Agronomic and biochemical evaluation of fifteen exotic groundnut parameters (Arachis hypogaea L.) varieties grown in Northern Cameroon

Agronomic and biochemical evaluation of fifteen exotic groundnut parameters (Arachis hypogaea L.) varieties grown in Northern Cameroon | 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 Agronomic and biochemical evaluation of fifteen exotic groundnut parameters (Arachis hypogaea L.) varieties grown in Northern Cameroon Dounia Désiré, Abakar Abba Said, Maygon Katoukam, Oumarou Haman Zéphirin, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8159782/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract Groundnuts ( Arachis hypogaea L.) is a major oilseed and legume in semi-arid regions, yet limited information exists on the agronomic and biochemical performance of recently introduced varieties under the environmental conditions of Northern Cameroon. This study evaluated fifteen exotic groundnut genotypes across three agro-ecological sites (Gazawa, Bocklé and Dang) to assess variability in yield components, oil and protein content, total polyphenols and antioxidant activity. Significant differences were observed among varieties for all traits studied. Pod weight was strongly correlated with overall yield (0.97), indicating that seed mass is a key determinant of productivity. Lipid and protein contents showed a strong negative correlation (r = 0.90), suggesting trade-offs in metabolic partitioning between oil and protein biosynthesis. Total polyphenol content was positively associated with antioxidant activity (r = 0.91), highlighting the nutraceutical potential of some varieties. Based on multivariate clustering, genotypes were grouped into high protein, high polyphenol and high lipid types, indicating opportunities for targeted selection depending on end use. These findings provide a valuable baseline for varietal improvement programs aimed at enhancing yield, nutritional quality and environmental adaptation of groundnut in the semi-arid zone. Groundnut biochemical traits antioxidant activity varietal evaluation Northern Cameroon Figures Figure 1 1. Introduction Groundnut ( Arachis hypogaea L.) is one of the world’s most important leguminous oilseed crop, cultivated widely across tropical and subtropical regions for its edible seeds, oil and protein-rich meal. It plays a vital role in human nutrition, livestock feed and soil fertility management due to its ability to fix atmospheric nitrogen in association with Rhizobium spp. In Sub-Sahara Africa, particularly in Cameroon, groundnut contributes significantly to household food security and rural income, yet productivity remains low compared with global averages (FAO, 2023). This yield gap is largely attributed to the use of low-yielding landraces, limited genetic improvement and poor adaptation of introduced varieties to local agro-ecological conditions. Groundnut yields and seed quality are influenced by both genetic and environmental factors. Traits such as pod weight, number of pods per plant are primary components determining yield, while seed composition especially oil, protein and phenolic content defines the crop’s economic and nutritional value (Asibuo et al ., 2008; Noubissié et al. , 2012). However, trade-offs often exist between these traits. High oil content is frequently associated with reduced protein concentration due to competition for assimilates during seed development (Liu et al. , 2019). Understanding the magnitude and direction of such correlations is essential for designing breeding programs that combine high yield with superior seed quality. Elsewhere macronutriment composition, biochemical constituents such as phenolics and flavonoids contribute to antioxidant activity, which is linked to health benefits and stress resilience. Recent studies highlight the importance of these metabolites in conferring tolerance to drought, heat and disease (Tavares et al. , 2010). Therefore, integrating biochemical profiling with agronomic evaluation can provide a more comprehensive understanding of varietal performance. Although several studies have evaluated local or improved groundnut genotypes in Cameroon (Noubissié et al ., 2012; Dolinassou et al ., 2016), information on recently introduced exotic varieties remains limited. Moreover, the relationships among yield, oil, protein and antioxidant traits under Northern Cameroonian conditions are poorly characterized. The present study was thus conducted to (i) assess the agronomic performance and biochemical composition of fifteen exotic groundnut varieties; (ii) determine correlations among key yield and biochemical parameters and (iii) classify varieties based on their biochemical profiles to identify promising genotypes for further improvement and adaptation in the semi-arid zone of Cameroon. 2. Materials and Methods 2.1. Study area The experiment was conducted during the 2019 to 2021 cropping seasons across three agro-ecological sites in Northern Cameroun: Far-north (Gazawa), North (Bocklé) and Adamawa (Dang). These locations are representative of Sudanian and Sahelian zone and differ slightly in rainfall, temperature and soil characteristics. Annual rainfall ranges from 800 to 1 100mm, with average daytime temperatures between 27 o C and 34 o C. The soils are predominantly sandy loams with moderate organic matter content and slightly acid pH (5.8–6.4). The choice of site aimed to capture environmental variability relevant to peanut cultivation in the region. 2.2. Plant material Fifteen exotic groundnut ( Arachis hypogaea L.) varieties were evaluated (Table 1 ). These genotypes were introduced from the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) in Niger and selected for their reported variability in yield, oil content and disease tolerance. They were divided into two main groups: the Virginia group, which is creeping, has a longer vegetative cycle (120 to 150 days) and seeds that do not germinate prematurely; the Valencia and Spanish group, which is erect and has a shorter vegetative cycle (80 to 110 days). Table 1 Characteristics of the 15 varieties of Arachis hypogaea selected for experimentation Number Accession Alterid Origin/Country Growth babit Branching Vegetative Cycle (days) 1 GGP 687 C5 India Erect/crawl Alternate 101 2 GGP 1147 RCM439 Bolivia Erect/crawl Alternate 80 3 GGP 1360 JH24 India Erect Alternate 92 4 GGP 4964 U12-7-1 Brazil Erect Sequential 79 5 GGP 1365 EC2164 Indonesia Erect Alternate 90 6 GGP 1466 U 4-4-32 Congo Erect Irregular 102 7 GGP 3317 58–619 Argentina Erect Alternate 110 8 GGP 692 C29 Tanzania Erect/crawl Alternate 120 9 GGP 3743 AP80-43 Madagascar Erect/crawl Alternate 100 10 GGP 699 C75 India Erect/crawl Alternate 120 11 GGP 1454 R4-A India Erect Sequential 90 12 GGP 1397 EC106965 USA Erect Sequential 90 13 GGP 1346 US17 Argentina Erect Alternate 91 14 GGP 927 55–437 Argentina Erect Sequential 85 15 GGP 434 SP2B Brazil Erect Sequential 110 2.3. Experimental design and crop management The experimental design was a Randomized Complete Block Design (RCBD) with three replications at each site. Each plot measured 3m × 2m (6m 2 ) and consisted of four rows, spaced 50 cm apart, with a plant spacing of 20 cm within rows. The plot was cleaned, ploughed and the ridges were formed, the seeds were removed from their shells, and then the seeds suitable for sowing were selected. No chemical or organic treatments were applied to the plot. The soils are clayey-sandy in the Far North, clay-loamy in the North region, and clay-siliceous in Adamawa. The climate is of the Sudano-Sahelian tropical type. 2.4. Agronomic and biochemical parameters measured Agronomic parameters : - Number of pods per plant and number of seeds per plant. These were determined on a sample of teen plants per variety and per repetition, then averaged for each variety according to the method described by Abdoul (2003). NPP = (Ʃ Pods on sampled plants)/n NSP= (Ʃ Seeds on sampled plants)/n NPP: Number of pods per plant NSP = Number of seeds per plant n: number of plants sampled (n = 10) - Weight of 100 pods In each replicate, 100 pods were collected for each variety and weighed with an electronic balance (sensitivity: 0.01g). - Pod yield in kilograms per hectare The estimated pod yield was calculated based on a planting density of 90 000 plants/ha, using the formula of Mothilal et al . (2010): Pod yield (kg/ha) = [(Pod weight × Number of pods / 10 000)] × 90 000 Biochemical parameters Biochemical analyses were performed on seeds that had been previously ground using a food processor. For this purpose, 10g of seeds from each variety were ground. - Protein content (%) The protein content was determined using the Kjeldahl method (AFNOR, 1981) for mineralization and the method of Devani et al . (1989) for nitrogen determination. The crude protein content was obtained by multiplying nitrogen content by the conventional factor of 6.25. Protein (%) = Nitrogen (%) × 6.25 - Oil content : Soxhlet extraction (%) The Franz Von Soxhlet method is a reference method used to determine the fat content in dehydrated solid foods. It is a gravimetric method, with the sample being weighed before extraction and the fat content at the end of extraction. Oil content (%) = (Mass of extracted fat (g)) / (Mass of sample (g)) × 100 - Total polyphenol content Polyphenols were determined by spectrophotometry, following the protocol applied by Goli et al . (2005). The calibration curve was performed using gallic acid at different concentrations (0-250µg/ml), under the same conditions and following the same dosage steps. The results were thus expressed in mg gallic acid equivalent per 100g dry matter (mg GAE/100gDM). - Antioxidant activity (%) Evaluated by the DPPH method (Meda et al . 2005). The results were expressed as a percentage (%). AA (%) = ((Abs C – Abs E) / Abs C) × 100 AA (%) = Percentage reduction in DPPH Abs C = Absorbance of the control Abs E = Absorbance of the sample All analyses were conducted in triplicate to ensure accuracy 2.5. Statistical analysis Data were analyzed by ANOVA using STATGRAPHICS version 5.0. Means separation was performed using the Less Significant Difference (LSD) test at p ≤ 0.05. The Pearson correlation coefficient (r) was used to assess relationships between parameters. The formula used is as follows: r = Σ [(Xi –Xm) × (Yi –Ym)] / [Σ (Xi –Xm) 2 × Σ (Yi –Ym) 2] 1/2 r = Correlation coefficient (-1 ≤ r ≤ 1) Xi, Yi = Values of variables X and Y for variety i \(\:\stackrel{-}{\varvec{X}},\:\stackrel{-}{\varvec{Y}}\) : Means of Xi and Yi for all varieties studied Significance thresholds: p < 0.05 (*) and p < 0.01 (**). The XLSTAT software was also used for correlations and Hierarchical Ascending Classification (HAC) were performed to classify genotypes based on their yield and biochemical profiles. 3. Results 3.1. Agronomic parameters - Number of pods per plant The mean number of pods per plant ranged from 26.50 to 105.50 among the 15 varieties studied (Table 2 ). Varieties 55–437 and U12-7-1 recorded the highest values (105.50 and 87.50 pods/plant, respectively). Conversely, the lowest values (26.50 and 35.50) were recorded in genotypes AP80-43 and U4-4-32, followed by variety C75 with 39.50 pods/plant. - Number of seeds per plant The number of seeds per plant varies between 42.00 and 130.50. The best performances were obtained in varieties 55–437, 58–619, C5, R4-A and US17. In contrast, U12-7-1 and AP80-43 had the lowest averages. - Weight of 100 pods The weight of 100 pods reveals that varieties 58–619 and AP80-43 stand out with high average weights. In contrast, varieties EC106965 and C5 have the lowest weights (42.57 g and 43.52 g). The other genotypes, notably JH24 and US17, have values that are close to the overall average (Table 2 ). - Pod yield in kg/ha Pod yield varied significantly among varieties. 58–619, AP80-43 and C75 ranked highest with 4 767, 4 541 and 4 064 kg/ha respectively (Table 2 ). Intermediate yields were recorded in R4-A (3 521 kg/ha), SP2B (3 462 kg/ha), C29 (3 386 kg/ha), JH24 (3 099kg/ha) and US17 (3 077 kg/ha). The lowest yields were observed in C5 (1 958 kg/ha) and EC106965 (1 916 kg/ha). Table 2 Variability of agronomic parameters of 15 exotic varieties of Arachis hypogaea in Northern Cameroon Parameters Genotypes Number of pods per plant Number of seeds per plant Weight of 100 pods (g) Pod yield in kg/ha C5 42.00 ± 2,82b 96.00 ± 7.31e 43.52 ± 0.38a 1 958 ± 43a RCM439 45.00 ± 5,65bc 67.50 ± 9.89cd 60.54 ± 15.63b 2 725 ± 138b JH24 52.00 ± 2,82cd 76.00 ± 36.76de 68.87 ± 3.90bcd 3 099 ± 234bcd U12-7-1 87.50 ± 21,21f 42.00 ± 14.14a 61.29 ± 7.33b 2 758 ± 240b EC21164 53.00 ± 22,62c 76.00 ± 4.42de 63.97 ± 5.13bc 2 879 ± 308bc U4-4-32 35.50 ± 11,31ab 50.50 ± 11.20abc 64.17 ± 13.17bc 2 888 ± 290bc 58–619 69.50 ± 7,07d 113.00 ± 31.11g 105.93 ± 20.32fg 4 767 ± 219g C29 47.50 ± 12,72bc 73.00 ± 4.41cd 75.25 ± 13.80bcd 3 386 ± 228cde AP80-43 26.50 ± 1,41a 48.00 ± 9.50a 116.40 ± 11.96g 4 541 ± 227g C75 39.50 ± 7,07b 68.00 ± 5.43cde 90.32 ± 4.79ef 4 064 ± 287f R4-A 68.50 ± 1,41d 95.00 ± 12.62f 78.24 ± 10.43de 3 521 ± 326e EC106965 50.00 ± 5,67c 64.50 ± 8.38bc 42.57 ± 2.37a 1 916 ± 142a US17 62.50 ± 12,72d 93.00 ± 8.48f 68.38 ± 12.20bcd 3 077 ± 472bcd 55–437 105.50 ± 25,45g 130.50 ± 8.38h 63.63 ± 12.75bc 2 863 ± 125bc SP2B 42.50 ± 4,24bc 61.50 ± 9.89b 76.94 ± 5.28cde 3 462 ± 317de Means 55.13 ± 9,61 76.96 ± 13.47 72.00 ± 13.30 3 194 ± 565 CV (%) 17.43 17.50 18.47 13.55 NPP: Number of pods per plant; NSP: Number of seeds per plant; W100P: Weight of 100 pods; PY: Pod yield in kilograms per hectare; %L: Lipid content; %P: Protein content; PPT: Total polyphenol content; AOA: Antioxidant activity; CV: Coefficient of variation. 3.2. Biochemical parameters - Protein content Analysis of the protein content of exotic peanut varieties grown in the Northern Zone reveals significant variability (Table 3 ). The highest values were recorded in US17 (28.73%) and RCM439 (27.66%). These values suggest interesting potential for selection programs aimed at protein enrichment. However, the SP2B and 58–619 varieties have lower protein contents than the previous ones, with values of 19.80% and 19.40%, indicating lower nutritional quality in terms of protein. The US17 variety produced the highest protein level throughout the study area (28.73%). - Lipid content Lipid levels ranged from 37.76% to 55.33%. Varieties 58–619 and U4-4-32 showed the highest contents (55.33% and 51.53%), suggesting particular interest for industrial use geared towards oil production. In contrast, the RCM439 and US17 varieties have lower values, ranging from 37.76% to 40.10%, reflecting a more moderate lipid composition. - Total polyphenol content The results of the analysis of variance show a statistically significant difference in total polyphenol content between varieties (p < 0.05). Genotypes 58–619 and R4-A stand out with high contents, ranging from 1.73 to 1.67 mg GAE/100g, reflecting good potential in antioxidant compounds. The EC21164 and C75 varieties followed with an average content of 1.57mgGAE/100g. The ten other varieties had concentrations ranging from 1.51mgGAE/100g (RCM439) to 1.16mgGAE/100g (SP2B), reflecting notable biochemical diversity. - Antioxidant activity The evaluation of the antioxidant activity of the seeds, measured by the DPPH radical scavenging method, highly significant differences between genotypes (p < 0.01). Variety 58–619 has the highest antioxidant activity, reaching 79.33%, which indicates high functional potential. Varieties EC21164 and R4-A follow closely behind, with levels of 77.76% and 76.73% respectively. In contrast, the SP2B and 55–437 varieties had the lowest capacities, ranging from 56.33% to 55.16% (Table 3 ). These results highlight the potential of certain genotypes for nutritional or nutraceutical applications related to their antioxidant properties. Table 3 Variability of biochemical parameters of 15 exotic varieties of Arachis hypogaea in northern Cameroon Parameters Genotypes Protein content Lipid content Total polyphenol content Antioxidant activity in seeds C5 26.26 ± 1,05hg 41.10 ± 0,95bc 1.41 ± 0.11bcd 73.16 ± 1,15e RCM439 27.66 ± 2,23g 37.76 ± 1,15a 1.51 ± 0.07cd 71.83 ± 0,83e JH24 25.83 ± 0,23f 41.36 ± 0,66bcd 1.47 ± 0.09cd 66.16 ± 0,58d U12-7-1 25.03 ± 1,05efg 46.00 ± 1,78ef 1.37 ± 0.11bcd 62.30 ± 0,36c EC21164 22.93 ± 0,61cde 44.26 ± 1,35de 1.57 ± 0.12de 77.76 ± 0,72f U4-4-32 20.06 ± 1,20ab 51.53 ± 2,40g 1.33 ± 0.06ab 61.03 ± 0,63d 58–619 19.40 ± 0,70a 55.33 ± 2,30h 1.73 ± 0.12e 79.33 ± 0,70f C29 24.06 ± 1,20def 43.53 ± 1,30cde 1.38 ± 0.06bcd 71.00 ± 0,34e AP80-43 20.86 ± 1,05abc 48.76 ± 1,56fg 1.33 ± 0.05ab 59.16 ± 0,32b C75 24.46 ± 1,15ef 40.83 ± 0,55ab 1.57 ± 0.11de 70.96 ± 0,41de R4-A 23.53 ± 2,30def 44.06 ± 0,37cde 1.67 ± 0.12e 76.73 ± 0,51f EC106965 23.83 ± 2,05def 42.03 ± 0,40bcd 1.36 ± 0.04abc 65.23 ± 0,73c US17 28.73 ± 1,23g 40.10 ± 1,36ab 1.39 ± 0.06bcd 59.60 ± 0,34b 55–437 21.90 ± 0,65bcd 46.00 ± 1,17ef 1.26 ± 0.10ab 55.16 ± 0,51a SP2B 19.80 ± 0,75ab 50.60 ± 1,20g 1.16 ± 0.07a 56.33 ± 0,64a Means 23.62 ± 2,18 44.88 ± 3,23 1.43 ± 0.17 67.05 ± 6,58 CV(%) 9.23 7.20 11.89 9.81 NPP: Number of pods per plant; NSP: Number of seeds per plant; W100P: Weight of 100 pods; PY: Pod yield in kilograms per hectare; %L: Lipid content; %P: Protein content; PPT: Total polyphenol content; AOA: Antioxidant activity; CV: Coefficient of variation. 3.3 Correlations between yield and biochemical parameters The weight of 100 pods (W100P) was strongly and positively correlated with yield (PY) (r = 0.97); total polyphenol content (PPT) and antioxidant activity (AOA) with r = 0.91; and the number of pods (NPP) and the number of seeds (NSP) with r = 0.77. The weight of 100 pods (W100P) was positively and moderately correlated with the lipid content (%L) (r = 0.50) and negatively correlated with protein content (%P) (r=-0.49) (Table 4 ). Similarly, the Pod yield per hectare was positively and moderately related to the total polyphenol content (PPT): r = 0.30, positively correlated with the antioxidant activity (AOA) of peanut seeds. Lipid content (%L) was strongly and negatively correlated with the protein content (%P) (r = 0.90). It was also negatively correlated with polyphenol content and antioxidant activity. Table 4 Correlation matrix between agronomic and biochemical parameters Variables NPP NSP W100P PY %L %P PPT AOA NPP 1 NSP 0.77* 1 W100P -0.34 -0.24ns 1 PY -0.29 -0.18 0.97** 1 %L -0.09 -0.11 0.50 0.40 1 %P 0.11 0.13 -0.49 -0.43 -0.90** 1 PPT -0.06 0.08 0.29 0.30 -0.13 0.18ns 1 AOA -0.20 0.02 0.21 0.21 -0.19 0.19 0.91** 1 NPP: Number of pods per plant; NSP: Number of seeds per plant; W100P: Weight of 100 pods; PY: Pod yield; %L: Lipid content; %P: Protein content; PPT: Total polyphenol content; AOA: Antioxidant activity; CV: Coefficient of variation. 4. Discussion The present study revealed significant variability among the 15-exotic peanut ( Arachis hypogaea L.) varieties grown in Northern Cameroun, particularly in pod yield, seed weight and biochemical quality traits. The strong positive correlation observed between pod weight and yield (r = 0.97) confirms that seed mass is a major determinant of productivity, consistent with earlier results by Dolinassou et al . (2016) and recent multi-environment analyses by Wang et al . (2023), who demonstrated that kernel size and weight remain the most heritable yield-related traits across diverse agro-ecological zones. Similarly, new genome wide association studies (GWAS) have identified key loci controlling pod weight and yield stability, notably on chromosomes A05 and B03 (Wang et al ., 2024), supporting the genetic basic of these agronomic correlations. The variability in seed protein and lipid contents among varieties aligns with previous observations from Ghana (Asibuo et al ., 2008) and Cameroon (Noubissié et al ., 2012). while recent genomic studies have demonstrated that oil and protein biosynthesis are inversely regulated at the molecular level (Wang et al ., 2023; Liu et al. , 2019). This trade-off was also evident in our study, where lipid content was negatively correlated with protein content (0.90). Recent pangenomic analyses involving 269 accessions have shown that structural variants within the Aharf 2–2 gene regulate seed size and oil accumulation (Kunkun et al. , 2025), providing a molecular explanation for these biochemical contrasts observed in local varieties. The lipid content range (37.7–55.3%) obtained in this study is consistent with findings from recent evaluations in West Africa and Asia, confirming the adaptability of high oil genotypes to semi-arid conditions (Swathi et al. ,2023). Moreover, new high protein lines developed in China between 2023 and 2025 (Li et al ., 2025) achieved protein contents exceeding 30%, suggesting that integrating molecular makers for both traits may overcome the classical negative correlation between oil and protein concentrations. Regarding antioxidant activity and total phenol content, our results (up to 79.33% DPPH activity and 1.73 mg GAE/100g) indicate high nutraceutical potential. This agrees with recent biochemical studies showing that phenol compounds in peanuts especially resveratrol, proanthocyanidins and flavonoids are key determinants of antioxidant defense under stress (Tavares et al. , 2010; Devi et al. , 2019). In 2024, transcriptomic analyses of A. hypogaea under Ralstonia solanacearum infection revealed upregulation of genes related to phenylpropanoid and flavonoid pathways (Wang et al. , 2024), corroborating the association we found between polyphenols and antioxidant activity (r = 0.91). These results suggest that biochemical traits could serve as indicators of both nutritional value and stress tolerance. Recent progress in peanut breeding further reinforces these findings. Quantitative trait locus (QTL) mapping and GWAS have identified genomic regions linked to disease resistance, including PSWDR-1 for Tomato Spotted Wilt Virus (Dongliang et al ., 2025) and several loci conferring resistance to stem rot (Veerendrakumar et al , 2025). These discoveries support marker assisted selection for high-yield and high-quality genotypes. Furthermore, the application of tissue culture free genome editing approaches such as CRISPR is accelerating improvement of traits like oil composition, drought tolerance and allergen reduction (Alam, 2025). The strong phenotypic associations found in this study may reflect coordinated metabolic networks regulating lipid and protein biosynthesis (Wang et al. , 2019). Environmental stresses, particularly temperature and water deficit, are also know to influence these processes (Zhao et al ., 2011). Integrating such physiological and molecular understanding into local breeding programs could enhance the development of peanut cultivars adapted to the semi-arid zones of Northern Cameroon. Grouping of varieties into three biochemical clusters (protein, polyphenol, lipid) is consistent with current global strategies for peanut value-chain diversification (Li et al , 2025). Similar approaches combining rhizobial inoculation and mycorrhizal symbiosis have been reported to improve both yield and nutritional composition under West and central African conditions (Igiehon et al. , 2021; Mpongwana et al. , 2023; Ajayi et al. , 2024). Overall, the integration of agronomic and biochemical traits in this study offers a comprehensive framework for the genetic improvement of Arachis hypogaea . The correlations observed mirror recent global findings and confirm that the concurrent enhancement of yield, oil content and antioxidant potential is feasible through combined molecular breeding and agronomic practices. 5. Grouping of varieties With a view to improving agro-nutritional qualities, the quality of the harvested product and the availability of varieties for peanut production in semi-arid areas, the adoption of relatively more plastic and more suitable varieties that require less intensive technical inputs. In addition, genetic variability is the basic condition for crop improvement, as it provides a wider germplasm for varietal selection. Confectionery and oilseed varieties could be distinguished from food varieties in order to enhance the peanut sector both nutritionally and commercially in this Northern Zone of Cameroon. The Ascending Hierarchical Classification (AHC) (Fig. 1 ) allowed the fifteen varieties studied to be classified into three classes: Class 1: Varieties with protein contents between 20 and 30% are considered to have a high protein content, a finding also reported by Pinstrup Andersen et al . (1999) for peanuts. Varieties C5, U12-7-1, EC106965, US17, and 55–437 have the highest protein contents in this study. They can be used as “ snack peanuts ” and as part of a food supplement for infants, which would help combat severe malnutrition among children in the North Cameroon region (Brouwer et al ., 2004). Class 2: The varieties RCM439, JH24, EC21164, C29 and C75 are characterized by an average protein content, high polyphenol content and high antioxidant activity (Table 3 ). These varieties can be recommended for confectionery and could help reduce the risk of cardiovascular disease and certain cancers (Mukuddem-Petersen et al ., 2005). The high polyphenol content, which is positively correlated with pods yield in kg/ha, suggests that the varieties have potential in terms of both polyphenol content and pods yield in kg/ha and could be selected for use as “ snack peanuts” . The Virginia type is the most recommended in this case, and the C29 variety would be the most readily available in the North Cameroon region for use as snack peanuts. Class 3: The varieties U4-4-32, 58–619, AP80-43, R4-A and SP2B are characterized by a pod yield in kg/ha and a high lipid content, a polyphenol content and average antioxidant activity. These varieties have agronomic and biochemical potential that could be part of an extension program in northern Cameroon as oilseed peanuts. In this class, varieties 58–619 and AP80-43 are more suitable for oil production (Table 3 ). Conclusion The study shows that there is significant variability among the 15 exotic peanut varieties grown in northern Cameroon. The weight of 100 pods (W100P) is strongly and positively correlated with yield (PY); Pod yield is positively correlated with lipid content, total polyphenol content and antioxidant activity, but negatively correlated with protein content. The number of pods per plants (NPP) and the number of seeds per plants (NSP) show a very high positive correlation. The identification of stable correlations between agronomic and biochemical traits offers an opportunity for breeders to combine yield and nutritional quality in the same breeding program. However, certain unfavorable correlations, such as that between yield and protein content, require compromises or the use of marker-assisted selection techniques to dissociate linked genetic traits. These results also pave the way for varietal selection that integrates both agronomic performance and biochemical quality in response to the nutritional and economic challenges of the region. Further studies, particularly in functional genomics and multi-location trials, will be necessary to validate the stability of these correlations in different agroecological environments. Declarations Corresponding Author: Dounia Désiré, Department of Sustainable Agriculture and Disaster Management, Faculty of Science, University of Garoua. P.O. Box 346, Garoua-Cameroon, E-Mail: [email protected] Acknowledgements The authors thank the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) for peanut seeds supplied for this study. Authors’ contributions Conceptualization: D. Désiré, Methodology: D. Désiré and J-B Tchiagam Noubissie. Formal Analysis: D. Désiré, O. H. Zéphirin and N. M. Antoine, writing original draft: D. Désiré, Writing-review and editing: D. Dounia, A. A. Said, K. Maygong, O. H. Zéphirin, N. M. Antoine and J-B Tchiagam Noubissie, Acquisition: D. Désiré and J-B Tchiagam Noubissie, Supervision: J-B Tchiagam Noubissie. All authors read and approved the final manuscript. Funding Declaration This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. Data Availability Statement The datasets generated and/or analysed during the current study are available from the corresponding author on reasonable request. Competing Interest Declaration The authors declare that there are no competing interests. References Abdoul, H.Z., 2003. Effets of seed quality on groundnut ( Arachis hypogaea ) production in Senegal. Master’s Thesis, Ecole Nationale Supérieure d’Agriculture (ENSA), Dakar, Senegal, 59pp. Adanga, P.G., Mamba, G., Ngama, F., Litucha, J., Okungo, A., 2024. Effet of sowing dates and densities on groundnut ( Arachis hypogaea ) yield in Isiro region, Haut-Uélé Province, DR Congo. Journal of Research in Humanities and Social Science. 12(10) : 82-88. AFNOR., 1981 . Fat, Oilseeds and derived products, 2 nd edition. AFNOR, Paris, France, 438pp. Alleidi, I., Hamidou, F., Younoussa, O.M., Bakasso, Y., Zongo, J.D., 2016. Agro-morphological characterization of groundnut ( Arachis hypogaea ) accessions for oil content. European Scientific Journal, 15 (12): 1857-7881. Agri-stat Cameroon, 2012. Yearbook of agricultural statistics. Ministry of Agriculture and Rural development (MINADER), Yaoundé, Cameroon, 123pp. Ajayi, O.O., Dianda, M., Fagade, O.E., 2024. Rhizobia inoculation’s impact on the biomass and moisture content of leguminous Bambara groundnut ( Vigna subterranean L. Verdc). Discover Sustain. 5;315. https://doi.org/10.1007/s43621-024-00502-0. Alam, T., 2025. Advances in tissue culture-free genetic engineering and genome editing of peanut. Mol. Biotechnol. https://doi.org/10.1007/s12033-025-01476-8. Asibuo, J. Y., Akrmah, R., Safo-Katanka, O., Adu-Dapaah, H.K., Ohemeng-Dapaah, S., Agyeman, A., 2008. Chemical composition of groundnut ( Arachis hypogaea L.) landraces. African Journal of Biotechnogy., 7(13): 2203-2208. https://doi.org/10.5897/AJB08.024. Betdogo, S., Sali, B., Adamou, I., Woin, N., 2015. Agronomic evaluation of five groundnut cultivars ( Arachis hypogaea L.) introduced in the North Region of Cameroon. Journal of Applied Biosciences , 89: 8311– 8319. https://doi.org/10.1093/jn/134.4.919. Cheikh, T., 2008. Bioactivity of extracts from Calotropis procera and Senna occidentalis L. on Caryedon serratus , a pest of peanut stocks and seeds in Senegal. PhD Thesis, Cheikh Anta Diop University of Dakar, Senegal,196pp. https://hdl.handle.net/20.500.12177/2889. Brouwer, I.A., Katan, M.B., Zock, P.L., 2004. Dietary alpha-linolenic acid is associated with reduced risk of fatal coronary heart disease, but increased prostate cancer risk: a meta-analysis. Journal of Nutrition . 134 : 919-922. https://doi.org/10.1093/jn/134.4.919. Dapoigny, L., Tourdonnet, S., Eestrade, J.R., Jeuffroy, M.H., Fleury, A., 2000. Effect of nitrogen nutrition on growth and nitrate accumulation in lettuce ( Lactuca sativa L.), under various conditions of radiation and temperature. Agriculture, Ecosystems & Environment, 20: 843–855. https://doi.org/10.1016/S0167-8809(99)00103-6. Devani, M.B., Sioshoo, J.C., Shal, S.A., Suhagia, B.N., 1989. Spectrophotometrical method for micro-determination of nitrogen in Kjedalh digest. J. Ass. Off. Anal. Chem ., 72(6): 953-956. https://doi.org/ 10.1093/jaoac/72.6.953. Dolinassou, S., Noubissié, T.J.B., Djiranta, K.A., Njintang, Y.N., 2016. Genotype × environment interaction and kernel yield-stability of groundnut ( Arachis hypogaea L.) in Northern Cameroon. Journal of Applied Biology and Biotechnolgy , 4 (01): 1-7. https://doi.org/10.7324/JABB.2016.40101. Dolinassou, S., Noubissié, T.J.B., Malhala, M., Nguimbou, R.M., Njintang, Y.N., 2017. Genotype × environment interaction and oil content stability analysis of groundnut ( Arachis hypogaea L.) in Northern Cameroon. Journal Plant Breeding and Crop Science , 9 (4): 45-53. https://doi.org/10.5897/JPBCS. 2017.0647. Dongliang W., Chuanzhi Z., Walid K., Ethan A.T., Hui W., Gaurav A., Jake C. F., Albert C., Corley H. C., Xingjun W., Josh P. C., Baozhu G., 2025. High-resolution genetic and physical mapping reveals a peanut spotted wilt disease resistance locus, PSWDR-1 , to Tomato spotted wilt virus (TSWV), within a recombination coldspot on chromosome A01. BMC Genomics. 26: 224. https://doi.org/10.1186/s12864-025-11366-7. Food and Agriculture Organization of the United Nations (FAO), 2023. FAO in Africa: highlights in 2023. Rome FAO. https://openknowledge.fao.org/handle/20.500.11766. FAOSTAT, 2014. Statistical database of the Food and Agriculture Organization of the United Nations. Goli, A.H., Barzeger, M., Sahari, M.A., 2005. Antioxidant activity and total phenolic compounds of pistachio ( Pistachia vera )hull extracts. Food Chemistry. 92:521-525. https://doi.org/10.1016/j.foodchem.2004.08.020. Howell, R. W., Collins, R. F., 1957. Factors affecting linolenic and linoleic acid content of soybean oil. Agron. J. 49: 593-597. https://doi.org/10.2134/agronj1957.00021962004900120014x. Igiehon, N.O., Babalola, O.O., Cheseto, X., Torto, B., 2021. Effects of Rhizobia and arbuscular mycorrhizal fungi on yield, size distribution and fatty acid of soybean seeds grown under drought stress. Microbiol. Res. 242:126640. https://doi.org/10.1016/j.micres.2020.126640. Katim, T., Tamsir, M., Diatta, P.M., Foncéka, D., Issa, F., Bradford, M., 2022. Use of improved varieties in the peanut basin of Senegal. Khaled, S., 2008. Contribution to the study of adaptation of durum wheat cutivars ( Triticum durum ) to organic farming: grain yield stability, quality technology and died. Doctoral Thesis, Montpelier 171pp. Kunkun, Z., Hongzhang, X., Guowei, L., Annpurna, C., Yi F., Zenghui, C.,Xiaourui, D., Huimim L., Kai, Z., Lin, Z., Ding Qiu, Rui Ren, Fangping G., Zhongfeng L., Xingli, M., Shubo, W., Rajeev, K. V., Chaochun, W., Dongmei Y., 2025. Pangenome analysis structural variation associated with seed size and weight trait in peanut. Nature Genetics . https://doi.org/10.1038/s41588-025-025-02170-w. Larson, R.A., 1988. The antioxidants of higher plants. Phytochemistry . 27(4) : 969-978. https://doi.org/10.1016/0031-9422(88)80254-1. Li, Z., Zhang, Y., Liu, Y., Fan, Y., Qiu, D., Li, Z., Gong, F., Yin, D., 2025. Research Progress on high-protein peanut ( Arachis hypogaea L.) varieties in China. Plant, 14(18): 2917. https://doi.org/10.3390/plants14182917. Liu, N., Guo, J., Zhou, X., Wu, B., Huang, L., Luo, H.Y., Chen, Y.N., Chen, W.G., Lei, Y., Huang, Y., Liao, B.S., Jiang, H.F., 2019. High-resolution Mapping of a Major and Consensus Quantitative Trait Locus for Oil Content to a 0.8-Mb Region on Chromosome A08 in Peanut ( Arachis hypogaea L.). Theoretical and Applied Genetics 133, 37-49. https://doi.org/10.1007/s00122-019-03438-6. Magrin, G., 2003. A market-orientated staple: peanut. In: Altas Agriculture and Rural Developpment in Central African Savannas, CIRAD/PRASAD, 63-64pp. Mahatma, M. K., Thawait, V., Bishi, V., Khatediya, S. K., Rathnakumar, A. L., Lalwani, H.B., Misra, J. B., 2016. Nutritional composition and antioxidant activity of Spanish and Virginia groundnuts ( Arachis hypogaea L.): a comparative study. Journal Food Science Technology, 53(5) : 2279-2286. https://doi.org/10.1007/s13197-016-2187-y. Meda, A., 2005. Therapeutic use of honey and honeynee larvae in central Burkina Faso. Journal of Ethnopharmacomogy , 101(1-3), 1-5. https://doi.org/10.1016/j.jep.2005.04.017. Mothilal, A, Vindhiya, V.P, Manivannan, N. 2010. Genotype × environment for kernel yield in groundnut ( Arachis hypogaea L.). Electronic Journal of. Plant Breeding , 1(5): 1306-1308. https://doi.org/10.5555/20113019542. Mukuddem-Peterson, J., Oosthuizen, W., Jerling, J. C., 2005. A systematic review of the effects of nutson blood lipid profiles in humans. Journal of Nutrition, 135 (9), 2082-2089. https://doi.org/10.1093/jn/135.9.2082. Mpongwana, S., Manyevere, A., Mupangwa, J., Mpendulo, C. T., Mashamaite, C. V., 2023. Foliar nutrient content responses to bio-inoculation of arbuscular mycorrhizal fungi and Rhizobium on three herbaceous forage legumes. Front. Sustain. Food Syst. 7:1256717. https://doi.org/10.3389/fsufs.2023.1256717. Nassourou, M. A., Noubissié, T. J-B., Gonne, S., Hamadama, Y., Bell, J.M., Njintang, Y.N., 2015. Diallel analysis of polyphenols and phytates content in cowpea ( Vigna unguiculata L. Walp.). Scientia Agriculturae , 12(1): 46-51. https://doi.org/10.15192/PSCP.SA.2015.12.1.4651. Ntoukam G., Endonto C., Ousman T., Kontcheu Mc., Hamasselbe A., Njomoha C., Ndikawe R. & Abba A., 1996. Productions des légumineuses à graines : acquis de la recherche. In : Agricultures des savanes du Nord Cameroun vers un développement solidaire des savanes d’Afrique centrale, pp : 215-223. Noubissié T.J.B., Njintang N.Y. & Dolinassou S., 2012. Heritability studies of protein and oil contents in groundnut ( Arachis hypogaea L.) genotypes. International Journal of Innovations in Bio Sciences, 2 (3): 162-171. Nunes L. L., Cavalcanti R. S. & Péricles A. M. F., 2011. Correlation and path analysis of peanut traits associated with the peg. Crop Breeding and Applied Biotechnology , 11: 88-93. https://doi.org/10.1590/S1984-70332011000100013. Palanisamy B.D., Radjendran V., Sathyaseelan S., Nagappa G.M., Venkatesan B.P. 2014. Health benefits of finger millet ( Eleusine coracana L.) polyphenols and dietary fiber. Journal of Food Science and Technology 51 (6) 1021-1040. https://doi.org/10.1007/s13197-011-0590-7. Parmar D.L., Rathna Kumar A.L. & Bharodia P.S., 2000. Genetic and interrelationship of oil and protein contents in cross involving confectionery genotypes of groundnut. International Arachis Newsletter, 20: 17-18. Perem A.L.L., 2012. Evaluation of various inoculation methods of arbuscular mychorrhizal fungi and the effect of inoculum sieving on peanut performance ( Arachis hypogaea L.) DIPES II. University of Yaoundé I. 51pp. Pinstrup-Andersen, P., Pandya-Lorch, R. & Rosegrant, M.W. 1999. World food prospects: critical issues for the twenty-first century . IFPRI, Washington. Rice-Evans C.A, Miller N.J, Paganga G., 1996. Structure antioxidant activity relationships of flavonoids and phenolic acids. Fre Radic Biol Med . 20(7) : 933-956. https://doi.org/10.1016/0891-5849(95)02227-9. Schilling R., 1992. Peanut. Courrier de la planète. Agriculture, Environnement, Alimentation, trois défis pour un monde solidaire, Paris, France, 35p. Swathi, Y., Rajanikanth, P., Satya N., Uppala N.M., Guntha, A., Vemula, A., Hari K.S., 2023. Effect of sub-optimal moisture levels on the quality of groundnut ( Arachis hypogaea L.) during storage in triple-layer hermetic storage bags. Frontiers in Sustainable Food Systems . 7:1275133 . https://doi.org/10.3389/fsufs.2023.1275133. Talcott, S.T., Duncan, E.C., Del Pozoinsfran, D., Gorbet D.W., 2005. Polyphenolic and antioxidant changes during storage of normal, mid and high oleic acid peanuts. Food Chemistry , 89: 77-84. https://doi.org/10.1016/j.foodchem.2004.02.020. Tavares L., Fortalezas S., Carrilho C., Mc Dougall G.J., Stewart D., Ferreira R.B., & Santos C.N., 2010. Antioxidant and antiproliferative properties of strawberry tree tissues. Journal of Berry Research , 1(1): 3-12. https://doi.org/10.3233/BR-2010-001. Touroumgaye, G., Mariama, D.D., Guiguindibaye, M., Ali, M.Z., Aliou, G., 2017. Determination of optimal sowing density on peanut ( Arachis hypogaea L.) productivity in the Sudanian zone of Chad. European Scientific Journal, 13(9) : 316-324. Veerendrakumar, H. V., Sudini, H. K., Kiranmayee, B., Devika, T., Gangurde, S. S., Vasanthi, R. P., Nirmal K. A. R., Bera, S. K., Guo, B., Liao, B., Varsheney, R. K., Pandey, M. K., 2025. Dissecting the genomic regions, candidate genes and pathways using multi-locus genome-wide association study for stem rot disease resistance in groundnut. The Plant Genome, 18(3): 70089. https://doi.org/10.1002/tpg2.70089. Wang, X., Qi, F., Sun, Z., Liu, H., Wu, Y., Wu, X., Xu, J., H., Qin, L., Wang, Z., Sang, S., Dong, W., Huang, B., Zheng, Z., Zhang, X., 2024. Transcriptome sequencing and expression analysis in peanut reveal the potential mechanism response to Ralstonia solanacearum infection. BMC Plant Biology, 24, 207. https://doi.org/10.1186/s12870-024-04877-0. Wang, K., Shi, L., Zheng, B., He, He, Y., 2023. Response of wheat kernel to diverse allelic combinations under projected climate change condition. Frontiers in Plant Science, 14: 1138966. https://doi.org/103389/fpls.2023.1138966. Mar, Mar, W., Azizah, A-H., Bablishah, S.B., Farooq, A., Mandumpal, C. S., Mohd, P-D., 2011. Phenolic compounds and antioxidant activity of peanut’s skin, hull, raw kernel and roasted flour. Pakistan Journal of Botany, 43(3): 1635-1642. https://www.pakbs.org/pjbot/PDFs/43(3)/PJB43(3)1635. Zhihui, W., Yue, Z., Liying, Y., Yuning, C., Yanping, K., Dongxin, H., Xin, W., Kede, L., Huifang, J., Yong, L., Boshou, L., 2023. Correlation and variability analysis of yield and quality related traits in different peanut varieties across various ecological zones of China. Oil Crop Science. 8: 236-242. https://doi.org/10.1016/j.ocsci.2023.12.001. Zhao X., Nishimura Y., Fukumoto Y. & Li J., 2011. Effect of high temperature on active oxygen species, senescence and photosynthetic properties in cucumber leaves. Environmental and Experimental Botany .70: 212-216. https://doi.org/10.1016/j.envexpbot.2010.09.005. Additional Declarations No competing interests reported. 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Introduction","content":"\u003cp\u003eGroundnut (\u003cem\u003eArachis hypogaea\u003c/em\u003e L.) is one of the world\u0026rsquo;s most important leguminous oilseed crop, cultivated widely across tropical and subtropical regions for its edible seeds, oil and protein-rich meal. It plays a vital role in human nutrition, livestock feed and soil fertility management due to its ability to fix atmospheric nitrogen in association with \u003cem\u003eRhizobium\u003c/em\u003e spp. In Sub-Sahara Africa, particularly in Cameroon, groundnut contributes significantly to household food security and rural income, yet productivity remains low compared with global averages (FAO, 2023). This yield gap is largely attributed to the use of low-yielding landraces, limited genetic improvement and poor adaptation of introduced varieties to local agro-ecological conditions.\u003c/p\u003e\u003cp\u003eGroundnut yields and seed quality are influenced by both genetic and environmental factors. Traits such as pod weight, number of pods per plant are primary components determining yield, while seed composition especially oil, protein and phenolic content defines the crop\u0026rsquo;s economic and nutritional value (Asibuo \u003cem\u003eet al\u003c/em\u003e., 2008; Noubissi\u0026eacute; \u003cem\u003eet al.\u003c/em\u003e, 2012). However, trade-offs often exist between these traits. High oil content is frequently associated with reduced protein concentration due to competition for assimilates during seed development (Liu \u003cem\u003eet al.\u003c/em\u003e, 2019). Understanding the magnitude and direction of such correlations is essential for designing breeding programs that combine high yield with superior seed quality.\u003c/p\u003e\u003cp\u003eElsewhere macronutriment composition, biochemical constituents such as phenolics and flavonoids contribute to antioxidant activity, which is linked to health benefits and stress resilience. Recent studies highlight the importance of these metabolites in conferring tolerance to drought, heat and disease (Tavares \u003cem\u003eet al.\u003c/em\u003e, 2010). Therefore, integrating biochemical profiling with agronomic evaluation can provide a more comprehensive understanding of varietal performance.\u003c/p\u003e\u003cp\u003eAlthough several studies have evaluated local or improved groundnut genotypes in Cameroon (Noubissi\u0026eacute; \u003cem\u003eet al\u003c/em\u003e., 2012; Dolinassou \u003cem\u003eet al\u003c/em\u003e., 2016), information on recently introduced exotic varieties remains limited. Moreover, the relationships among yield, oil, protein and antioxidant traits under Northern Cameroonian conditions are poorly characterized. The present study was thus conducted to (i) assess the agronomic performance and biochemical composition of fifteen exotic groundnut varieties; (ii) determine correlations among key yield and biochemical parameters and (iii) classify varieties based on their biochemical profiles to identify promising genotypes for further improvement and adaptation in the semi-arid zone of Cameroon.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1. Study area\u003c/h2\u003e\u003cp\u003eThe experiment was conducted during the 2019 to 2021 cropping seasons across three agro-ecological sites in Northern Cameroun: Far-north (Gazawa), North (Bockl\u0026eacute;) and Adamawa (Dang). These locations are representative of Sudanian and Sahelian zone and differ slightly in rainfall, temperature and soil characteristics. Annual rainfall ranges from 800 to 1 100mm, with average daytime temperatures between 27\u003csup\u003eo\u003c/sup\u003eC and 34\u003csup\u003eo\u003c/sup\u003eC. The soils are predominantly sandy loams with moderate organic matter content and slightly acid pH (5.8\u0026ndash;6.4). The choice of site aimed to capture environmental variability relevant to peanut cultivation in the region.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2. Plant material\u003c/h2\u003e\u003cp\u003eFifteen exotic groundnut (\u003cem\u003eArachis hypogaea\u003c/em\u003e L.) varieties were evaluated (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). These genotypes were introduced from the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) in Niger and selected for their reported variability in yield, oil content and disease tolerance. They were divided into two main groups:\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003ethe Virginia group, which is creeping, has a longer vegetative cycle (120 to 150 days) and seeds that do not germinate prematurely;\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003ethe Valencia and Spanish group, which is erect and has a shorter vegetative cycle (80 to 110 days).\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCharacteristics of the 15 varieties of \u003cem\u003eArachis hypogaea\u003c/em\u003e selected for experimentation\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 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colname=\"c7\"\u003e\u003cp\u003e90\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGGP 1397\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eEC106965\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eUSA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eErect\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eSequential\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e90\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGGP 1346\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eUS17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eArgentina\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eErect\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eAlternate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e91\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGGP 927\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e55\u0026ndash;437\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eArgentina\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eErect\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eSequential\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e85\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGGP 434\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSP2B\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eBrazil\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eErect\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eSequential\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e110\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3. Experimental design and crop management\u003c/h2\u003e\u003cp\u003eThe experimental design was a Randomized Complete Block Design (RCBD) with three replications at each site. Each plot measured 3m \u0026times; 2m (6m\u003csup\u003e2\u003c/sup\u003e) and consisted of four rows, spaced 50 cm apart, with a plant spacing of 20 cm within rows.\u003c/p\u003e\u003cp\u003eThe plot was cleaned, ploughed and the ridges were formed, the seeds were removed from their shells, and then the seeds suitable for sowing were selected. No chemical or organic treatments were applied to the plot.\u003c/p\u003e\u003cp\u003eThe soils are clayey-sandy in the Far North, clay-loamy in the North region, and clay-siliceous in Adamawa. The climate is of the Sudano-Sahelian tropical type.\u003c/p\u003e\u003cp\u003e2.4. Agronomic and biochemical parameters measured\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003e\u003cem\u003eAgronomic parameters\u003c/em\u003e:\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003e- Number of pods per plant and number of seeds per plant.\u003c/em\u003e\u003c/p\u003e\u003cp\u003e These were determined on a sample of teen plants per variety and per repetition, then averaged for each variety according to the method described by Abdoul (2003).\u003c/p\u003e\u003cp\u003eNPP = (Ʃ Pods on sampled plants)/n NSP= (Ʃ Seeds on sampled plants)/n\u003c/p\u003e\u003cp\u003eNPP: Number of pods per plant NSP\u0026thinsp;=\u0026thinsp;Number of seeds per plant\u003c/p\u003e\u003cp\u003en: number of plants sampled (n\u0026thinsp;=\u0026thinsp;10)\u003c/p\u003e\u003cp\u003e\u003cem\u003e- Weight of 100 pods\u003c/em\u003e\u003c/p\u003e\u003cp\u003eIn each replicate, 100 pods were collected for each variety and weighed with an electronic balance (sensitivity: 0.01g).\u003c/p\u003e\u003cp\u003e\u003cem\u003e- Pod yield in kilograms per hectare\u003c/em\u003e\u003c/p\u003e\u003cp\u003eThe estimated pod yield was calculated based on a planting density of 90 000 plants/ha, using the formula of Mothilal \u003cem\u003eet al\u003c/em\u003e. (2010):\u003c/p\u003e\u003cp\u003ePod yield (kg/ha) = [(Pod weight \u0026times; Number of pods / 10 000)] \u0026times; 90 000\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003e\u003cem\u003eBiochemical parameters\u003c/em\u003e\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003cp\u003eBiochemical analyses were performed on seeds that had been previously ground using a food processor. For this purpose, 10g of seeds from each variety were ground.\u003c/p\u003e\u003cp\u003e\u003cem\u003e- Protein content\u003c/em\u003e (%)\u003c/p\u003e\u003cp\u003eThe protein content was determined using the Kjeldahl method (AFNOR, 1981) for mineralization and the method of Devani \u003cem\u003eet al\u003c/em\u003e. (1989) for nitrogen determination. The crude protein content was obtained by multiplying nitrogen content by the conventional factor of 6.25.\u003c/p\u003e\u003cp\u003eProtein (%)\u0026thinsp;=\u0026thinsp;Nitrogen (%) \u0026times; 6.25\u003c/p\u003e\u003cp\u003e\u003cem\u003e- Oil content : Soxhlet extraction\u003c/em\u003e (%)\u003c/p\u003e\u003cp\u003eThe Franz Von Soxhlet method is a reference method used to determine the fat content in dehydrated solid foods. It is a gravimetric method, with the sample being weighed before extraction and the fat content at the end of extraction.\u003c/p\u003e\u003cp\u003eOil content (%) = (Mass of extracted fat (g)) / (Mass of sample (g)) \u0026times; 100\u003c/p\u003e\u003cp\u003e\u003cem\u003e- Total polyphenol content\u003c/em\u003e\u003c/p\u003e\u003cp\u003ePolyphenols were determined by spectrophotometry, following the protocol applied by Goli \u003cem\u003eet al\u003c/em\u003e. (2005). The calibration curve was performed using gallic acid at different concentrations (0-250\u0026micro;g/ml), under the same conditions and following the same dosage steps. The results were thus expressed in mg gallic acid equivalent per 100g dry matter (mg GAE/100gDM).\u003c/p\u003e\u003cp\u003e\u003cem\u003e- Antioxidant activity\u003c/em\u003e (%)\u003c/p\u003e\u003cp\u003eEvaluated by the DPPH method (Meda \u003cem\u003eet al\u003c/em\u003e. 2005). The results were expressed as a percentage (%).\u003c/p\u003e\u003cp\u003eAA (%) = ((Abs C \u0026ndash; Abs E) / Abs C) \u0026times; 100\u003c/p\u003e\u003cp\u003eAA (%)\u0026thinsp;=\u0026thinsp;Percentage reduction in DPPH\u003c/p\u003e\u003cp\u003eAbs C\u0026thinsp;=\u0026thinsp;Absorbance of the control\u003c/p\u003e\u003cp\u003eAbs E\u0026thinsp;=\u0026thinsp;Absorbance of the sample\u003c/p\u003e\u003cp\u003eAll analyses were conducted in triplicate to ensure accuracy\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.5. Statistical analysis\u003c/h2\u003e\u003cp\u003eData were analyzed by ANOVA using STATGRAPHICS version 5.0. Means separation was performed using the Less Significant Difference (LSD) test at p\u0026thinsp;\u0026le;\u0026thinsp;0.05. The Pearson correlation coefficient (r) was used to assess relationships between parameters. The formula used is as follows:\u003c/p\u003e\u003cp\u003er\u0026thinsp;=\u0026thinsp;Σ [(Xi \u0026ndash;Xm) \u0026times; (Yi \u0026ndash;Ym)] / [Σ (Xi \u0026ndash;Xm) 2\u0026thinsp;\u0026times;\u0026thinsp;Σ (Yi \u0026ndash;Ym) 2]\u003csup\u003e1/2\u003c/sup\u003e\u003c/p\u003e\u003cp\u003er\u0026thinsp;=\u0026thinsp;Correlation coefficient (-1\u0026thinsp;\u0026le;\u0026thinsp;r \u0026le;\u0026thinsp;1)\u003c/p\u003e\u003cp\u003eXi, Yi\u0026thinsp;=\u0026thinsp;Values of variables X and Y for variety i\u003c/p\u003e\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\stackrel{-}{\\varvec{X}},\\:\\stackrel{-}{\\varvec{Y}}\\)\u003c/span\u003e\u003c/span\u003e : Means of Xi and Yi for all varieties studied\u003c/p\u003e\u003cp\u003eSignificance thresholds: p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 (*) and p\u0026thinsp;\u0026lt;\u0026thinsp;0.01 (**).\u003c/p\u003e\u003cp\u003eThe XLSTAT software was also used for correlations and Hierarchical Ascending Classification (HAC) were performed to classify genotypes based on their yield and biochemical profiles.\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cp\u003e3.1. Agronomic parameters\u003c/p\u003e\u003cp\u003e\u003cem\u003e- Number of pods per plant\u003c/em\u003e\u003c/p\u003e\u003cp\u003eThe mean number of pods per plant ranged from 26.50 to 105.50 among the 15 varieties studied (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Varieties 55\u0026ndash;437 and U12-7-1 recorded the highest values (105.50 and 87.50 pods/plant, respectively). Conversely, the lowest values (26.50 and 35.50) were recorded in genotypes AP80-43 and U4-4-32, followed by variety C75 with 39.50 pods/plant.\u003c/p\u003e\u003cp\u003e\u003cem\u003e- Number of seeds per plant\u003c/em\u003e\u003c/p\u003e\u003cp\u003eThe number of seeds per plant varies between 42.00 and 130.50. The best performances were obtained in varieties 55\u0026ndash;437, 58\u0026ndash;619, C5, R4-A and US17. In contrast, U12-7-1 and AP80-43 had the lowest averages.\u003c/p\u003e\u003cp\u003e\u003cem\u003e- Weight of 100 pods\u003c/em\u003e\u003c/p\u003e\u003cp\u003eThe weight of 100 pods reveals that varieties 58\u0026ndash;619 and AP80-43 stand out with high average weights. In contrast, varieties EC106965 and C5 have the lowest weights (42.57 g and 43.52 g). The other genotypes, notably JH24 and US17, have values that are close to the overall average (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cem\u003e- Pod yield in kg/ha\u003c/em\u003e\u003c/p\u003e\u003cp\u003ePod yield varied significantly among varieties. 58\u0026ndash;619, AP80-43 and C75 ranked highest with 4 767, 4 541 and 4 064 kg/ha respectively (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Intermediate yields were recorded in R4-A (3 521 kg/ha), SP2B (3 462 kg/ha), C29 (3 386 kg/ha), JH24 (3 099kg/ha) and US17 (3 077 kg/ha). The lowest yields were observed in C5 (1 958 kg/ha) and EC106965 (1 916 kg/ha).\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\u003eVariability of agronomic parameters of 15 exotic varieties of \u003cem\u003eArachis hypogaea\u003c/em\u003e in Northern Cameroon\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\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\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;Parameters\u003c/p\u003e\u003cp\u003eGenotypes\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNumber of pods per plant\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNumber of seeds per plant\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eWeight of 100 pods (g)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ePod yield in kg/ha\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eC5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e42.00\u0026thinsp;\u0026plusmn;\u0026thinsp;2,82b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e96.00\u0026thinsp;\u0026plusmn;\u0026thinsp;7.31e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e43.52\u0026thinsp;\u0026plusmn;\u0026thinsp;0.38a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1 958\u0026thinsp;\u0026plusmn;\u0026thinsp;43a\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRCM439\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e45.00\u0026thinsp;\u0026plusmn;\u0026thinsp;5,65bc\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e67.50\u0026thinsp;\u0026plusmn;\u0026thinsp;9.89cd\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e60.54\u0026thinsp;\u0026plusmn;\u0026thinsp;15.63b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2 725\u0026thinsp;\u0026plusmn;\u0026thinsp;138b\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eJH24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e52.00\u0026thinsp;\u0026plusmn;\u0026thinsp;2,82cd\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e76.00\u0026thinsp;\u0026plusmn;\u0026thinsp;36.76de\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e68.87\u0026thinsp;\u0026plusmn;\u0026thinsp;3.90bcd\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3 099\u0026thinsp;\u0026plusmn;\u0026thinsp;234bcd\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eU12-7-1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e87.50\u0026thinsp;\u0026plusmn;\u0026thinsp;21,21f\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e42.00\u0026thinsp;\u0026plusmn;\u0026thinsp;14.14a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e61.29\u0026thinsp;\u0026plusmn;\u0026thinsp;7.33b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2 758\u0026thinsp;\u0026plusmn;\u0026thinsp;240b\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEC21164\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e53.00\u0026thinsp;\u0026plusmn;\u0026thinsp;22,62c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e76.00\u0026thinsp;\u0026plusmn;\u0026thinsp;4.42de\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e63.97\u0026thinsp;\u0026plusmn;\u0026thinsp;5.13bc\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2 879\u0026thinsp;\u0026plusmn;\u0026thinsp;308bc\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eU4-4-32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e35.50\u0026thinsp;\u0026plusmn;\u0026thinsp;11,31ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e50.50\u0026thinsp;\u0026plusmn;\u0026thinsp;11.20abc\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e64.17\u0026thinsp;\u0026plusmn;\u0026thinsp;13.17bc\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2 888\u0026thinsp;\u0026plusmn;\u0026thinsp;290bc\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e58\u0026ndash;619\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e69.50\u0026thinsp;\u0026plusmn;\u0026thinsp;7,07d\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e113.00\u0026thinsp;\u0026plusmn;\u0026thinsp;31.11g\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e105.93\u0026thinsp;\u0026plusmn;\u0026thinsp;20.32fg\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4 767\u0026thinsp;\u0026plusmn;\u0026thinsp;219g\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eC29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e47.50\u0026thinsp;\u0026plusmn;\u0026thinsp;12,72bc\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e73.00\u0026thinsp;\u0026plusmn;\u0026thinsp;4.41cd\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e75.25\u0026thinsp;\u0026plusmn;\u0026thinsp;13.80bcd\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3 386\u0026thinsp;\u0026plusmn;\u0026thinsp;228cde\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAP80-43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e26.50\u0026thinsp;\u0026plusmn;\u0026thinsp;1,41a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e48.00\u0026thinsp;\u0026plusmn;\u0026thinsp;9.50a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e116.40\u0026thinsp;\u0026plusmn;\u0026thinsp;11.96g\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4 541\u0026thinsp;\u0026plusmn;\u0026thinsp;227g\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eC75\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e39.50\u0026thinsp;\u0026plusmn;\u0026thinsp;7,07b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e68.00\u0026thinsp;\u0026plusmn;\u0026thinsp;5.43cde\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e90.32\u0026thinsp;\u0026plusmn;\u0026thinsp;4.79ef\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4 064\u0026thinsp;\u0026plusmn;\u0026thinsp;287f\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eR4-A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e68.50\u0026thinsp;\u0026plusmn;\u0026thinsp;1,41d\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e95.00\u0026thinsp;\u0026plusmn;\u0026thinsp;12.62f\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e78.24\u0026thinsp;\u0026plusmn;\u0026thinsp;10.43de\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3 521\u0026thinsp;\u0026plusmn;\u0026thinsp;326e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEC106965\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e50.00\u0026thinsp;\u0026plusmn;\u0026thinsp;5,67c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e64.50\u0026thinsp;\u0026plusmn;\u0026thinsp;8.38bc\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e42.57\u0026thinsp;\u0026plusmn;\u0026thinsp;2.37a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1 916\u0026thinsp;\u0026plusmn;\u0026thinsp;142a\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUS17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e62.50\u0026thinsp;\u0026plusmn;\u0026thinsp;12,72d\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e93.00\u0026thinsp;\u0026plusmn;\u0026thinsp;8.48f\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e68.38\u0026thinsp;\u0026plusmn;\u0026thinsp;12.20bcd\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3 077\u0026thinsp;\u0026plusmn;\u0026thinsp;472bcd\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e55\u0026ndash;437\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e105.50\u0026thinsp;\u0026plusmn;\u0026thinsp;25,45g\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e130.50\u0026thinsp;\u0026plusmn;\u0026thinsp;8.38h\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e63.63\u0026thinsp;\u0026plusmn;\u0026thinsp;12.75bc\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2 863\u0026thinsp;\u0026plusmn;\u0026thinsp;125bc\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSP2B\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e42.50\u0026thinsp;\u0026plusmn;\u0026thinsp;4,24bc\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e61.50\u0026thinsp;\u0026plusmn;\u0026thinsp;9.89b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e76.94\u0026thinsp;\u0026plusmn;\u0026thinsp;5.28cde\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3 462\u0026thinsp;\u0026plusmn;\u0026thinsp;317de\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMeans\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e55.13\u0026thinsp;\u0026plusmn;\u0026thinsp;9,61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e76.96\u0026thinsp;\u0026plusmn;\u0026thinsp;13.47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e72.00\u0026thinsp;\u0026plusmn;\u0026thinsp;13.30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3 194\u0026thinsp;\u0026plusmn;\u0026thinsp;565\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCV (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e17.43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e17.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e18.47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e13.55\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\u003eNPP: Number of pods per plant; NSP: Number of seeds per plant; W100P: Weight of 100 pods; PY: Pod yield in kilograms per hectare; %L: Lipid content; %P: Protein content; PPT: Total polyphenol content; AOA: Antioxidant activity; CV: Coefficient of variation.\u003c/p\u003e\u003cp\u003e3.2. Biochemical parameters\u003c/p\u003e\u003cp\u003e\u003cem\u003e- Protein content\u003c/em\u003e\u003c/p\u003e\u003cp\u003eAnalysis of the protein content of exotic peanut varieties grown in the Northern Zone reveals significant variability (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The highest values were recorded in US17 (28.73%) and RCM439 (27.66%). These values suggest interesting potential for selection programs aimed at protein enrichment. However, the SP2B and 58\u0026ndash;619 varieties have lower protein contents than the previous ones, with values of 19.80% and 19.40%, indicating lower nutritional quality in terms of protein. The US17 variety produced the highest protein level throughout the study area (28.73%).\u003c/p\u003e\u003cp\u003e\u003cem\u003e- Lipid content\u003c/em\u003e\u003c/p\u003e\u003cp\u003eLipid levels ranged from 37.76% to 55.33%. Varieties 58\u0026ndash;619 and U4-4-32 showed the highest contents (55.33% and 51.53%), suggesting particular interest for industrial use geared towards oil production. In contrast, the RCM439 and US17 varieties have lower values, ranging from 37.76% to 40.10%, reflecting a more moderate lipid composition.\u003c/p\u003e\u003cp\u003e\u003cem\u003e- Total polyphenol content\u003c/em\u003e\u003c/p\u003e\u003cp\u003eThe results of the analysis of variance show a statistically significant difference in total polyphenol content between varieties (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Genotypes 58\u0026ndash;619 and R4-A stand out with high contents, ranging from 1.73 to 1.67 mg GAE/100g, reflecting good potential in antioxidant compounds. The EC21164 and C75 varieties followed with an average content of 1.57mgGAE/100g. The ten other varieties had concentrations ranging from 1.51mgGAE/100g (RCM439) to 1.16mgGAE/100g (SP2B), reflecting notable biochemical diversity.\u003c/p\u003e\u003cp\u003e\u003cem\u003e- Antioxidant activity\u003c/em\u003e\u003c/p\u003e\u003cp\u003eThe evaluation of the antioxidant activity of the seeds, measured by the DPPH radical scavenging method, highly significant differences between genotypes (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Variety 58\u0026ndash;619 has the highest antioxidant activity, reaching 79.33%, which indicates high functional potential. Varieties EC21164 and R4-A follow closely behind, with levels of 77.76% and 76.73% respectively. In contrast, the SP2B and 55\u0026ndash;437 varieties had the lowest capacities, ranging from 56.33% to 55.16% (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e3\u003c/span\u003e). These results highlight the potential of certain genotypes for nutritional or nutraceutical applications related to their antioxidant properties.\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 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eVariability of biochemical parameters of 15 exotic varieties of \u003cem\u003eArachis hypogaea\u003c/em\u003e in northern Cameroon\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\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\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;Parameters\u003c/p\u003e\u003cp\u003eGenotypes\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eProtein content\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eLipid content\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTotal polyphenol content\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAntioxidant activity in seeds\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eC5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e26.26\u0026thinsp;\u0026plusmn;\u0026thinsp;1,05hg\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e41.10\u0026thinsp;\u0026plusmn;\u0026thinsp;0,95bc\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.41\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11bcd\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e73.16\u0026thinsp;\u0026plusmn;\u0026thinsp;1,15e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRCM439\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e27.66\u0026thinsp;\u0026plusmn;\u0026thinsp;2,23g\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e37.76\u0026thinsp;\u0026plusmn;\u0026thinsp;1,15a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.51\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07cd\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e71.83\u0026thinsp;\u0026plusmn;\u0026thinsp;0,83e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eJH24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e25.83\u0026thinsp;\u0026plusmn;\u0026thinsp;0,23f\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e41.36\u0026thinsp;\u0026plusmn;\u0026thinsp;0,66bcd\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.47\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09cd\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e66.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0,58d\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eU12-7-1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e25.03\u0026thinsp;\u0026plusmn;\u0026thinsp;1,05efg\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e46.00\u0026thinsp;\u0026plusmn;\u0026thinsp;1,78ef\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.37\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11bcd\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e62.30\u0026thinsp;\u0026plusmn;\u0026thinsp;0,36c\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEC21164\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e22.93\u0026thinsp;\u0026plusmn;\u0026thinsp;0,61cde\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e44.26\u0026thinsp;\u0026plusmn;\u0026thinsp;1,35de\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.57\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12de\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e77.76\u0026thinsp;\u0026plusmn;\u0026thinsp;0,72f\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eU4-4-32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e20.06\u0026thinsp;\u0026plusmn;\u0026thinsp;1,20ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e51.53\u0026thinsp;\u0026plusmn;\u0026thinsp;2,40g\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.33\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e61.03\u0026thinsp;\u0026plusmn;\u0026thinsp;0,63d\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e58\u0026ndash;619\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e19.40\u0026thinsp;\u0026plusmn;\u0026thinsp;0,70a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e55.33\u0026thinsp;\u0026plusmn;\u0026thinsp;2,30h\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.73\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e79.33\u0026thinsp;\u0026plusmn;\u0026thinsp;0,70f\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eC29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e24.06\u0026thinsp;\u0026plusmn;\u0026thinsp;1,20def\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e43.53\u0026thinsp;\u0026plusmn;\u0026thinsp;1,30cde\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.38\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06bcd\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e71.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0,34e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAP80-43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e20.86\u0026thinsp;\u0026plusmn;\u0026thinsp;1,05abc\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e48.76\u0026thinsp;\u0026plusmn;\u0026thinsp;1,56fg\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.33\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e59.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0,32b\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eC75\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e24.46\u0026thinsp;\u0026plusmn;\u0026thinsp;1,15ef\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e40.83\u0026thinsp;\u0026plusmn;\u0026thinsp;0,55ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.57\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11de\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e70.96\u0026thinsp;\u0026plusmn;\u0026thinsp;0,41de\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eR4-A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e23.53\u0026thinsp;\u0026plusmn;\u0026thinsp;2,30def\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e44.06\u0026thinsp;\u0026plusmn;\u0026thinsp;0,37cde\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.67\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e76.73\u0026thinsp;\u0026plusmn;\u0026thinsp;0,51f\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEC106965\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e23.83\u0026thinsp;\u0026plusmn;\u0026thinsp;2,05def\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e42.03\u0026thinsp;\u0026plusmn;\u0026thinsp;0,40bcd\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.36\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04abc\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e65.23\u0026thinsp;\u0026plusmn;\u0026thinsp;0,73c\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUS17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e28.73\u0026thinsp;\u0026plusmn;\u0026thinsp;1,23g\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e40.10\u0026thinsp;\u0026plusmn;\u0026thinsp;1,36ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.39\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06bcd\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e59.60\u0026thinsp;\u0026plusmn;\u0026thinsp;0,34b\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e55\u0026ndash;437\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e21.90\u0026thinsp;\u0026plusmn;\u0026thinsp;0,65bcd\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e46.00\u0026thinsp;\u0026plusmn;\u0026thinsp;1,17ef\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.26\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e55.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0,51a\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSP2B\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e19.80\u0026thinsp;\u0026plusmn;\u0026thinsp;0,75ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e50.60\u0026thinsp;\u0026plusmn;\u0026thinsp;1,20g\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e56.33\u0026thinsp;\u0026plusmn;\u0026thinsp;0,64a\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMeans\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e23.62\u0026thinsp;\u0026plusmn;\u0026thinsp;2,18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e44.88\u0026thinsp;\u0026plusmn;\u0026thinsp;3,23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.43\u0026thinsp;\u0026plusmn;\u0026thinsp;0.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e67.05\u0026thinsp;\u0026plusmn;\u0026thinsp;6,58\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCV(%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e9.23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e11.89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e9.81\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\u003eNPP: Number of pods per plant; NSP: Number of seeds per plant; W100P: Weight of 100 pods; PY: Pod yield in kilograms per hectare; %L: Lipid content; %P: Protein content; PPT: Total polyphenol content; AOA: Antioxidant activity; CV: Coefficient of variation.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e3.3 Correlations between yield and biochemical parameters\u003c/h2\u003e\u003cp\u003eThe weight of 100 pods (W100P) was strongly and positively correlated with yield (PY) (r\u0026thinsp;=\u0026thinsp;0.97); total polyphenol content (PPT) and antioxidant activity (AOA) with r\u0026thinsp;=\u0026thinsp;0.91; and the number of pods (NPP) and the number of seeds (NSP) with r\u0026thinsp;=\u0026thinsp;0.77. The weight of 100 pods (W100P) was positively and moderately correlated with the lipid content (%L) (r\u0026thinsp;=\u0026thinsp;0.50) and negatively correlated with protein content (%P) (r=-0.49) (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eSimilarly, the Pod yield per hectare was positively and moderately related to the total polyphenol content (PPT): r\u0026thinsp;=\u0026thinsp;0.30, positively correlated with the antioxidant activity (AOA) of peanut seeds. Lipid content (%L) was strongly and negatively correlated with the protein content (%P) (r\u0026thinsp;=\u0026thinsp;0.90). It was also negatively correlated with polyphenol content and antioxidant activity.\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 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCorrelation matrix between agronomic and biochemical 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=\"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\u003cdiv align=\"left\" 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\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNPP\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNSP\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eW100P\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ePY\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e%L\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003e%P\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003ePPT\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003eAOA\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNPP\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNSP\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.77*\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\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eW100P\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.24ns\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\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePY\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.97**\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\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e%L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.40\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\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e%P\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.90**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePPT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.18ns\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAOA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.91**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e1\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\u003eNPP: Number of pods per plant; NSP: Number of seeds per plant; W100P: Weight of 100 pods; PY: Pod yield; %L: Lipid content; %P: Protein content; PPT: Total polyphenol content; AOA: Antioxidant activity; CV: Coefficient of variation.\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThe present study revealed significant variability among the 15-exotic peanut (\u003cem\u003eArachis hypogaea\u003c/em\u003e L.) varieties grown in Northern Cameroun, particularly in pod yield, seed weight and biochemical quality traits. The strong positive correlation observed between pod weight and yield (r\u0026thinsp;=\u0026thinsp;0.97) confirms that seed mass is a major determinant of productivity, consistent with earlier results by Dolinassou \u003cem\u003eet al\u003c/em\u003e. (2016) and recent multi-environment analyses by Wang \u003cem\u003eet al\u003c/em\u003e. (2023), who demonstrated that kernel size and weight remain the most heritable yield-related traits across diverse agro-ecological zones. Similarly, new genome wide association studies (GWAS) have identified key loci controlling pod weight and yield stability, notably on chromosomes A05 and B03 (Wang \u003cem\u003eet al\u003c/em\u003e., 2024), supporting the genetic basic of these agronomic correlations.\u003c/p\u003e\u003cp\u003eThe variability in seed protein and lipid contents among varieties aligns with previous observations from Ghana (Asibuo \u003cem\u003eet al\u003c/em\u003e., 2008) and Cameroon (Noubissi\u0026eacute; \u003cem\u003eet al\u003c/em\u003e., 2012). while recent genomic studies have demonstrated that oil and protein biosynthesis are inversely regulated at the molecular level (Wang \u003cem\u003eet al\u003c/em\u003e., 2023; Liu \u003cem\u003eet al.\u003c/em\u003e, 2019). This trade-off was also evident in our study, where lipid content was negatively correlated with protein content (0.90). Recent pangenomic analyses involving 269 accessions have shown that structural variants within the \u003cem\u003eAharf 2\u0026ndash;2\u003c/em\u003e gene regulate seed size and oil accumulation (Kunkun \u003cem\u003eet al.\u003c/em\u003e, 2025), providing a molecular explanation for these biochemical contrasts observed in local varieties.\u003c/p\u003e\u003cp\u003eThe lipid content range (37.7\u0026ndash;55.3%) obtained in this study is consistent with findings from recent evaluations in West Africa and Asia, confirming the adaptability of high oil genotypes to semi-arid conditions (Swathi \u003cem\u003eet al.\u003c/em\u003e,2023). Moreover, new high protein lines developed in China between 2023 and 2025 (Li \u003cem\u003eet al\u003c/em\u003e., 2025) achieved protein contents exceeding 30%, suggesting that integrating molecular makers for both traits may overcome the classical negative correlation between oil and protein concentrations.\u003c/p\u003e\u003cp\u003eRegarding antioxidant activity and total phenol content, our results (up to 79.33% DPPH activity and 1.73 mg GAE/100g) indicate high nutraceutical potential. This agrees with recent biochemical studies showing that phenol compounds in peanuts especially resveratrol, proanthocyanidins and flavonoids are key determinants of antioxidant defense under stress (Tavares \u003cem\u003eet al.\u003c/em\u003e, 2010; Devi \u003cem\u003eet al.\u003c/em\u003e, 2019). In 2024, transcriptomic analyses of \u003cem\u003eA. hypogaea\u003c/em\u003e under \u003cem\u003eRalstonia solanacearum\u003c/em\u003e infection revealed upregulation of genes related to phenylpropanoid and flavonoid pathways (Wang \u003cem\u003eet al.\u003c/em\u003e, 2024), corroborating the association we found between polyphenols and antioxidant activity (r\u0026thinsp;=\u0026thinsp;0.91). These results suggest that biochemical traits could serve as indicators of both nutritional value and stress tolerance.\u003c/p\u003e\u003cp\u003eRecent progress in peanut breeding further reinforces these findings. Quantitative trait locus (QTL) mapping and GWAS have identified genomic regions linked to disease resistance, including \u003cem\u003ePSWDR-1\u003c/em\u003e for Tomato Spotted Wilt Virus (Dongliang \u003cem\u003eet al\u003c/em\u003e., 2025) and several loci conferring resistance to stem rot (Veerendrakumar \u003cem\u003eet al\u003c/em\u003e, 2025). These discoveries support marker assisted selection for high-yield and high-quality genotypes. Furthermore, the application of tissue culture free genome editing approaches such as CRISPR is accelerating improvement of traits like oil composition, drought tolerance and allergen reduction (Alam, 2025).\u003c/p\u003e\u003cp\u003eThe strong phenotypic associations found in this study may reflect coordinated metabolic networks regulating lipid and protein biosynthesis (Wang \u003cem\u003eet al.\u003c/em\u003e, 2019). Environmental stresses, particularly temperature and water deficit, are also know to influence these processes (Zhao \u003cem\u003eet al\u003c/em\u003e., 2011). Integrating such physiological and molecular understanding into local breeding programs could enhance the development of peanut cultivars adapted to the semi-arid zones of Northern Cameroon.\u003c/p\u003e\u003cp\u003eGrouping of varieties into three biochemical clusters (protein, polyphenol, lipid) is consistent with current global strategies for peanut value-chain diversification (Li \u003cem\u003eet al\u003c/em\u003e, 2025). Similar approaches combining rhizobial inoculation and mycorrhizal symbiosis have been reported to improve both yield and nutritional composition under West and central African conditions (Igiehon \u003cem\u003eet al.\u003c/em\u003e, 2021; Mpongwana \u003cem\u003eet al.\u003c/em\u003e, 2023; Ajayi \u003cem\u003eet al.\u003c/em\u003e, 2024).\u003c/p\u003e\u003cp\u003eOverall, the integration of agronomic and biochemical traits in this study offers a comprehensive framework for the genetic improvement of \u003cem\u003eArachis hypogaea\u003c/em\u003e. The correlations observed mirror recent global findings and confirm that the concurrent enhancement of yield, oil content and antioxidant potential is feasible through combined molecular breeding and agronomic practices.\u003c/p\u003e"},{"header":"5. Grouping of varieties","content":"\u003cp\u003eWith a view to improving agro-nutritional qualities, the quality of the harvested product and the availability of varieties for peanut production in semi-arid areas, the adoption of relatively more plastic and more suitable varieties that require less intensive technical inputs. In addition, genetic variability is the basic condition for crop improvement, as it provides a wider germplasm for varietal selection. Confectionery and oilseed varieties could be distinguished from food varieties in order to enhance the peanut sector both nutritionally and commercially in this Northern Zone of Cameroon.\u003c/p\u003e\u003cp\u003eThe Ascending Hierarchical Classification (AHC) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) allowed the fifteen varieties studied to be classified into three classes:\u003c/p\u003e\u003cp\u003eClass 1: Varieties with protein contents between 20 and 30% are considered to have a high protein content, a finding also reported by Pinstrup Andersen \u003cem\u003eet al\u003c/em\u003e. (1999) for peanuts. Varieties C5, U12-7-1, EC106965, US17, and 55\u0026ndash;437 have the highest protein contents in this study. They can be used as \u0026ldquo;\u003cem\u003esnack peanuts\u003c/em\u003e\u0026rdquo; and as part of a food supplement for infants, which would help combat severe malnutrition among children in the North Cameroon region (Brouwer \u003cem\u003eet al\u003c/em\u003e., 2004).\u003c/p\u003e\u003cp\u003eClass 2: The varieties RCM439, JH24, EC21164, C29 and C75 are characterized by an average protein content, high polyphenol content and high antioxidant activity (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e3\u003c/span\u003e). These varieties can be recommended for confectionery and could help reduce the risk of cardiovascular disease and certain cancers (Mukuddem-Petersen \u003cem\u003eet al\u003c/em\u003e., 2005). The high polyphenol content, which is positively correlated with pods yield in kg/ha, suggests that the varieties have potential in terms of both polyphenol content and pods yield in kg/ha and could be selected for use as \u0026ldquo;\u003cem\u003esnack peanuts\u0026rdquo;\u003c/em\u003e. The Virginia type is the most recommended in this case, and the C29 variety would be the most readily available in the North Cameroon region for use as snack peanuts.\u003c/p\u003e\u003cp\u003eClass 3: The varieties U4-4-32, 58\u0026ndash;619, AP80-43, R4-A and SP2B are characterized by a pod yield in kg/ha and a high lipid content, a polyphenol content and average antioxidant activity. These varieties have agronomic and biochemical potential that could be part of an extension program in northern Cameroon as oilseed peanuts. In this class, varieties 58\u0026ndash;619 and AP80-43 are more suitable for oil production (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe study shows that there is significant variability among the 15 exotic peanut varieties grown in northern Cameroon. The weight of 100 pods (W100P) is strongly and positively correlated with yield (PY); Pod yield is positively correlated with lipid content, total polyphenol content and antioxidant activity, but negatively correlated with protein content. The number of pods per plants (NPP) and the number of seeds per plants (NSP) show a very high positive correlation. The identification of stable correlations between agronomic and biochemical traits offers an opportunity for breeders to combine yield and nutritional quality in the same breeding program. However, certain unfavorable correlations, such as that between yield and protein content, require compromises or the use of marker-assisted selection techniques to dissociate linked genetic traits. These results also pave the way for varietal selection that integrates both agronomic performance and biochemical quality in response to the nutritional and economic challenges of the region. Further studies, particularly in functional genomics and multi-location trials, will be necessary to validate the stability of these correlations in different agroecological environments.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eCorresponding Author:\u003c/p\u003e\n\u003cp\u003eDounia D\u0026eacute;sir\u0026eacute;, Department of Sustainable Agriculture and Disaster Management, Faculty of Science, University of Garoua. P.O. Box 346, Garoua-Cameroon, E-Mail: [email protected]\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAcknowledgements\u003c/p\u003e\n\u003cp\u003eThe authors thank the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) for peanut seeds supplied for this study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAuthors\u0026rsquo; contributions\u003c/p\u003e\n\u003cp\u003eConceptualization: D. D\u0026eacute;sir\u0026eacute;, Methodology: D. D\u0026eacute;sir\u0026eacute; and J-B Tchiagam Noubissie. Formal Analysis: D. D\u0026eacute;sir\u0026eacute;, O. H. Z\u0026eacute;phirin and N. M. Antoine, writing original draft: D. D\u0026eacute;sir\u0026eacute;, Writing-review and editing: D. Dounia, A. A. Said, K. Maygong, O. H. Z\u0026eacute;phirin, N. M. Antoine and J-B Tchiagam Noubissie, Acquisition: D. D\u0026eacute;sir\u0026eacute; and J-B Tchiagam Noubissie, Supervision: J-B Tchiagam Noubissie. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003eFunding Declaration\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003eData Availability Statement\u003c/p\u003e\n\u003cp\u003eThe datasets generated and/or analysed during the current study are available from the corresponding author on reasonable request.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCompeting Interest Declaration\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe authors declare that there are no competing interests.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003cp\u003eAbdoul, H.Z., 2003. Effets of seed quality on groundnut (\u003cem\u003eArachis hypogaea\u003c/em\u003e) production in Senegal. \u003cem\u003eMaster’s Thesis, Ecole Nationale Supérieure d’Agriculture (ENSA), Dakar, Senegal, 59pp. \u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eAdanga, P.G., Mamba, G., Ngama, F., Litucha, J., Okungo, A., 2024. Effet of sowing dates and densities on groundnut (\u003cem\u003eArachis hypogaea\u003c/em\u003e) yield in Isiro region, Haut-Uélé Province, DR Congo.\u003cem\u003e Journal of Research in Humanities and Social Science. \u003c/em\u003e12(10) : 82-88.\u003c/p\u003e\n\u003cp\u003eAFNOR., 1981\u003cem\u003e. \u003c/em\u003eFat, \u003cem\u003eOilseeds and derived products, 2\u003csup\u003end\u003c/sup\u003e edition. \u003c/em\u003eAFNOR, Paris, France, 438pp.\u003c/p\u003e\n\u003cp\u003eAlleidi, I., Hamidou, F., Younoussa, O.M., Bakasso, Y., Zongo, J.D., 2016. Agro-morphological characterization of groundnut (\u003cem\u003eArachis hypogaea\u003c/em\u003e) accessions for oil content. \u003cem\u003eEuropean Scientific Journal, \u003c/em\u003e15 (12): 1857-7881.\u003c/p\u003e\n\u003cp\u003eAgri-stat Cameroon, 2012. \u003cem\u003eYearbook of agricultural statistics. \u003c/em\u003eMinistry of Agriculture and Rural development (MINADER), Yaoundé, Cameroon, 123pp.\u003c/p\u003e\n\u003cp\u003eAjayi, O.O., Dianda, M., Fagade, O.E., 2024. Rhizobia inoculation’s impact on the biomass and moisture content of leguminous Bambara groundnut (\u003cem\u003eVigna subterranean \u003c/em\u003eL. Verdc). \u003cem\u003eDiscover Sustain.\u003c/em\u003e5;315. https://doi.org/10.1007/s43621-024-00502-0. \u003c/p\u003e\n\u003cp\u003eAlam, T., 2025. Advances in tissue culture-free genetic engineering and genome editing of peanut. \u003cem\u003eMol. Biotechnol.\u003c/em\u003e https://doi.org/10.1007/s12033-025-01476-8.\u003c/p\u003e\n\u003cp\u003eAsibuo, J. Y., Akrmah, R., Safo-Katanka, O., Adu-Dapaah, H.K., Ohemeng-Dapaah, S., Agyeman, A., 2008. Chemical composition of groundnut (\u003cem\u003eArachis hypogaea \u003c/em\u003eL.) landraces. \u003cem\u003eAfrican Journal of Biotechnogy., \u003c/em\u003e7(13): 2203-2208. https://doi.org/10.5897/AJB08.024.\u003c/p\u003e\n\u003cp\u003eBetdogo, S., Sali, B., Adamou, I., Woin, N., 2015. Agronomic evaluation of five groundnut cultivars (\u003cem\u003eArachis hypogaea \u003c/em\u003eL.) introduced in the North Region of Cameroon. \u003cem\u003eJournal of Applied Biosciences\u003c/em\u003e, 89: 8311– 8319. https://doi.org/10.1093/jn/134.4.919.\u003c/p\u003e\n\u003cp\u003eCheikh, T., 2008. Bioactivity of extracts from \u003cem\u003eCalotropis procera \u003c/em\u003eand \u003cem\u003eSenna occidentalis \u003c/em\u003eL. on \u003cem\u003eCaryedon serratus\u003c/em\u003e, a pest of peanut stocks and seeds in Senegal. PhD Thesis, Cheikh Anta Diop University of Dakar, Senegal,196pp. https://hdl.handle.net/20.500.12177/2889. \u003c/p\u003e\n\u003cp\u003eBrouwer, I.A., Katan, M.B., Zock, P.L., 2004. Dietary alpha-linolenic acid is associated with reduced risk of fatal coronary heart disease, but increased prostate cancer risk: a meta-analysis. \u003cem\u003eJournal of Nutrition\u003c/em\u003e. 134 : 919-922. https://doi.org/10.1093/jn/134.4.919.\u003c/p\u003e\n\u003cp\u003eDapoigny, L., Tourdonnet, S., Eestrade, J.R., Jeuffroy, M.H., Fleury, A., 2000. Effect of nitrogen nutrition on growth and nitrate accumulation in lettuce (\u003cem\u003eLactuca sativa \u003c/em\u003eL.), under various conditions of radiation and temperature. \u003cem\u003eAgriculture, Ecosystems \u0026amp; Environment, \u003c/em\u003e20: 843–855. https://doi.org/10.1016/S0167-8809(99)00103-6.\u003c/p\u003e\n\u003cp\u003eDevani, M.B., Sioshoo, J.C., Shal, S.A., Suhagia, B.N., 1989. Spectrophotometrical method for micro-determination of nitrogen in Kjedalh digest. \u003cem\u003eJ. Ass. Off. Anal. Chem\u003c/em\u003e., 72(6): 953-956. https://doi.org/ 10.1093/jaoac/72.6.953.\u003c/p\u003e\n\u003cp\u003eDolinassou, S., Noubissié, T.J.B., Djiranta, K.A., Njintang, Y.N., 2016. Genotype × environment interaction and kernel yield-stability of groundnut (\u003cem\u003eArachis hypogaea \u003c/em\u003eL.) in Northern Cameroon. \u003cem\u003eJournal of Applied Biology and Biotechnolgy\u003c/em\u003e, 4 (01): 1-7. https://doi.org/10.7324/JABB.2016.40101.\u003c/p\u003e\n\u003cp\u003eDolinassou, S., Noubissié, T.J.B., Malhala, M., Nguimbou, R.M., Njintang, Y.N., 2017. Genotype × environment interaction and oil content stability analysis of groundnut (\u003cem\u003eArachis hypogaea \u003c/em\u003eL.) in Northern Cameroon. \u003cem\u003eJournal Plant Breeding and Crop Science\u003c/em\u003e, 9 (4): 45-53. https://doi.org/10.5897/JPBCS. 2017.0647.\u003c/p\u003e\n\u003cp\u003eDongliang W., Chuanzhi Z., Walid K., Ethan A.T., Hui W., Gaurav A., Jake C. F., Albert C., Corley H. C., Xingjun W., Josh P. C., Baozhu G., 2025. High-resolution genetic and physical\u003cbr\u003emapping reveals a peanut spotted wilt disease resistance locus, \u003cem\u003ePSWDR-1\u003c/em\u003e, to Tomato spotted\u003cbr\u003ewilt virus (TSWV), within a recombination coldspot on chromosome A01. \u003cem\u003eBMC Genomics.\u003c/em\u003e26: 224. https://doi.org/10.1186/s12864-025-11366-7.\u003c/p\u003e\n\u003cp\u003eFood and Agriculture Organization of the United Nations (FAO), 2023. FAO in Africa: \u003cem\u003ehighlights in 2023. \u003c/em\u003eRome FAO. https://openknowledge.fao.org/handle/20.500.11766.\u003c/p\u003e\n\u003cp\u003eFAOSTAT, 2014. Statistical database of the Food and Agriculture Organization of the United Nations.\u003c/p\u003e\n\u003cp\u003eGoli, A.H., Barzeger, M., Sahari, M.A., 2005. Antioxidant activity and total phenolic compounds of pistachio (\u003cem\u003ePistachia vera\u003c/em\u003e)hull extracts. \u003cem\u003eFood Chemistry. \u003c/em\u003e92:521-525. https://doi.org/10.1016/j.foodchem.2004.08.020.\u003c/p\u003e\n\u003cp\u003eHowell, R. W., Collins, R. F., 1957. Factors affecting linolenic and linoleic acid content of soybean oil. \u003cem\u003eAgron. J. \u003c/em\u003e49: 593-597. https://doi.org/10.2134/agronj1957.00021962004900120014x.\u003c/p\u003e\n\u003cp\u003eIgiehon, N.O., Babalola, O.O., Cheseto, X., Torto, B., 2021. Effects of Rhizobia and arbuscular mycorrhizal fungi on yield, size distribution and fatty acid of soybean seeds grown under drought stress. \u003cem\u003eMicrobiol. Res. \u003c/em\u003e242:126640. https://doi.org/10.1016/j.micres.2020.126640.\u003c/p\u003e\n\u003cp\u003eKatim, T., Tamsir, M., Diatta, P.M., Foncéka, D., Issa, F., Bradford, M., 2022. Use of improved varieties in the peanut basin of Senegal.\u003c/p\u003e\n\u003cp\u003eKhaled, S., 2008. Contribution to the study of adaptation of durum wheat cutivars (\u003cem\u003eTriticum durum\u003c/em\u003e) to organic farming: grain yield stability, quality technology and died. Doctoral Thesis, Montpelier 171pp.\u003c/p\u003e\n\u003cp\u003eKunkun, Z., Hongzhang, X., Guowei, L., Annpurna, C., Yi F., Zenghui, C.,Xiaourui, D., Huimim L., Kai, Z., Lin, Z., Ding Qiu, Rui Ren, Fangping G., Zhongfeng L., Xingli, M., Shubo, W., Rajeev, K. V., Chaochun, W., Dongmei Y., 2025. Pangenome analysis structural variation associated with seed size and weight trait in peanut.\u003cem\u003e Nature Genetics\u003c/em\u003e. https://doi.org/10.1038/s41588-025-025-02170-w.\u003c/p\u003e\n\u003cp\u003eLarson, R.A., 1988. The antioxidants of higher plants. \u003cem\u003ePhytochemistry\u003c/em\u003e. 27(4) : 969-978. https://doi.org/10.1016/0031-9422(88)80254-1.\u003c/p\u003e\n\u003cp\u003eLi, Z., Zhang, Y., Liu, Y., Fan, Y., Qiu, D., Li, Z., Gong, F., Yin, D., 2025. Research Progress on high-protein peanut (\u003cem\u003eArachis hypogaea \u003c/em\u003eL.) varieties in China. \u003cem\u003ePlant, \u003c/em\u003e14(18): 2917. https://doi.org/10.3390/plants14182917.\u003c/p\u003e\n\u003cp\u003eLiu, N., Guo, J., Zhou, X., Wu, B., Huang, L., Luo, H.Y., Chen, Y.N., Chen, W.G., Lei, Y., Huang, Y., Liao, B.S., Jiang, H.F., 2019. High-resolution Mapping of a Major and Consensus Quantitative Trait Locus for Oil Content to a 0.8-Mb Region on Chromosome A08 in Peanut (\u003cem\u003eArachis hypogaea\u003c/em\u003e L.). \u003cem\u003eTheoretical and Applied Genetics\u003c/em\u003e 133, 37-49. https://doi.org/10.1007/s00122-019-03438-6.\u003c/p\u003e\n\u003cp\u003eMagrin, G., 2003. A market-orientated staple: peanut. In: Altas Agriculture and Rural Developpment in Central African Savannas, CIRAD/PRASAD, 63-64pp.\u003c/p\u003e\n\u003cp\u003eMahatma, M. K., Thawait, V., Bishi, V., Khatediya, S. K., Rathnakumar, A. L., Lalwani, H.B., Misra, J. B., 2016. Nutritional composition and antioxidant activity of Spanish and Virginia groundnuts (\u003cem\u003eArachis hypogaea \u003c/em\u003eL.): a comparative study. \u003cem\u003eJournal Food Science Technology, \u003c/em\u003e53(5) : 2279-2286. https://doi.org/10.1007/s13197-016-2187-y.\u003c/p\u003e\n\u003cp\u003eMeda, A., 2005. Therapeutic use of honey and honeynee larvae in central Burkina Faso. \u003cem\u003eJournal of Ethnopharmacomogy\u003c/em\u003e, 101(1-3), 1-5. https://doi.org/10.1016/j.jep.2005.04.017.\u003c/p\u003e\n\u003cp\u003eMothilal, A, Vindhiya, V.P, Manivannan, N. 2010. Genotype × environment for kernel yield in groundnut (\u003cem\u003eArachis hypogaea \u003c/em\u003eL.). \u003cem\u003eElectronic Journal of. Plant Breeding\u003c/em\u003e, 1(5): 1306-1308. https://doi.org/10.5555/20113019542.\u003c/p\u003e\n\u003cp\u003eMukuddem-Peterson, J., Oosthuizen, W., Jerling, J. C., 2005. A systematic review of the\u003cbr\u003eeffects of nutson blood lipid profiles in humans. \u003cem\u003eJournal of Nutrition, \u003c/em\u003e135 (9), 2082-2089. https://doi.org/10.1093/jn/135.9.2082.\u003c/p\u003e\n\u003cp\u003eMpongwana, S., Manyevere, A., Mupangwa, J., Mpendulo, C. T., Mashamaite, C. V., 2023. Foliar nutrient content responses to bio-inoculation of arbuscular mycorrhizal fungi and Rhizobium on three herbaceous forage legumes. \u003cem\u003eFront. Sustain. Food Syst. \u003c/em\u003e7:1256717. https://doi.org/10.3389/fsufs.2023.1256717. \u003c/p\u003e\n\u003cp\u003eNassourou, M. A., Noubissié, T. J-B., Gonne, S., Hamadama, Y., Bell, J.M., Njintang, Y.N., 2015. Diallel analysis of polyphenols and phytates content in cowpea (\u003cem\u003eVigna unguiculata \u003c/em\u003eL. Walp.). \u003cem\u003eScientia Agriculturae\u003c/em\u003e, 12(1): 46-51. https://doi.org/10.15192/PSCP.SA.2015.12.1.4651.\u003c/p\u003e\n\u003cp\u003eNtoukam G., Endonto C., Ousman T., Kontcheu Mc., Hamasselbe A., Njomoha C., Ndikawe R. \u0026amp; Abba A., 1996. Productions des légumineuses à graines : acquis de la recherche. \u003cem\u003eIn : \u003c/em\u003eAgricultures des savanes du Nord Cameroun vers un développement solidaire des savanes d’Afrique centrale, pp : 215-223.\u003c/p\u003e\n\u003cp\u003eNoubissié T.J.B., Njintang N.Y. \u0026amp; Dolinassou S., 2012. Heritability studies of protein and oil contents in groundnut (\u003cem\u003eArachis hypogaea \u003c/em\u003eL.) genotypes. \u003cem\u003eInternational Journal of Innovations in Bio Sciences, \u003c/em\u003e2 (3): 162-171. \u003c/p\u003e\n\u003cp\u003eNunes L. L., Cavalcanti R. S. \u0026amp; Péricles A. M. F., 2011. Correlation and path analysis of peanut traits associated with the peg. \u003cem\u003eCrop Breeding and Applied Biotechnology\u003c/em\u003e, 11: 88-93. https://doi.org/10.1590/S1984-70332011000100013.\u003c/p\u003e\n\u003cp\u003ePalanisamy B.D., Radjendran V., Sathyaseelan S., Nagappa G.M., Venkatesan B.P. 2014. Health benefits of finger millet (\u003cem\u003eEleusine coracana \u003c/em\u003eL.) polyphenols and dietary fiber. \u003cem\u003eJournal of Food Science and Technology \u003c/em\u003e51 (6) 1021-1040. https://doi.org/10.1007/s13197-011-0590-7.\u003c/p\u003e\n\u003cp\u003eParmar D.L., Rathna Kumar A.L. \u0026amp; Bharodia P.S., 2000. Genetic and interrelationship of oil and protein contents in cross involving confectionery genotypes of groundnut. \u003cem\u003eInternational Arachis Newsletter, \u003c/em\u003e20: 17-18.\u003c/p\u003e\n\u003cp\u003ePerem A.L.L., 2012. Evaluation of various inoculation methods of arbuscular mychorrhizal fungi and the effect of inoculum sieving on peanut performance (\u003cem\u003eArachis hypogaea \u003c/em\u003eL.) DIPES II. University of Yaoundé I. 51pp.\u003c/p\u003e\n\u003cp\u003ePinstrup-Andersen, P., Pandya-Lorch, R. \u0026amp; Rosegrant, M.W. 1999. \u003cem\u003eWorld food prospects: critical issues for the twenty-first century\u003c/em\u003e. IFPRI, Washington.\u003c/p\u003e\n\u003cp\u003eRice-Evans C.A, Miller N.J, Paganga G., 1996. Structure antioxidant activity relationships of flavonoids and phenolic acids. \u003cem\u003eFre Radic Biol Med\u003c/em\u003e. 20(7) : 933-956. https://doi.org/10.1016/0891-5849(95)02227-9.\u003c/p\u003e\n\u003cp\u003eSchilling R., 1992. Peanut. Courrier de la planète. Agriculture, Environnement, Alimentation, trois défis pour un monde solidaire, Paris, France, 35p. \u003c/p\u003e\n\u003cp\u003eSwathi, Y., Rajanikanth, P., Satya N., Uppala N.M., Guntha, A., Vemula, A., Hari K.S., 2023. Effect of sub-optimal moisture levels on the quality of groundnut (\u003cem\u003eArachis hypogaea\u003c/em\u003e L.) during storage in triple-layer hermetic storage bags. \u003cem\u003eFrontiers in Sustainable Food Systems\u003c/em\u003e. 7:1275133\u003cem\u003e. \u003c/em\u003ehttps://doi.org/10.3389/fsufs.2023.1275133.\u003c/p\u003e\n\u003cp\u003eTalcott, S.T., Duncan, E.C., Del Pozoinsfran, D., Gorbet D.W., 2005. Polyphenolic and antioxidant changes during storage of normal, mid and high oleic acid peanuts. \u003cem\u003eFood Chemistry\u003c/em\u003e, 89: 77-84. https://doi.org/10.1016/j.foodchem.2004.02.020.\u003c/p\u003e\n\u003cp\u003eTavares L., Fortalezas S., Carrilho C., Mc Dougall G.J., Stewart D., Ferreira R.B., \u0026amp; Santos C.N., 2010. Antioxidant and antiproliferative properties of strawberry tree tissues. \u003cem\u003eJournal of Berry Research\u003c/em\u003e, 1(1): 3-12. https://doi.org/10.3233/BR-2010-001.\u003c/p\u003e\n\u003cp\u003eTouroumgaye, G., Mariama, D.D., Guiguindibaye, M., Ali, M.Z., Aliou, G., 2017. Determination of optimal sowing density on peanut (\u003cem\u003eArachis hypogaea\u003c/em\u003e L.) productivity in the Sudanian zone of Chad. \u003cem\u003eEuropean Scientific Journal,\u003c/em\u003e 13(9) : 316-324.\u003c/p\u003e\n\u003cp\u003eVeerendrakumar, H. V., Sudini, H. K., Kiranmayee, B., Devika, T., Gangurde, S. S., Vasanthi, R. P., Nirmal K. A. R., Bera, S. K., Guo, B., Liao, B., Varsheney, R. K., Pandey, M. K., 2025. Dissecting the genomic regions, candidate genes and pathways using multi-locus genome-wide association study for stem rot disease resistance in groundnut. \u003cem\u003eThe Plant Genome, \u003c/em\u003e18(3): 70089. https://doi.org/10.1002/tpg2.70089.\u003c/p\u003e\n\u003cp\u003eWang, X., Qi, F., Sun, Z., Liu, H., Wu, Y., Wu, X., Xu, J., H., Qin, L., Wang, Z., Sang, S., Dong, W., Huang, B., Zheng, Z., Zhang, X., 2024. Transcriptome sequencing and expression analysis in peanut reveal the potential mechanism response to \u003cem\u003eRalstonia solanacearum \u003c/em\u003einfection. \u003cem\u003eBMC Plant Biology, \u003c/em\u003e24, 207. https://doi.org/10.1186/s12870-024-04877-0.\u003c/p\u003e\n\u003cp\u003eWang, K., Shi, L., Zheng, B., He, He, Y., 2023. Response of wheat kernel to diverse allelic combinations under projected climate change condition. \u003cem\u003eFrontiers in Plant Science, \u003c/em\u003e14: 1138966. https://doi.org/103389/fpls.2023.1138966.\u003c/p\u003e\n\u003cp\u003eMar, Mar, W., Azizah, A-H., Bablishah, S.B., Farooq, A., Mandumpal, C. S., Mohd, P-D., 2011. Phenolic compounds and antioxidant activity of peanut’s skin, hull, raw kernel and roasted flour. \u003cem\u003ePakistan Journal of Botany, \u003c/em\u003e43(3): 1635-1642. https://www.pakbs.org/pjbot/PDFs/43(3)/PJB43(3)1635.\u003c/p\u003e\n\u003cp\u003eZhihui, W., Yue, Z., Liying, Y., Yuning, C., Yanping, K., Dongxin, H., Xin, W., Kede, L., Huifang, J., Yong, L., Boshou, L., 2023. Correlation and variability analysis of yield and quality related traits in different peanut varieties across various ecological zones of China. \u003cem\u003eOil Crop Science.\u003c/em\u003e 8: 236-242. https://doi.org/10.1016/j.ocsci.2023.12.001.\u003c/p\u003e\n\u003cp\u003eZhao X., Nishimura Y., Fukumoto Y. \u0026amp; Li J., 2011. Effect of high temperature on active oxygen species, senescence and photosynthetic properties in cucumber leaves. \u003cem\u003eEnvironmental and Experimental Botany\u003c/em\u003e.70: 212-216. https://doi.org/10.1016/j.envexpbot.2010.09.005.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"indian-journal-of-genetics-and-plant-breeding","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Indian Journal of Genetics and Plant Breeding](https://link.springer.com/journal/44489)","snPcode":"44489","submissionUrl":"https://submission.springernature.com/new-submission/44489/3","title":"Indian Journal of Genetics and Plant Breeding","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Groundnut, biochemical traits, antioxidant activity, varietal evaluation, Northern Cameroon","lastPublishedDoi":"10.21203/rs.3.rs-8159782/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8159782/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eGroundnuts (\u003cem\u003eArachis hypogaea\u003c/em\u003e L.) is a major oilseed and legume in semi-arid regions, yet limited information exists on the agronomic and biochemical performance of recently introduced varieties under the environmental conditions of Northern Cameroon. This study evaluated fifteen exotic groundnut genotypes across three agro-ecological sites (Gazawa, Bockl\u0026eacute; and Dang) to assess variability in yield components, oil and protein content, total polyphenols and antioxidant activity. Significant differences were observed among varieties for all traits studied. Pod weight was strongly correlated with overall yield (0.97), indicating that seed mass is a key determinant of productivity. Lipid and protein contents showed a strong negative correlation (r\u0026thinsp;=\u0026thinsp;0.90), suggesting trade-offs in metabolic partitioning between oil and protein biosynthesis. Total polyphenol content was positively associated with antioxidant activity (r\u0026thinsp;=\u0026thinsp;0.91), highlighting the nutraceutical potential of some varieties. Based on multivariate clustering, genotypes were grouped into high protein, high polyphenol and high lipid types, indicating opportunities for targeted selection depending on end use. These findings provide a valuable baseline for varietal improvement programs aimed at enhancing yield, nutritional quality and environmental adaptation of groundnut in the semi-arid zone.\u003c/p\u003e","manuscriptTitle":"Agronomic and biochemical evaluation of fifteen exotic groundnut parameters (Arachis hypogaea L.) varieties grown in Northern Cameroon","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-12 10:07:16","doi":"10.21203/rs.3.rs-8159782/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-01-03T18:21:30+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-17T00:19:07+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"153933257517747541949218635112647824085","date":"2025-12-10T04:31:11+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-12-09T09:44:12+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-11-27T12:30:00+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-11-27T12:29:44+00:00","index":"","fulltext":""},{"type":"submitted","content":"Indian Journal of Genetics and Plant Breeding","date":"2025-11-20T03:01:59+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"indian-journal-of-genetics-and-plant-breeding","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Indian Journal of Genetics and Plant Breeding](https://link.springer.com/journal/44489)","snPcode":"44489","submissionUrl":"https://submission.springernature.com/new-submission/44489/3","title":"Indian Journal of Genetics and Plant Breeding","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"cc0f7b5a-4da6-4830-8859-0ad73501edfc","owner":[],"postedDate":"December 12th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-01-25T19:11:01+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-12 10:07:16","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8159782","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8159782","identity":"rs-8159782","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}