.6 0.4 0.2 0.0 Figure 9. Binary plot of RAPD amplification. Dendrogram Average Linkage, Manhattan Distance 41.38 60.92 80.46 100.00 D L 1 G 1 2 3 5 6 7 8 CB AAG AA AKA D- AKOKP D- D- D- D- D- D- G K D- O D Z IS -4 -9 10 D L -1 NA ADA RI RI RI RI RI RI AG KW KN E RI AG A AD -DAK AGI BA D- ID ID D- AG AMU CB CB BO D NAD NA BR BR RI HYBHYBHYBHYBHYBHYBHY B HY HY HYB Accessions Figure 10. Dendrogram of molecular data. 4. Discussion reported in some works[21,22], this outcome agrees with other studies reporting high variability in Characters displayed huge variability among groundnut[23,24]. the collections, especially the pod sizes and the Seed infestation due to diseases was high overall grain yield. This finding is in tandem with (18%). This could be interpreted as the presence of previous reports on groundnut that pod and seed 18 contaminated seeds from every 100 seeds har- yield accounted for the highest diversity that vested. There is every possibility that other seeds formed the basis of the selection of superior geno- might be contaminated with time during storage, if types and subsequent improvement of weaker not controlled, because the seeds are packaged to- types[16–18]. The established variability among the gether. Although the sources of the diseases were collections is supported by the low coefficient of not investigated in this work, may be due to patho- similarity ranging from 29 to 100 and 41 to 100 in gens of viral or bacterial or fungal origin. The eco- the phylogenetic analyses of morphological and nomic losses and detrimental health hazards asso- molecular data, respectively. The present investiga- ciated with the consumption of contaminated seeds tion supports previous studies[19,20] on the existence are well documented globally[13,17,25,26]. For exam- of divergent morphological and genetic characters ple, aflatoxin is a common carcinogenic toxin in Arachis hypogea. Unlike the low variability 112 Genetic similarity coefficient Binary operation (0 and 1) produced by a fungus (Aspergillus flavus) that shown from the overall performances. They may causes aspergillilosis when ingested in contami- complement the resilient landraces identified in nated seeds[13,17]. Therefore, the collections should this work including Agric-Musha, Bomboyi-Dugu be investigated further to determine the real causes and Agric-Dazhogwa by initiating a good breeding of seed infestation and identify sources that are sus- programme to achieve high yielding and resilient ceptible and resistant to diseases of health concern. landraces. Apart from Agric-Dazhogwa, notable Also, yield losses can be prevented by cultivating landraces that demonstrated some elements of tol- highly resistant seeds that are resistant to specific erance to diseases include: Agric-Alwaza, Chika diseases. buhu-Lafia, Kpoklo-Gude, Bomboyi-Dugu, The Inbred lines are well adapted to the field Akwashiki-Doma and Agric-Igbavo. The present environmental conditions as revealed in their high study is in agreement with well-established re- survivorship where 9 out of the 11 accessions se- ports[8,29,30] that disease susceptibility depends on lected for high adaptability were all products of the type of plant variety. Hence, the use of host re- groundnut breeding. The two landraces selected for sistant varieties is the most effective, economical their high rate of survival are Agric-Musha and and sustainable way to control groundnut disease[7]. Bomboyi-Dugu. The relationship between plant The present outcome agrees with other au- adaptability as physiological attributes and genetic thors who described the groundnut plant as a crop factors is well established in literature[2]. It can be with a moderate level of character association in inferred that the selected genotypes are vigorous, quantitative traits including yield[24,31,32]. This work highly tolerant to stresses and well suitable for cul- revealed the complexity of yield factor and it has tivation. They could serve as a template for im- further confirmed earlier reports on the complex proving groundnut accessions for tolerance to en- character association of yield and other agronomic vironmental conditions, although some of them are traits[24]. This complexity in yield determination products of ongoing breeding work to achieve cer- may be due to the polygenic nature of the inher- tain specific objectives. Apart from high adaptabil- itance of yield traits since the genes that control ity, the inbred lines were noted for disease re- genes and disease resistance in many crops are pol- sistance with few exceptions while most of the ygenetic, hence they are studied through QTL landraces were susceptible to diseases of ground- (quantitative trait loci) analysis. Quantitative traits nut as evident in the high incidence of LLS (late are controlled by interactions and additive effects leaf spot) in some landraces. Previous reports have of many genes[24,33]. In this study, plant survivor- shown that groundnut disease causes losses of up ship determined yield by 51% while disease infes- to 100% pod yield if infection occurs before flow- tation affected yield by 15% only, most signifi- ering[8,27–29]. The most outstanding landraces in cantly the BNR@30 and DSV@60*RUST@60 terms of disease tolerance was the Agric- interaction. The implication is that the remaining Dazhogwa but it should be subjected to further tri- 34% in yield variability is attributed to other als in a different environment before a conclusion known and unknown factors. It further shows that can be drawn. However, this landrace is likely to the use of highly vigorous, resilient and disease re- possess the genes for disease resistance and, there- sistant varieties is not a complete guarantee to fore, a potential candidate for a resistance breeding achieve high yield in groundnut. The interpretation programme. of this model is corroborated by the fact that the This study has identified genotypes that pos- best genotype in yield component (Samnut 24 and sess high yield. Top on the list was the INBRED ICGV–91328) coded as INBRED LINE–10 was LINE–10 made from a cross between Samnut 24 not resistant to diseases as shown in the high inci- and ICGV–91328 yielding 517 kg/ha. Four other dence of 31% in early leaf spot disease, thus sug- high yielding selections were inbred lines. This gesting the need for resistance breeding on this va- shows that the collections used in this work are riety. Khedikar[8] reported that breeding for disease bred for tolerance, resistance and yield qualities as resistance was linked to undesirable traits like low 113 pod yield and small seed size. This assertion partly genotype × environment effect called g × e effect explains why inbred line–10 possessed a high yield postulated by geneticists[22,31,32,37]. From the fore- but low resistance. going, all landraces that possess quality agronomic Generally, the outcome of this work is not in characteristics are well noted. This outcome is in tandem with the report of Khedikar[8] since most of agreement with other reports in that landraces are a the high yielding Inbred lines are also disease re- valuable source of genetic diversity and possess sistant. Molecular markers applied on different useful traits for breeding[18,37–39]. As such, they can groundnut breeds are channeled towards breeding be introduced into groundnut breeding pro- for yield or resistance/tolerance to some biotic and grammes to incorporate unique genes such as re- abiotic challenges[1,5,34,35]. This present study has sistance to biotic and abiotic stresses; and quality established a model where groundnut yield and its attributes. trend could be predicted using a simple regression analysis that involves survivorship and pathologi- 5. Conclusion cal indices. This type of model aligns with previous In this study, yield related characters dis- models in soybeans[36]. More complex multi-facto- played considerable variability among the collec- rial models may help provide useful information to tions, especially the pod sizes and the overall grain unravel the complex nature of factors affecting the yield. The established variability among the collec- overall survival and yield of the groundnut crop[13]. tions is supported by the low coefficient of similar- The outcome of molecular marker studies achieved ity ranging from 29 to 100 in the analysis of mor- through a multiplex of SSR primers linked to genes phological data. Seed infestation due to diseases for resistance to a particular disease has identified was high (18%). The Inbred lines were noted for 4 accessions that lacked the genes of interest. The their high survivorship, good yield, and disease re- inbred line–10 pointed out through morphological sistance. The line Samnut 24 × ICGV–91328 had data as a susceptible cultivar is among the four ac- the highest yield (517 kg/ha) but was susceptible to cessions without the genes. The two varieties re- diseases. Among the landraces, Agric-Musha, ported as resilient landraces (Agric-Musha, Bom- Bomboyi-Dugu and Agric-Dazhogwa were se- boyi-Dugu) in the morphological data have been lected for high survivorship and disease resistance. revealed as distinct accessions using RAPD analy- This study has established a model where ground- sis. Therefore, morphological and molecular data nuts yield and its trend could be predicted using a are complimentary. However, the actual level of simple regression analysis that involves survivor- similarity among the accessions was 41% as re- ship and pathological indices. Morphological and vealed by molecular data. molecular data are complementary. The actual Results are consistent with the findings of level of similarity among the accessions was 41% Wang et al.[24] who stated that molecular markers as revealed by molecular data. The selected inbred provide the genetic fingerprint that reveals true ge- lines and landraces are valuable genetic resources netic convergence and divergence among varieties that may harbor beneficial traits for breeding. of a species since it is not influenced by environ- Those accessions that possess quality agronomic mental factors unlike in morphological studies. traits should be presented to the growers. This is because they represent landmarks on DNA that are linked to various genes controlling. More- Author contributions over, SSR (Simple Sequence Repeats) markers are Conceptualization, LOO and CUA; software, highly distinguishing microsatellites while both OJO and SST; validation, LOO; formal analysis, RAPD and SSR markers are highly polymor- OJO and DP; investigation, IJ and OJO; resources, phic[13,24]. 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