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Efficacy of bio-fertilizers and chemical fertilizers on growth and yield of cowpea varieties

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  • Cowpea is valued for its nutrition and nitrogen-fixing ability, and investigating bio-fertilizers offers a sustainable way to enhance cowpea growth and yield. A field experiment was conducted from February to June 2022 in the Nawalparasi West, Nepal, to investigate the impact of different fertilizers, including bio-fertilizers and chemical fertilizers, on the growth parameters and yield of cowpea varieties. Employing a double factorial Randomized Complete Block Design (RCBD), the experiment considered two factors: cowpea varieties (Malepatan-1 and Stickless) and fertilizers (control, mycorrhizal, rhizobia, recommended dose of chemical fertilizer (RDF), mycorrhizal + rhizobia, and mycorrhiza + rhizobium + RDF). Malepatan-1 exhibited superior growth and yield compared to Stickless, with higher plant height (125.73 cm), seed weight plant−1 (72.29 g), thousand grain weight (151.62 g), and yield ha−1 (3,536.83 kg ha−1). While the application of rhizobia + mycorrhiza and chemical fertilizers increased various growth parameters, mycorrhiza + rhizobium showed comparable results in terms of yield (4,321.41 kg ha−1) and thousand grain weight (167.19 g) compared to the combination of the former (4,714.26 kg ha−1 and 176.83 g, respectively). Moreover, mycorrhiza + rhizobium demonstrated a higher benefit-cost ratio (3.76), making it economically and environmentally preferable to biofertilizers with chemicals. The study recommends mycorrhiza + rhizobium for its comparable yield, superior economic returns, and environmental sustainability over biofertilizers combined with chemicals. For maximizing economic and sustainable production, the study suggests using the Malepatan-1 cowpea variety with biofertilizers, excluding chemical (inorganic) fertilizers.
  • Starting in the early 2000s, China has experienced rapid growth as an emerging wine market. It has now established itself as the world's second-largest grape-growing country in terms of vineyard surface area. Furthermore, China has also secured its position as the sixth-biggest wine producer globally and the fifth-most significant wine consumer in terms of volume[1]. The Ningxia Hui autonomous region, known for its reputation as the highest quality wine-producing area in China, is considered one of the country's most promising wine regions. The region's arid or semiarid climate, combined with ample sunlight and warmth, thanks to the Yellow River, provides ideal conditions for grape cultivation. Wineries in the Ningxia Hui autonomous region are renowned as the foremost representatives of elite Chinese wineries. All wines produced in this region originate from grapes grown in their vineyards, adhering to strict quality requirements, and have gained a well-deserved international reputation for excellence. Notably, in 2011, Helan Mountain's East Foothill in the Ningxia Hui Autonomous Region received protected geographic indication status in China. Subsequently, in 2012, it became the first provincial wine region in China to be accepted as an official observer by the International Organisation of Vine and Wine (OIV)[2]. The wine produced in the Helan Mountain East Region of Ningxia, China, is one of the first Agricultural and Food Geographical Indications. Starting in 2020, this wine will be protected in the European Union[3].

    Marselan, a hybrid variety of Cabernet Sauvignon and Grenache was introduced to China in 2001 by the French National Institute for Agricultural Research (INRA). Over the last 15 years, Marselan has spread widely across China, in contrast to its lesser cultivation in France. The wines produced from Marselan grapes possess a strong and elegant structure, making them highly suitable for the preferences of Chinese consumers. As a result, many wineries in the Ningxia Hui Autonomous Region have made Marselan wines their main product[4]. Wine is a complex beverage that is influenced by various natural and anthropogenic factors throughout the wine-making process. These factors include soil, climate, agrochemicals, and human intervention. While there is an abundance of research available on wine production, limited research has been conducted specifically on local wines in the Eastern Foot of Helan Mountain. This research gap is of significant importance for the management and quality improvement of Chinese local wines.

    Ion mobility spectrometry (IMS) is a rapid analytical technique used to detect trace gases and characterize chemical ionic substances. It achieves this through the gas-phase separation of ionized molecules under an electric field at ambient pressure. In recent years, IMS has gained increasing popularity in the field of food-omics due to its numerous advantages. These advantages include ultra-high analytical speed, simplicity, easy operation, time efficiency, relatively low cost, and the absence of sample preparation steps. As a result, IMS is now being applied more frequently in various areas of food analysis, such as food composition and nutrition, food authentication, detection of food adulteration, food process control, and chemical food safety[5,6]. The orthogonal hyphenation of gas chromatography (GC) and IMS has greatly improved the resolution of complex food matrices when using GC-IMS, particularly in the analysis of wines[7].

    The objective of this study was to investigate the changes in the physicochemical properties of Marselan wine during the winemaking process, with a focus on the total phenolic and flavonoids content, antioxidant activity, and volatile profile using the GC-IMS method. The findings of this research are anticipated to make a valuable contribution to the theoretical framework for evaluating the authenticity and characterizing Ningxia Marselan wine. Moreover, it is expected that these results will aid in the formulation of regulations and legislation pertaining to Ningxia Marselan wine in China.

    All the grapes used to produce Marselan wines, grow in the Xiban vineyard (106.31463° E and 38.509541° N) situated in Helan Mountain's East Foothill of Ningxia Hui Autonomous Region in China.

    Folin-Ciocalteau reagent, (±)-6-Hydroxy-2,5,7,8-tetramethylchroman-2-carboxylic acid (Trolox), 2,20-azino-bis-(3-ethylbenzthiazoline-6-sulfonic acid) (ABTS), 2,4,6-tris (2-pyridyl)-s-triazine (TPTZ), anhydrous methanol, sodium nitrite, and sodium carbonate anhydrous were purchased from Shanghai Aladdin Biochemical Technology Co., Ltd. (Shanghai, China). Reference standards of (+)-catechin, gallic acid, and the internal standard (IS) 4-methyl-2-pentanol were supplied by Shanghai Yuanye Bio-Technology Co., Ltd (Shanghai, China). The purity of the above references was higher than 98%. Ultrapure water (18.2 MΩ cm) was prepared by a Milli-Q system (Millipore, Bedford, MA, USA).

    Stage 1−Juice processing: Grapes at the fully mature stage are harvested and crushed, and potassium metabisulfite (5 mg/L of SO2) was evenly spread during the crushing process. The obtained must is transferred into stainless steel tanks. Stage 2−Alcoholic fermentation: Propagated Saccharomyces cerevisiae ES488 (Enartis, Italy) are added to the fresh must, and alcoholic fermentation takes place, after the process is finished, it is kept in the tanks for 7 d for traditional maceration to improve color properties and phenolics content. Stage 3−Malolactic fermentation: When the pomace is fully concentrated at the bottom of the tanks, the wine is transferred to another tank for separation from these residues. Oenococcus oeni VP41 (Lallemand Inc., France) is inoculated and malic acid begins to convert into lactic acid. Stage 4−Wine stabilization: After malolactic fermentation, potassium metabisulfite is re-added (35 mg/L of SO2), and then transferred to oak barrels for stabilization, this process usually takes 6-24 months. A total of four batches of samples during the production process of Marselan wine were collected in this study.

    Total polyphenols were determined on 0.5 mL diluted wine sample using the Folin-Ciocalteu method[8], using gallic acid as a reference compound, and expressed as milligrams of gallic acid equivalents per liter of wine. The total flavonoid content was measured on 0.05 mL of wine sample by a colorimetric method previously described[9]. Results are calculated from the calibration curve obtained with catechin, as milligrams of catechin equivalents per liter of wine.

    The antioxidative activity was determined using the ABTS·+ assay[10]. Briefly, the ABTS·+ radical was prepared from a mixture of 88 μL of potassium persulfate (140 mmol/L) with 5 mL of the ABTS·+ solution (7 mmol/L). The reaction was kept at room temperature under the absence of light for 16 h. Sixty μL samples were mixed with 3 mL of ABTS·+ solution with measured absorption of 0.700 ± 0.200 at 734 nm. After 6 min reaction, the absorbance of samples were measured with a spectrophotometer at 734 nm. Each sample was tested in triplicate. The data were expressed as mmol Trolox equivalent of antioxidative capacity per liter of the wine sample (mmol TE/L). Calibration curves, in the range 64.16−1,020.20 μmol TE/L, showed good linearity (R2 ≥ 0.99).

    The FRAP assay was conducted according to a previous study[11]. The FRAP reagent was freshly prepared and mixed with 10 mM/L TPTZ solution prepared in 20 mM/L FeCl3·6H2O solution, 40 mM/L HCl, and 300 mM/L acetate buffer (pH 3.6) (1:1:10; v:v:v). Ten ml of diluted sample was mixed with 1.8 ml of FRAP reagent and incubated at 37 °C for 30 min. The absorbance was determined at 593 nm and the results were reported as mM Fe (II) equivalent per liter of the wine sample. The samples were analyzed and calculated by a calibration curve of ferrous sulphate (0.15−2.00 mM/mL) for quantification.

    The volatile compounds were analyzed on a GC-IMS instrument (FlavourSpec, GAS, Dortmund, Germany) equipped with an autosampler (Hanon Auto SPE 100, Shandong, China) for headspace analysis. One mL of each wine was sampled in 20 mL headspace vials (CNW Technologies, Germany) with 20 μL of 4-methyl-2-pentanol (20 mg/L) ppm as internal standard, incubated at 60 °C and continuously shaken at 500 rpm for 10 min. One hundred μL of headspace sample was automatically loaded into the injector in splitless mode through a syringe heated to 65 °C. The analytes were separated on a MxtWAX capillary column (30 m × 0.53 mm, 1.0 μm) from Restek (Bellefonte, Pennsylvania, USA) at a constant temperature of 60 °C and then ionized in the IMS instrument (FlavourSpec®, Gesellschaft für Analytische Sensorsysteme mbH, Dortmund, Germany) at 45 °C. High purity nitrogen gas (99.999%) was used as the carrier gas at 150 mL/min, and drift gas at 2 ml/min for 0−2.0 min, then increased to 100 mL/min from 2.0 to 20 min, and kept at 100 mL/min for 10 min. Ketones C4−C9 (Sigma Aldrich, St. Louis, MO, USA) were used as an external standard to determine the retention index (RI) of volatile compounds. Analyte identification was performed using a Laboratory Analytical Viewer (LAV) 2.2.1 (GAS, Dortmund, Germany) by comparing RI and the drift time of the standard in the GC-IMS Library.

    All samples were prepared in duplicate and tested at least six times, and the results were expressed as mean ± standard error (n = 4) and the level of statistical significance (p < 0.05) was analyzed by using Tukey's range test using SPSS 18.0 software (SPSS Inc., IL, USA). The principal component analysis (PCA) was performed using the LAV software in-built 'Dynamic PCA' plug-in to model patterns of aroma volatiles. Orthogonal partial least-square discriminant analysis (OPLS-DA) in SIMCA-P 14.1 software (Umetrics, Umeă, Sweden) was used to analyze the different volatile organic compounds in the different fermentation stages.

    The results of the changes in the antioxidant activity of Marselan wines during the entire brewing process are listed in Table 1. It can be seen that the contents of flavonoids and polyphenols showed an increasing trend during the brewing process of Marselan wine, which range from 315.71−1,498 mg CE/L and 1,083.93−3,370.92 mg GAE/L, respectively. It was observed that the content increased rapidly in the alcoholic fermentation stage, but slowly in the subsequent fermentation stage. This indicated that the formation of flavonoid and phenolic substances in wine mainly concentrated in the alcoholic fermentation stage, which is consistent with previous reports. This is mainly because during the alcoholic fermentation of grapes, impregnation occurred to extract these compounds[12]. The antioxidant activities of Marselan wine samples at different fermentation stages were detected by FRAP and ABTS methods[11]. The results showed that the ferric reduction capacity and ABST·+ free radical scavenging capacity of the fermented Marselan wines were 2.4 and 1.5 times higher than the sample from the juice processing stage, respectively, indicating that the fermented Marselan wine had higher antioxidant activity. A large number of previous studies have suggested that there is a close correlation between antioxidant activity and the content of polyphenols and flavonoids[1315]. Previous studies have reported that Marselan wine has the highest total phenol and anthocyanin content compared to the wine of Tannat, Cabernet Sauvignon, Merlot, Cabernet Franc, and Syrah[13]. Polyphenols and flavonoids play an important role in improving human immunity. Therefore, Marselan wines are popular because of their high phenolic and flavonoid content and high antioxidant capacity.

    Table 1.  GC-IMS integration parameters of volatile compounds in Marselan wine at different fermentation stages.
    No. Compounds Formula RI* Rt
    [sec]**
    Dt
    [RIPrel]***
    Identification
    approach
    Concentration (μg/mL) (n = 4)
    Stage 1 Stage 2 Stage 3 Stage 4
    Aldehydes
    5 Furfural C5H4O2 1513.1 941.943 1.08702 RI, DT, IS 89.10 ± 4.05c 69.98 ± 3.22c 352.16 ± 39.06b 706.30 ± 58.22a
    6 Furfural dimer C5H4O2 1516.6 948.77 1.33299 RI, DT, IS 22.08 ± 0.69b 18.68 ± 2.59c 23.73 ± 2.69b 53.39 ± 9.42a
    12 (E)-2-hexenal C6H10O 1223.1 426.758 1.18076 RI, DT, IS 158.17 ± 7.26a 47.57 ± 2.51b 39.00 ± 2.06c 43.52 ± 4.63bc
    17 (E)-2-pentenal C5H8O 1129.2 333.392 1.1074 RI, DT, IS 23.00 ± 4.56a 16.42 ± 1.69c 18.82 ± 0.27b 18.81 ± 0.55b
    19 Heptanal C7H14O 1194.2 390.299 1.33002 RI, DT, IS 17.28 ± 2.25a 10.22 ± 0.59c 14.50 ± 8.84b 9.11 ± 1.06c
    22 Hexanal C6H12O 1094.6 304.324 1.25538 RI, DT, IS 803.11 ± 7.47c 1631.34 ± 19.63a 1511.11 ± 26.91b 1526.53 ± 8.12b
    23 Hexanal dimer C6H12O 1093.9 303.915 1.56442 RI, DT, IS 588.85 ± 7.96a 93.75 ± 4.67b 92.93 ± 3.13b 95.49 ± 2.50b
    29 3-Methylbutanal C5H10O 914.1 226.776 1.40351 RI, DT, IS 227.86 ± 6.39a 33.32 ± 2.59b 22.36 ± 1.18c 21.94 ± 1.73c
    33 Dimethyl sulfide C2H6S 797.1 193.431 0.95905 RI, DT, IS 120.07 ± 4.40c 87.a02 ± 3.82d 246.81 ± 5.62b 257.18 ± 3.04a
    49 2-Methylpropanal C4H8O 828.3 202.324 1.28294 RI, DT, IS 150.49 ± 7.13a 27.08 ± 1.48b 19.36 ± 1.10c 19.69 ± 0.92c
    Ketones
    45 3-Hydroxy-2-butanone C4H8O2 1293.5 515.501 1.20934 RI, DT, IS 33.20 ± 3.83c 97.93 ± 8.72b 163.20 ± 21.62a 143.51 ± 21.48a
    46 Acetone C3H6O 836.4 204.638 1.11191 RI, DT, IS 185.75 ± 8.16c 320.43 ± 12.32b 430.74 ± 3.98a 446.58 ± 10.41a
    Organic acid
    3 Acetic acid C2H4O2 1527.2 969.252 1.05013 RI, DT, IS 674.66 ± 46.30d 3602.39 ± 30.87c 4536.02 ± 138.86a 4092.30 ± 40.33b
    4 Acetic acid dimer C2H4O2 1527.2 969.252 1.15554 RI, DT, IS 45.25 ± 3.89c 312.16 ± 19.39b 625.79 ± 78.12a 538.35 ± 56.38a
    Alcohols
    8 1-Hexanol C6H14O 1365.1 653.825 1.32772 RI, DT, IS 1647.65 ± 28.94a 886.33 ± 32.96b 740.73 ± 44.25c 730.80 ± 21.58c
    9 1-Hexanol dimer C6H14O 1365.8 655.191 1.64044 RI, DT, IS 378.42 ± 20.44a 332.65 ± 25.76a 215.78 ± 21.04b 200.14 ± 28.34b
    13 3-Methyl-1-butanol C5H12O 1213.3 414.364 1.24294 RI, DT, IS 691.86 ± 9.95c 870.41 ± 22.63b 912.80 ± 23.94a 939.49 ± 12.44a
    14 3-Methyl-1-butanol dimer C5H12O 1213.3 414.364 1.49166 RI, DT, IS 439.90 ± 29.40c 8572.27 ± 60.56b 9083.14 ± 193.19a 9152.25 ± 137.80a
    15 1-Butanol C4H10O 1147.2 348.949 1.18073 RI, DT, IS 157.33 ± 9.44b 198.92 ± 3.92a 152.78 ± 10.85b 156.02 ± 9.80b
    16 1-Butanol dimer C4H10O 1146.8 348.54 1.38109 RI, DT, IS 24.14 ± 2.15c 274.75 ± 12.60a 183.02 ± 17.72b 176.80 ± 19.80b
    24 1-Propanol C3H8O 1040.9 274.803 1.11042 RI, DT, IS 173.73 ± 4.75a 55.84 ± 2.16c 80.80 ± 4.99b 83.57 ± 2.34b
    25 1-Propanol dimer C3H8O 1040.4 274.554 1.24784 RI, DT, IS 58.20 ± 1.30b 541.37 ± 11.94a 541.33 ± 15.57a 538.84 ± 9.74a
    28 Ethanol C2H6O 930.6 231.504 1.11901 RI, DT, IS 5337.84 ± 84.16c 11324.05 ± 66.18a 9910.20 ± 100.76b 9936.10 ± 101.24b
    34 Methanol CH4O 903.6 223.79 0.98374 RI, DT, IS 662.08 ± 13.87a 76.94 ± 2.15b 61.92 ± 1.96c 62.89 ± 0.81c
    37 2-Methyl-1-propanol C4H10O 1098.5 306.889 1.35839 RI, DT, IS 306.91 ± 4.09c 3478.35 ± 25.95a 3308.79 ± 61.75b 3313.85 ± 60.88b
    48 1-Pentanol C5H12O 1257.6 470.317 1.25222 RI, DT, IS 26.13 ± 2.52c 116.50 ± 3.71ab 112.37 ± 6.26b 124.17 ± 7.04a
    Esters
    1 Methyl salicylate C8H8O3 1859.6 1616.201 1.20489 RI, DT, IS 615.00 ± 66.68a 485.08 ± 31.30b 470.14 ± 23.02b 429.12 ± 33.74b
    7 Butyl hexanoate C10H20O2 1403.0 727.561 1.47354 RI, DT, IS 95.83 ± 17.04a 62.87 ± 3.62a 92.59 ± 11.88b 82.13 ± 3.61c
    10 Hexyl acetate C8H16O2 1298.6 524.366 1.40405 RI, DT, IS 44.72 ± 8.21a 33.18 ± 2.17d 41.50 ± 4.38c 40.89 ± 4.33b
    11 Propyl hexanoate C9H18O2 1280.9 499.577 1.39274 RI, DT, IS 34.65 ± 3.90d 70.43 ± 5.95a 43.97 ± 4.39b 40.12 ± 4.05c
    18 Ethyl hexanoate C8H16O2 1237.4 444.749 1.80014 RI, DT, IS 55.55 ± 5.62c 1606.16 ± 25.63a 787.24 ± 16.95b 788.91 ± 28.50b
    20 Isoamyl acetate C7H14O2 1127.8 332.164 1.30514 RI, DT, IS 164.22 ± 1.00d 243.69 ± 8.37c 343.51 ± 13.98b 365.46 ± 1.60a
    21 Isoamyl acetate dimer C7H14O2 1126.8 331.345 1.75038 RI, DT, IS 53.61 ± 4.79d 4072.20 ± 11.94a 2416.70 ± 49.84b 2360.46 ± 43.29c
    26 Isobutyl acetate C6H12O2 1020.5 263.605 1.23281 RI, DT, IS 101.65 ± 1.81a 15.52 ± 0.67c 44.87 ± 3.21b 45.96 ± 1.41b
    27 Isobutyl acetate dimer C6H12O2 1019.6 263.107 1.61607 RI, DT, IS 34.60 ± 1.05d 540.84 ± 5.64a 265.54 ± 8.31c 287.06 ± 3.66b
    30 Ethyl acetate dimer C4H8O2 885.2 218.564 1.33587 RI, DT, IS 1020.75 ± 6.86d 5432.71 ± 6.55a 5052.99 ± 9.65b 5084.47 ± 7.30c
    31 Ethyl acetate C4H8O2 878.3 216.574 1.09754 RI, DT, IS 215.65 ± 3.58a 38.29 ± 2.37c 71.59 ± 2.99b 69.32 ± 2.85b
    32 Ethyl formate C3H6O2 838.1 205.127 1.19738 RI, DT, IS 175.48 ± 3.79d 1603.20 ± 13.72a 1472.10 ± 5.95c 1509.08 ± 13.26b
    35 Ethyl octanoate C10H20O2 1467.0 852.127 1.47312 RI, DT, IS 198.86 ± 36.71b 1853.06 ± 17.60a 1555.51 ± 24.21a 1478.05 ± 33.63a
    36 Ethyl octanoate dimer C10H20O2 1467.0 852.127 2.03169 RI, DT, IS 135.50 ± 13.02d 503.63 ± 15.86a 342.89 ± 11.62b 297.28 ± 14.40c
    38 Ethyl butanoate C6H12O2 1042.1 275.479 1.5664 RI, DT, IS 21.29 ± 2.68c 1384.67 ± 8.97a 1236.52 ± 20.21b 1228.09 ± 5.09b
    39 Ethyl 3-methylbutanoate C7H14O2 1066.3 288.754 1.26081 RI, DT, IS 9.70 ± 1.85d 200.29 ± 4.21a 146.87 ± 8.70b 127.13 ± 12.54c
    40 Propyl acetate C5H10O2 984.7 246.908 1.48651 RI, DT, IS 4.57 ± 1.07c 128.63 ± 4.28a 87.75 ± 3.26b 88.49 ± 1.99b
    41 Ethyl propanoate C5H10O2 962.1 240.47 1.46051 RI, DT, IS 10.11 ± 0.34d 107.08 ± 3.50a 149.60 ± 5.39c 167.15 ± 12.90b
    42 Ethyl isobutyrate C6H12O2 971.7 243.229 1.56687 RI, DT, IS 18.29 ± 2.61d 55.22 ± 1.07c 98.81 ± 4.67b 104.71 ± 4.73a
    43 Ethyl lactate C5H10O3 1352.2 628.782 1.14736 RI, DT, IS 31.81 ± 2.91c 158.03 ± 2.80b 548.14 ± 74.21a 527.01 ± 39.06a
    44 Ethyl lactate dimer C5H10O3 1351.9 628.056 1.53618 RI, DT, IS 44.55 ± 2.03c 47.56 ± 4.02c 412.23 ± 50.96a 185.87 ± 31.25b
    47 Ethyl heptanoate C9H18O2 1339.7 604.482 1.40822 RI, DT, IS 39.55 ± 6.37a 38.52 ± 2.47a 28.44 ± 1.52c 30.77 ± 2.79b
    Unknown
    1 RI, DT, IS 15.53 ± 0.18 35.69 ± 0.80 12.70 ± 0.80 10.57 ± 0.86
    2 RI, DT, IS 36.71 ± 1.51 120.41 ± 3.44 198.12 ± 6.01 201.19 ± 3.70
    3 RI, DT, IS 44.35 ± 0.88 514.12 ± 4.28 224.78 ± 6.56 228.32 ± 4.62
    4 RI, DT, IS 857.64 ± 8.63 33.22 ± 1.99 35.05 ± 5.99 35.17 ± 3.97
    * Represents the retention index calculated using n-ketones C4−C9 as external standard on MAX-WAX column. ** Represents the retention time in the capillary GC column. *** Represents the migration time in the drift tube.
     | Show Table
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    This study adopted the GC-IMS method to test the volatile organic compounds (VOCs) in the samples from the different fermentation stages of Marselan wine. Figure 1 shows the gas phase ion migration spectrum obtained, in which the ordinate represents the retention time of the gas chromatographic peaks and the abscissa represents the ion migration time (normalized)[16]. The entire spectrum represents the aroma fingerprints of Marselan wine at different fermentation stages, with each signal point on the right of the relative reactant ion peak (RIP) representing a volatile organic compound detected from the sample[17]. Here, the sample in stage 1 (juice processing) was used as a reference and the characteristic peaks in the spectrum of samples in other fermentation stages were compared and analyzed after deducting the reference. The colors of the same component with the same concentration cancel each other to form a white background. In the topographic map of other fermentation stages, darker indicates higher concentration compared to the white background. In the 2D spectra of different fermentation stages, the position and number of peaks indicated that peak intensities are basically the same, and there is no obvious difference. However, it is known that fermentation is an extremely complex chemical process, and the content and types of volatile organic compounds change with the extension of fermentation time, so other detection and characterization methods are needed to make the distinction.

    Figure 1.  2D-topographic plots of volatile organic compounds in Marselan wine at different fermentation stages.

    To visually display the dynamic changes of various substances in the fermentation process of Marselan wine, peaks with obvious differences were extracted to form the characteristic fingerprints for comparison (Fig. 2). Each row represents all signal peaks selected from samples at the same stage, and each column means the signal peaks of the same volatile compound in samples from different fermentation stages. Figure 2 shows the volatile organic compounds (VOCs) information for each sample and the differences between samples, where the numbers represent the undetermined substances in the migration spectrum library. The changes of volatile substances in the process of Marselan winemaking is observed by the fingerprint. As shown in Fig. 2 and Table 2, a total of 40 volatile chemical components were detected by qualitative analysis according to their retention time and ion migration time in the HS-GC-IMS spectrum, including 17 esters, eight alcohols, eight aldehydes, two ketones, one organic acid, and four unanalyzed flavor substances. The 12 volatile organic compounds presented dimer due to ionization of the protonated neutral components before entering the drift tube[18]. As can be seen from Table 2, the VOCs in the winemaking process of Marselan wine are mainly composed of esters, alcohols, and aldehydes, which play an important role in the construction of aroma characteristics.

    Figure 2.  Fingerprints of volatile organic compounds in Marselan wine at different fermentation stages.
    Table 2.  Antioxidant activity, total polyphenols, and flavonoids content of Marselan wine at different fermentation stages.
    Winemaking stage TFC (mg CE/L) TPC (mg GAE/L) FRAP (mM FeSO4/mL) ABTs (mM Trolox/L)
    Stage 1 315.71 ± 0.00d 1,083.93 ± 7.79d 34.82c 38.92 ± 2.12c
    Stage 2 1,490.00 ± 7.51c 3,225.51 ± 53.27c 77.32b 52.17 ± 0.95b
    Stage 3 1,510.00 ± 8.88a 3,307.143 ± 41.76b 77.56b 53.04 ± 0.76b
    Stage 4 1,498.57 ± 6.34b 3,370.92 ± 38.29a 85.07a 57.46 ± 2.55a
    Means in the same column with different letters are significantly different (p < 0.05).
     | Show Table
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    Esters are produced by the reaction of acids and alcohols in wine, mainly due to the activity of yeast during fermentation[19], and are the main components of fruit juices and wines that produce fruit flavors[20,21]. In this study, it was found that they were the largest detected volatile compound group in Marselan wine samples, which is consistent with previous reports[22]. It can be observed from Table 2 that the contents of most esters increased gradually with the extension of fermentation time, and they mainly began to accumulate in large quantities during the stage of alcohol fermentation. The contents of ethyl hexanoate (fruity), isoamyl acetate (banana, pear), ethyl octanoate (fruity, pineapple, apple, brandy), ethyl acetate (fruity), ethyl formate (spicy, pineapple), and ethyl butanoate (sweet, pineapple, banana, apple) significantly increased at the stage of alcoholic fermentation and maintained a high level in the subsequent fermentation stage (accounting for 86% of the total detected esters). These esters can endow a typical fruity aroma of Marselan wine, and played a positive role in the aroma profiles of Marselan wine. Among them, the content of ethyl acetate is the highest, which is 5,153.79 μg/mL in the final fermentation stage, accounting for 33.6% of the total ester. However, the content of ethyl acetate was relatively high before fermentation, which may be from the metabolic activity of autochthonous microorganisms present in the raw materials. Isobutyl acetate, ethyl 3-methyl butanoate, propyl acetate, ethyl propanoate, ethyl isobutyrate, and ethyl lactate were identified and quantified in all fermentation samples. The total contents of these esters in stage 1 and 4 were 255.28 and 1,533.38 μg/mL, respectively, indicating that they may also have a potential effect on the aroma quality of Marselan wine. The results indicate that esters are an important factor in the formation of flavor during the brewing process of Marselan wine.

    Alcohols were the second important aromatic compound in Marselan wine, which were mainly synthesized by glucose and amino acid decomposition during alcoholic fermentation[23,24]. According to Table 2, eight alcohols including methanol, ethanol, propanol, butanol, hexanol, amyl alcohol, 3-methyl-1-butanol, and 2-methyl-1-propanol were detected in the four brewing stages of Marselan wine. The contents of ethanol (slightly sweet), 3-methyl-1-butanol (apple, brandy, spicy), and 2-methyl-1-propanol (whiskey) increased gradually during the fermentation process. The sum of these alcohols account for 91%−92% of the total alcohol content, which is the highest content of three alcohols in Marselan wine, and may be contributing to the aromatic and clean-tasting wines. On the contrary, the contents of 1-hexanol and methanol decreased gradually in the process of fermentation. Notably, the content of these rapidly decreased at the stage of alcoholic fermentation, from 2,026.07 to 1,218.98 μg/mL and 662.08 to 76.94 μg/mL, respectively, which may be ascribed to volatiles changed from alcohols to esters throughout fermentation. The reduction of the concentration of some alcohols also alleviates the strong odor during wine fermentation, which plays an important role in the improvement of aroma characteristics.

    Acids are mainly produced by yeast and lactic acid bacteria metabolism at the fermentation stage and are considered to be an important part of the aroma of wine[22]. Only one type of acid (acetic acid) was detected in this experiment, which was less than previously reported, which may be related to different brewing processes. Acetic acid content is an important factor in the balance of aroma and taste of wine. Low contents of volatile acids can provide a mild acidic smell in wine, which is widely considered to be ideal for producing high-quality wines. However, levels above 700 μg/mL can produce a pungent odor and weaken the wine's distinctive flavor[25]. The content of acetic acid increased first and then decreased during the whole fermentation process. The content of acetic acid increased rapidly in the second stage, from 719.91 to 3,914.55 μg/mL reached a peak in the third stage (5,161.81 μg/mL), and decreased to 4,630.65 μg/mL in the last stage of fermentation. Excessive acetic acid in Marselan wine may have a negative impact on its aroma quality.

    It was also found that the composition and content of aldehydes produced mainly through the catabolism of amino acids or decarboxylation of ketoacid were constantly changing during the fermentation of Marselan wines. Eight aldehydes, including furfural, hexanal, heptanal, 2-methylpropanal, 3-methylbutanal, dimethyl sulfide, (E)-2-hexenal, and (E)-2-pentenal were identified in all stage samples. Among them, furfural (caramel bread flavor) and hexanal (grass flavor) are the main aldehydes in Marselan wine, and the content increases slightly with the winemaking process. While other aldehydes such as (E)-2-hexenal (green and fruity), 3-methylbutanol (fresh and malt), and 2-methylpropanal (fresh and malt) were decomposed during brewing, reducing the total content from 536.52 to 85.15 μg/mL, which might potently affect the final flavor of the wine. Only two ketones, acetone, and 3-hydroxy-2-butanone, were detected in the wine samples, and their contents had no significant difference in the fermentation process, which might not affect the flavor of the wine.

    To more intuitively analyze the differences of volatile organic compounds in different brewing stages of Marselan wine samples, principal component analysis was performed[2628]. As presented in Fig. 3, the points corresponding to one sample group were clustered closely on the score plot, while samples at different fermentation stages were well separated in the plot. PC1 (79%) and PC2 (18%) together explain 97% of the total variance between Marselan wine samples, indicating significant changes in volatile compounds during the brewing process. As can be seen from the results in Fig. 3, samples of stages 1, 2, and 3 can be distinguished directly by PCA, suggesting that there are significant differences in aroma components in these three fermentation stages. Nevertheless, the separation of stage 3 and stage 4 samples is not very obvious and both presented in the same quadrant, which means that their volatile characteristics were highly similar, indicating that the volatile components of Marselan wine are formed in stage 3 during fermentation (Fig. S1). The above results prove that the unique aroma fingerprints of the samples from the distinct brewing stages of Marselan wine were successfully constructed using the HS-GC-IMS method.

    Figure 3.  PCA based on the signal intensity obtained with different fermentation stages of Marselan wine.

    Based on the results of the PCA, OPLS-DA was used to eliminate the influence of uncontrollable variables on the data through permutation test, and to quantify the differences between samples caused by characteristic flavors[28]. Figure 4 revealed that the point of flavor substances were colored according to their density and the samples obtained at different fermentation stages of wine have obvious regional characteristics and good spatial distribution. In addition, the reliability of the OPLS-DA model was verified by the permutation method of 'Y-scrambling'' validation. In this method, the values of the Y variable were randomly arranged 200 times to re-establish and analyze the OPLS-DA model. In general, the values of R2 (y) and Q2 were analyzed to assess the predictability and applicability of the model. The results of the reconstructed model illustrate that the slopes of R2 and Q2 regression lines were both greater than 0, and the intercept of the Q2 regression line was −0.535 which is less than 0 (Fig. 5). These results indicate that the OPLS-DA model is reliable and there is no fitting phenomenon, and this model can be used to distinguish the four brewing stages of Marselan wine.

    Figure 4.  Scores plot of OPLS-DA model of volatile components in Marselan wine at different fermentation stages.
    Figure 5.  Permutation test of OPLS-DA model of volatile components in Marselan wine at different fermentation stages (n = 200).

    VIP is the weight value of OPLS-DA model variables, which was used to measure the influence intensity and explanatory ability of accumulation difference of each component on classification and discrimination of each group of samples. In previous studies, VIP > 1 is usually used as a screening criterion for differential volatile substances[2830]. In this study, a total of 22 volatile substances had VIP values above 1, indicating that these volatiles could function as indicators of Marselan wine maturity during fermentation (see Fig. 6). These volatile compounds included furfural, ethyl lactate, heptanal, dimethyl sulfide, 1-propanol, ethyl isobutyrate, propyl acetate, isobutyl acetate, ethanol, ethyl hexanoate, acetic acid, methanol, ethyl formate, ethyl 3-methylbutanoate, ethyl acetate, hexanal, isoamyl acetate, 2-methylpropanal, 2-methyl-1-propanol, and three unknown compounds.

    Figure 6.  VIP plot of OPLS-DA model of volatile components in Marselan wine at different fermentation stages.

    This study focuses on the change of volatile flavor compounds and antioxidant activity in Marselan wine during different brewing stages. A total of 40 volatile aroma compounds were identified and collected at different stages of Marselan winemaking. The contents of volatile aroma substances varied greatly at different stages, among which alcohols and esters were the main odors in the fermentation stage. The proportion of furfural was small, but it has a big influence on the wine flavor, which can be used as one of the standards to measure wine flavor. Flavonoids and phenols were not only factors of flavor formation, but also important factors to improve the antioxidant capacity of Marselan wine. In this study, the aroma of Marselan wines in different fermentation stages was analyzed, and its unique aroma fingerprint was established, which can provide accurate and scientific judgment for the control of the fermentation process endpoint, and has certain guiding significance for improving the quality of Marselan wines (Table S1). In addition, this work will provide a new approach for the production management of Ningxia's special wine as well as the development of the native Chinese wine industry.

  • The authors confirm contribution to the paper as follows: study conception and design: Gong X, Fang L; data collection: Fang L, Li Y; analysis and interpretation of results: Qi N, Chen T; draft manuscript preparation: Fang L. All authors reviewed the results and approved the final version of the manuscript.

  • The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

  • This work were supported by the project of Hainan Province Science and Technology Special Fund (ZDYF2023XDNY031) and the Central Public-interest Scientific Institution Basal Research Fund for Chinese Academy of Tropical Agricultural Sciences in China (Grant No. 1630122022003).

  • The authors declare that they have no conflict of interest.

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  • Cite this article

    Gautam N, Ghimire S, Kafle S, Dawadi B. 2024. Efficacy of bio-fertilizers and chemical fertilizers on growth and yield of cowpea varieties. Technology in Agronomy 4: e007 doi: 10.48130/tia-0024-0004
    Gautam N, Ghimire S, Kafle S, Dawadi B. 2024. Efficacy of bio-fertilizers and chemical fertilizers on growth and yield of cowpea varieties. Technology in Agronomy 4: e007 doi: 10.48130/tia-0024-0004

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Efficacy of bio-fertilizers and chemical fertilizers on growth and yield of cowpea varieties

Technology in Agronomy  4 Article number: e007  (2024)  |  Cite this article

Abstract: Cowpea is valued for its nutrition and nitrogen-fixing ability, and investigating bio-fertilizers offers a sustainable way to enhance cowpea growth and yield. A field experiment was conducted from February to June 2022 in the Nawalparasi West, Nepal, to investigate the impact of different fertilizers, including bio-fertilizers and chemical fertilizers, on the growth parameters and yield of cowpea varieties. Employing a double factorial Randomized Complete Block Design (RCBD), the experiment considered two factors: cowpea varieties (Malepatan-1 and Stickless) and fertilizers (control, mycorrhizal, rhizobia, recommended dose of chemical fertilizer (RDF), mycorrhizal + rhizobia, and mycorrhiza + rhizobium + RDF). Malepatan-1 exhibited superior growth and yield compared to Stickless, with higher plant height (125.73 cm), seed weight plant−1 (72.29 g), thousand grain weight (151.62 g), and yield ha−1 (3,536.83 kg ha−1). While the application of rhizobia + mycorrhiza and chemical fertilizers increased various growth parameters, mycorrhiza + rhizobium showed comparable results in terms of yield (4,321.41 kg ha−1) and thousand grain weight (167.19 g) compared to the combination of the former (4,714.26 kg ha−1 and 176.83 g, respectively). Moreover, mycorrhiza + rhizobium demonstrated a higher benefit-cost ratio (3.76), making it economically and environmentally preferable to biofertilizers with chemicals. The study recommends mycorrhiza + rhizobium for its comparable yield, superior economic returns, and environmental sustainability over biofertilizers combined with chemicals. For maximizing economic and sustainable production, the study suggests using the Malepatan-1 cowpea variety with biofertilizers, excluding chemical (inorganic) fertilizers.

    • Cowpea (Vigna unguiculata L.) is a significant annual legume crop used for the dual purpose of pulses and fresh vegetables[1]. Originally from central Africa, it is extensively cultivated in the tropics and sub-tropical regions[2]. In Nepal, it occupies a considerable cultivation area in Terai and inner-Terai regions[3]. Farmers cultivate indigenous and improved varieties of cowpea for grain production[4]. However, despite the increasing trend in cowpea production, its productivity remains lower compared to other legumes[5]. The lower productivity can be attributed to various physical, biotic, and socio-economic constraints[3,6]. Furthermore, there is a lack of efficient integrated nutrient management (INM) practices specifically tailored for legume production in Nepal[3]. Currently, farmers heavily rely on the application of chemical fertilizer, leading to increasing trends in their usage[5,7]. However, the excessive use of chemical fertilizer beyond recommended rates not only results in soil degradation, air and water pollution, reduced soil fertility, and crop production[7,8] but also lowers the inherent nitrogen-fixing process of legumes[9]. To address these long-term effects and promote sustainable agriculture with improved production, the integration of bio-fertilizers into the farming system becomes crucial[10].

      Cowpea, as a leguminous crop, possesses the remarkable ability to fix atmospheric nitrogen, which is crucial for its early vegetative growth and development[11,12]. Prior to the initiation of nitrogen fixation in these legumes, especially those growing on poor organic matter soils, nitrogen fertilizer is typically provided during planting. When applying nitrogen, the rate must not exceed the advised dosage. The nitrogen fixation process is physically slowed down or halted by the legumes when too much nitrogen (N) is given[9].

      The sustainability of farming has been advocated by organic agriculture[7]. It relies on the utilization of microbial-based fertilizers, commonly known as biofertilizers. Among them, Phosphate Solubilizing Bacteria (PSB), Arbuscular Mycorrhiza Fungi (AMF), potassium-solubilizing bacteria, and nitrogen-fixing bacteria have been extensively employed to enhance soil fertility[1315]. In the case of grain legumes, biofertilizers such as rhizobium species and mycorrhiza are widely used[16]. Biofertilizers play a crucial role in plant metabolism and nutrient availability, facilitating nutrient uptake from the soil[17]. The symbiotic association of rhizobium species with legumes promotes biological nitrogen fixation, phosphate solubilization, and production of Indole-3 Acetic Acid (IAA), siderophores, and chitinase. These activities contribute to increased vegetative biomass and improved yield parameters in legumes[18,19]. Similarly, the incorporation of AMF into legume crops establishes a mutually beneficial symbiotic relationship. AMF enhances nutrient mineralization, increases the effective root area, and improves nutrient availability to crops, and in return, AMF obtains carbon from the crops[17,20].

      Despite their nutrient richness, inorganic fertilizers give rise to a myriad of issues[7,21]. Biofertilizers, though less mobile than their inorganic counterparts, offer a plethora of benefits to the cultivated soil[2224]. The necessity for environmentally safe agricultural practices, coupled with the scarcity and high cost of synthetic fertilizers, has prompted extensive research into organic-based alternatives, leading to their adoption by many farmers[7]. Nonetheless, much of the prevailing research has been unidirectional, focusing solely on either biofertilizers or inorganic fertilizers. The objective of this research was to investigate the effects of biofertilizers, inorganic fertilizers, and combined application of chemical fertilizers and biofertilizers on the growth attributes and yield parameters of different varieties of cowpea variety in Nawalparasi West, Nepal. Additionally, the study aimed to compare the performance of the Malepatan-1 variety with the Stickless variety in terms of growth parameters, yield attributes, and overall yield. The result holds immense value for both the practical and theoretical realms, as they provide invaluable recommendations to farmers on adopting sustainable and cost-effective practices that enhance yield while minimizing nutrient losses.

    • The study was conducted on a farmer's field in February 2022 at Ramgram-17, Nawalparasi West, Nepal. The study site is situated at a geographic position of 27°32' N latitude and 83°40' E longitude, with an elevation of 119 m above sea level. Nawalparasi West has a sub-tropical and humid climate.

    • Soil samples were taken from each replication by using a shovel from 0 to 15 cm depth. Then the sample was analyzed for soil properties as presented in Table 1. The soil was tested by the technical personnel from Soil and Fertilizer Testing Laboratory, Khajura, Banke. The total nitrogen was determined by Kjeldhal distillation method[25]; available phosphorous by Olsen's method[26], and available potassium by the ammonium acetate method. Organic matter was determined by the Walkley-Black method[27], pH (1:1 soil : water suspension) by Beckman Glass electrode pH meter and soil texture by the hydrometer method.

      Table 1.  Physico-chemical characteristics of soil in the experimental field.

      S. N.Soil propertiesValues
      1.Textural classClay loam (Alluvial)
      2.Chemical properties
      2.1pH7.7 (Alkaline)
      2.2Nitrogen (%)0.09 (Low)
      2.3Phosphorus, P2O5 (kg·ha−1)(Low)
      2.4Potash, K2O (kg·ha−1)(Low)
      2.5Organic matter (%)1.95 (Low)
    • The experiment was designed using a two-factor Randomized Complete Block Design (RCBD) with 12 treatments replicated three times. The factors considered were variety and fertilizer. Variety consisted of two types; Malepatan-1 (V1) and Stickless (V2). The fertilizer factor included no fertilizer treatment (F0), mycorrhiza (F1), rhizobium (F2 = 100 g per 5 kg of seed), the recommended dose of fertilizer (F3 = 20:40:20 kg NPK ha−1), mycorrhiza + rhizobium (F4), and mycorrhiza + rhizobium + RDF (F5). Cowpea varieties and fertilizers were obtained from Dawadi biofertilizer center, Buddha chowk, Chitwan (Nepal).

      Each experimental plot had an area of 2.4 m × 1.5 m, accommodating four rows. The rows were spaced 60 cm apart, with each row containing five hills spaced 30 cm apart. Two seeds were sown per hill. The inter-plot distance was set at 0.3 m, while the distance between replications was maintained at 0.75 m. The field was plowed 15 d before seed sowing by using a rotavator to achieve a good soil tilth. This was followed by shallow ploughing, and planking to level the land. After leveling, clods were broken, and weeds and stubbles of the previous crop were removed.

      The chemical fertilizers were supplied to the experimental fields as nitrogen, phosphorus, and potassium through urea, single super phosphate (SSP), and muriate of potash (MOP), respectively, at the rate of 20 kg N, 40 kg P and 20 kg K ha−1 i.e. 20:40:20 kg NPK ha−1. The recommended amounts of urea, SSP, and MOP were calculated per area basis and weighed separately for each treatment. The total nitrogen dose was split into two equal doses. The full dose of phosphorus and potassium and half of the nitrogen dose was applied as a basal dose one day prior to sowing. The second dose of nitrogen was applied as a top dress in the third week of sowing in March 2022. Gap filling was conducted two weeks after sowing to maintain the plant population. Irrigation was provided at weekly intervals until maturity. Weeding was performed manually, with the first round at 15 d after sowing (DAS), followed by the second and third rounds at 30 DAS and 45 DAS, respectively. Pesticides, specifically, Cypermethrin at 1 ml·L−1 and Emamectin benzoate at 5 ml per 15 L, were used during the research period to control pod borers.

    • Commercial rhizobia inoculants are available to farmers in various forms, such as solid, liquid, and freeze-dried formulations[28]. When selecting rhizobia inoculants, it is important to consider specific host legumes and ecological settings to ensure superior nodulation and nitrogen fixation efficiency compared to natural rhizobia populations[29]. Seeds were inoculated with Bradirhizobium sp. at 100 g per 5 kg of seed. To prepare the inoculant, 100 g of jaggary was initially dissolved in 250 ml of water to create jaggery slurry. The slurry was then boiled and cooled to room temperature. The recommended dose of Bradirhizobium sp. was added to the paste, and the required quantity of seeds was thoroughly mixed with the inoculant to achieve a uniform coating. The coated seeds were shade dried for 20 min prior to sowing, as outlined by Pandey et al.[30].

      For mycorrhiza treatment, mycorrhiza AVESTA (all endo mycorrhiza including Glomus sp. and Acaulospora sp. coated on carriers through Agrinos Gel Technology along with nutrients, AVESTA: 3,000−3,500 spores g−1 at 4 kg 10 katha−1 (1 katha = 0.00138 ha) was incorporated in soil at 14 DAS. Each plot was inoculated with 3.5 g plot−1 inoculate for mycorrhiza treatment; with inoculate placed 4 cm below the seeds. This was immediately followed by light irrigation.

    • Six plants were randomly selected excluding border crops and from which parameters were observed and measured. The plant height was measured with the help of a scale and measuring tape from the base of the plant at the ground surface to the tip of the highest visible part at 30, 45 and 60 DAS. All the pod bearing as well as non-bearing branches were observed at 30, 45 and 60 DAS for number of branches.

    • Number of pods plant−1, pod length and seed weight plant−1 were obtained from randomly selected six plants excluding border plants and finally, after averaging, the total number of pods plant−1, pod length and total weight of seed plant−1 in gram was obtained.

    • Sun-dried seeds of each plot were weighted to obtain yield per plot in grams. The seed yield per plot for each plot was converted into hectare to obtain the total yield in kg·ha−1. The weight of sun-dried thousands seed grain samples were weighted in grams.

    • The data recorded on different parameters were tabulated in Microsoft Excel 2010. Analysis of Variance (ANOVA) was performed using the "agricolae" package in R-Studio (R version 4.2.0). To compare means, Duncan's Multiple Range Test (DMRT) was applied to the analyzed data at a significance level of 5%.

    • Significant variation was observed in height of the plant of cowpea at different stages of growth as influenced by different varieties (Table 2). It was noted that the tallest plant height (42.06 cm) was recorded from Stickless at 30 DAS whereas the tallest plant height was recorded from Malepatan-1 at 77.56 and 125.73 cm at 45 and 60 DAS respectively. This variation in plant height between varieties might be due to individual varietal genetic superiority.

      Table 2.  Effect of different varieties and fertilizers on the plant height of cowpea.

      TreatmentPlant height (cm)
      30 DAS45 DAS60 DAS
      VarietyMalepatan-1 (V1)40.06b77.56a125.73a
      Stickless (V2)42.72a64.37b86.19b
      LSD (0.05)1.261.267.30
      SEM (±)0.210.441.24
      F-test*********
      CV (%)4.422.579.96
      FertilizerControl37.06d60.16e86.46c
      Mycorrhiza40.58c68.60d101.79bc
      Rhizobium40.99bc67.89cd98.40b
      RDF41.45bc72.97bc109.86b
      Mycorrhiza + Rhizobium43.15ab74.27b111.38b
      Mycorrhiza + Rhizobium + RDF45.10a81.90a127.85a
      LSD (0.05)2.194.5612.64
      SEM (±)0.120.250.71
      F-test*********
      CV (%)4.425.379.96
      Grand mean41.3970.96105.96
      Data in columns with the same letters in DMRT are not significantly different (p = 0.05), SEM = Standard Errors of Means, CV = Coefficient of Variation, LSD = Least Significant Difference, *** = significant at p < 0.001.

      The plant height of cowpea was influenced significantly at different growth stages influenced by different fertilizers. The results revealed that the tallest plant height was obtained from F5 at all the stages of growth. At 30 DAS, the tallest plant height (45.10 cm) was achieved from F5 which was at par with F4 (43.15 cm). Similarly, the shortest plant height (37.06 cm) was achieved from F0. The plant height obtained from F1 (40.58 cm), F2 (40.99 cm) and F3 (41.45 cm) were statistically similar. At 45 DAS, the tallest plant height (81.90 cm) was achieved which was significantly superior over all the other treatments viz; F0 (60.16 cm), F1 (68.60 cm), F2 (67.89 cm), F3 (72.97 cm) and F4 (74.27 cm) whereas the shortest plant height (60.16 cm) was achieved from F0. Similarly, at 60 DAS the tallest plant height (127.85 cm) was achieved which was significantly superior over all the other treatments. The height of the plant was not influenced significantly due to the effect of the interaction between variety and fertilizer at any stage of growth.

    • Significant variation was observed in the number of branches of cowpea at different stages of growth as influenced by different varieties (Table 3). It was noted that the higher number of branch (2.71) was recorded from Malepatan-1 at 30 DAS whereas the higher number of branches were recorded from Stickless, 4.49 and 6.36 at 45 DAS and 60 DAS respectively.

      Table 3.  Effect of different varieties and fertilizers on the branches per plant of cowpea.

      TreatmentNumber of branches plant−1
      30 DAS45 DAS60 DAS
      VarietyMalepatan-12.71a4.09b5.39b
      Stickless2.03b4.49a6.36a
      LSD (0.05)0.260.340.45
      SEm (±)0.0440.0590.078
      F-test*******
      CV (%)15.9011.7411.12
      FertilizerControl2.03c3.72b5.25c
      Mycorrhiza2.13c4.13b5.34bc
      Rhizobium2.28bc3.80b5.61bc
      RDF1.94c4.13b5.94bc
      Mycorrhiza + Rhizobium2.69b4.33b6.14b
      Mycorrhiza + Rhizobium + RDF3.16a5.63a6.97a
      LSD (0.05)0.450.6040.78
      SEM (±)0.0250.0340.045
      F-test********
      CV (%)15.9011.7411.12
      Grand mean2.374.295.87
      Data in columns with the same letters in DMRT are not significantly different (p = 0.05), SEM = Standard Errors of Means, CV = Coefficient of Variation, LSD = Least Significant Difference, * = significant at p < 0.05, ** = significant at p < 0.01, *** = significant at p<0.001.

      The number of branches per plant of cowpea was influenced significantly at different growth stages as influenced by different fertilizers (Table 3). The results revealed that higher numbers of branches were recorded from F5 at all the stages of growth. At 30 DAS, a higher number of a branch (3.16) was achieved from F5 which was significantly superior over all the other treatments viz; F0 (2.03), F1 (2.13), F2 (2.28), F3 (1.94) and F4 (2.69) whereas the lower number of a branch (1.94) was achieved from F3. At 45 DAS, a higher number of the branch (5.63) was achieved from F5 which was significantly superior over all the other treatments. Similarly, at 60 DAS, a higher number of a branch (6.97) was achieved from F5, which was significantly superior over all the other treatments whereas the lower number of a branch (5.25) was achieved from F0 but was at par with F1 (5.34), F2 (5.61), and F3 (5.94). The number of branches per plant was not influenced significantly due to the effect of interaction between variety and fertilizer at any stage of growth.

    • Significant variation was observed in the number of pods per plant of cowpea as influenced by different varieties (Table 4). It was noted that the higher number of pods plant−1 (31.34) was recorded from Stickless whereas the lower number of pods plant−1 (27.50) was recorded from Malepatan-1.

      Table 4.  Effect of different varieties and fertilizers on the pods per plant, seed weight and pod length of cowpea.

      TreatmentPods plant-1Seed weight plant−1 (g)Pod length (cm)
      VarietyMalepatan-127.50b72.29a25.39
      Stickless31.34a66.08b26.31
      LSD (0.05)2.624.85
      SEM (±)0.440.82
      F-test***NS
      CV (%)12.9210.15
      FertilizerControl24.61c47.92d23.47
      Mycorrhiza28.47bc62.21c27.01
      Rhizobium27.86bc57.01c25.25
      RDF26.52c57.65c25.81
      Mycorrhiza + Rhizobium31.86b88.98b25.71
      Mycorrhiza + Rhizobium + RDF37.19a101.35a27.84
      LSD (0.05)4.558.41
      SEM (±)0.250.47
      F-test******NS
      CV (%)12.9210.15
      Grand mean29.4269.19
      Data in columns with the same letters in DMRT are not significantly different (p = 0.05), SEM = Standard Errors of Means, CV = Coefficient of Variation, LSD = Least Significant Difference, * = significant at p < 0.05, ** = significant at p < 0.01, *** = significant at p < 0.001, NS = Non-significant.

      Number of pods per plant of cowpea were influenced significantly due to fertilizer (Table 4). The results revealed that the higher number of pods plant−1 (37.19) was achieved from F5 which was significantly superior over all the other treatments. Lowest number of pods plant−1 (24.61) were obtained from F0, which was statistically at par with treatments F1, F2, and F3. Similarly, number of pods plant−1 as obtained due to the effect of F4 were statistically similar with treatments F1, and F2. These findings are in accordance with the findings of Jayshree & Umesha[31], who demonstrated that there was significant increase in growth parameter viz., plant height, number of branches, number of nodules, plant dry weight, crop growth rate and yield attributing parameters viz., pods plant1, seeds pod−1, 1000-seed weight, seed yield and biological yield were recorded with dual inoculation of Phosphate Solubilizing Bacteria and VAM along with optimum dose of inorganic fertilizers. The numbers of pods per plant were not influenced significantly due to the effect of interaction between variety and fertilizer.

    • Significant variation was observed on seed weight per plant of cowpea as influenced by different variety (Table 4). It was noted that the higher seed weight plant−1 (72.29 g) were recorded from Malepatan-1 where the lower seed weight plant−1 (66.08 g) were recorded from Stickless. The findings of the present study are in line with the findings of Kwaga[32], who demonstrated that the variations among varieties in terms of parameters like plant height, number of leaves, pod length, pods plant-1 and yield is due to the individual varietal superiority, due to genetic variation, and environmental variations.

      Seed weight per plant of cowpea was influenced significantly due to fertilizer (Table 4). The results revealed that the higher seed weight per plant (101.35 g) was achieved from F5 which was significantly superior over all the other treatments. Lowest seed weight per plant (47.92 g) was obtained from F0. The seed weight per plant was not influenced significantly due to the effect of interaction between variety and fertilizer.

    • The pod length was not influenced significantly due to the effect of fertilizer (Table 4). However, mathematically higher pod length was observed from Stickless (26.31 cm). The pod length was not influenced significantly due to the effect of fertilizer. However, mathematically higher pod length was observed from F5 (27.84 cm) while shortest pod length was obtained from F0 (23.47 cm). The pod length was not influenced significantly due to the effect of interaction between variety and fertilizer.

    • Significant variation was observed on yield plot−1 of cowpea as influenced by different variety (Table 5). It was noted that the highest seed yield plot1 (1,273.24 g) was recorded from Malepatan-1 where the lowest yield plot−1 was recorded from Stickless. The findings of the present study are in line with the findings of Bhattarai et al.[4] and this variation might be due to the genetic make-up of the varieties, genotype x environment interaction and nutrient use efficiency of varieties[4].

      Table 5.  Effect of different varieties and fertilizers on the yield and test weight of cowpea.

      TreatmentYield plot−1
      (g)
      Yield hectare
      (kg ha−1)
      1,000 seed weight
      (g)
      VarietyMalepatan-11,273.24a3,536.83a151.62a
      Stickless1,173.21b3,258.94b125.46b
      LSD (0.05)92.82257.8613.06
      SEM (±)15.8243.962.23
      F-test*****
      CV (%)10.9710.9713.64
      FertilizerControl933.27b2,592.43b116.38b
      Mycorrhiza1,024.27b2,845.21b123.08b
      Rhizobium1,061.67b2,949.10b123.03b
      RDF1,067.35b2,964.90b124.71b
      Mycorrhiza + Rhizobium1,555.69a4,321.41a167.19a
      Mycorrhiza + Rhizobium + RDF1,697.12a4,714.26a176.83a
      LSD (0.05)160.78446.6222.62
      SEM (±)9.1325.381.28
      F-test*********
      CV (%)10.9710.9713.64
      Grand mean1,223.233,397.89138.54
      Data in columns with the same letters in DMRT are not significantly different (p = 0.05), SEM = Standard Errors of Means, CV = Coefficient of Variation, LSD = Least Significant Difference, * = significant at p < 0.05, *** = significant at p < 0.001.

      Seed yield per plot was influenced significantly due to fertilizer. The results revealed that the highest yield plot−1 (1,697.12 g) was achieved from F5 which was at par with fertilizer treatment F4 (1,555.69 g) but significantly superior over all other treatments viz; F0 (933.27 g), F1 (1,024.27 g), F2 (1,061.67 g), and F3 (1,067.35 g). Lowest yield plot−1 (933.27 g) was obtained from F0 which is statistically at par with treatments F1, F2 and F3. These findings are in accordance with the findings of Sharma & Jaga[33], who demonstrated that there was a significantly higher nutrient uptaking, higher nodule number and better quality of oil of soybean found due to the combined application of VAM + Rhizobium + PSB + 75% RDF. The higher yield plot−1 might be due to the effective absorption of mineral nutrients by mycorrhiza and biological nitrogen fixation by Rhizobium. Non-significant result was obtained for yield plot−1 due to interaction between variety and fertilizer.

    • Significant variation was observed on yield ha−1 of cowpea as influenced by different variety (Table 5). It was noted that the highest yield ha−1 (3,536.83 kg) was recorded from Malepatan-1 where the lowest yield ha−1 (3,258.94 kg) was recorded from Stickless. The findings of the present study are in line with the findings of Bhattarai et al.[4], who demonstrated that there is a correlation between yield plot−1 and yield ha−1.

      Yield ha−1 was significantly influenced due to fertilizer. The results revealed that the highest yield ha−1 (4,714.26 kg·ha−1) was achieved from F5 which was at par with F4 (4,321.41 kg·ha−1) but significantly superior over other treatments viz; F0 (2,592.43 kg·ha−1), F1 (2,845.21 kg·ha−1), F2 (2,949.10 kg·ha−1) and F3 (2,964.90 kg·ha−1). Lowest yield (2,592.43 kg·ha−1) was obtained from F0 which was statically at par with treatments F1, F2, and F3. These findings are in accordance with the findings of Molla and Solaiman[34], Sharma & Jaga[33] and Yadav et al.[35]. The increase in yield in kg ha−1 for F5 treatment might be due to the dual inoculation of mycorrhiza + rhizobium along with NPK fertilizer and the better utilization of inorganic fertilizers. Another possible reason for higher yield in kg per ha might be due to the translocation of essential metabolites and photosynthates to the economic parts of plants[33]. Non-significant results were obtained for yield ha>−1 due to interaction between variety and fertilizer.

    • Significant variation was observed on thousands seed weight of cowpea as influenced by different variety (Table 5). It was noted that the higher test weight (151.62 g) was recorded from Malepatan-1 where the lowest test weight (125.46 g) was recorded from Stickless. The findings of the present study are in line with the findings of Bhattarai et al.[4], who demonstrated that cowpea varieties show a great variation in terms of growth parameters and yield parameters. This variation in test weight might be due to the genetic variation among cowpea variety.

      Thousands seed weight was significantly influenced due to fertilizer. The results revealed that the highest test weight (176.83 g) was achieved from F5 which was at par with F4 (167.19 g) but significantly superior over other treatments viz; F0 (116.38 g), F1 (123.08 g), F2 (123.03 g) and F3 (124.71 g). These findings are in accordance with the findings of Dobo[36], who demonstrated that since rhizobia bacteria supply nitrogen to the host plant through biological nitrogen fixation and AM fungi deliver phosphate from the soil beyond root access, the tripartite interactions in legumes have a synergistic effect on the host plant growth response. Non-significant result was obtained for thousands seed weight due to interaction between variety and fertilizer.

    • The economic analysis of crop treatments, including different varieties and fertilizer applications, revealed distinct variations in key economical parameters. Among the varieties, Malepatan-1 demonstrated the highest gross return of NRs. 424,419.6 ha−1, net return of NRs. 304,419.6 ha−1 and benefit cost ratio (BCR) of 2.53. Stickless, another variety, exhibited a lower gross return of NRs. 391,072.8 ha−1 and a net return of NRs. 266,572.8 ha−1. In terms of fertilizers, the Mycorrhiza + Rhizobium combination demonstrated the highest BCR of 3.76, reflecting efficient cost management (Fig. 1). The RDF treatment resulted in lowest BCR of 2.18.

      Figure 1. 

      Effect of different varieties and fertilizers on the economics of cowpea production.

      Table 6 illustrates a sensitivity analysis conducted on cowpea cultivation, specifically employing the mycorrhiza + rhizobium treatment. The analysis explores the impact of variations in total cost and gross benefit on key economic parameters. Under the new condition of a 10% increase in total cost, the corresponding figures show a new total cost of NRs. 119,625, with a gross return of NRs. 518,569.2. This adjustment results in a net return of NRs. 398,944.2 and a BCR of 3.33. Despite the increased cost, the venture remains economically feasible. In the scenario where gross benefit is decreased by 10%, the new total cost is NRs. 108,750, with a gross return of NRs. 466,712.3. The net return and BCR stand at NRs. 357,962.3 and 3.29, respectively. Even with reduced gross benefit, the enterprise remains economically viable. Under simultaneous conditions of a 10% increase in total cost and a 10% decrease in gross benefit, the new total cost is NRs. 119,625, with a gross return of NRs. 466,712.3. This adjustment yields a net return of NRs. 347,087.3 and a BCR of 2.90. Despite these compounded adjustments, the venture remains economically feasible.

      Table 6.  Sensitivity analysis of cowpea with the application of mycorrhiza + rhizobium treatment.

      S.N.New conditionNew total cost (NRs.)New gross return (NRs.)Net return (NRs.)BCRRemarks
      1Total cost increased by 10%119625518569.2398944.23.33Still feasible
      2Gross benefit decreased by 10%108750466712.3357962.33.29Still feasible
      3Total cost increased by 10% and
      gross benefit decreased by 10%
      119625466712.3347087.32.90Still feasible
    • The Pearson correlation reveals valuable insights into the interrelationships among different variables influencing the growth and yield of cowpea varieties (Fig. 2). Plant height demonstrates a moderate positive correlation with the number of branches (0.35) and strong positive correlations with pods per plant (0.47), seed weight per plant (0.72), pod length (0.49), thousand grain weight (TGW) (0.80), and yield per hectare (0.71). Similarly, the number of branches exhibits a moderate positive correlation with plant height (0.35) and strong positive correlations with pods per plant (0.90), seed weight per plant (0.76), pod length (0.67), TGW (0.64), and yield per hectare (0.78). Notably, pods per plant demonstrate a strong positive correlation with both plant height (0.47) and the number of branches (0.90). Seed weight per plant shows strong positive correlations with plant height (0.72), the number of branches (0.76), and pods per plant (0.91). Furthermore, pod length exhibits strong positive correlations with plant height (0.49), the number of branches (0.67), and pods per plant (0.79). TGW shows strong positive correlations with plant height (0.80), the number of branches (0.64), pods per plant (0.78), and seed weight per plant (0.97). Finally, yield per hectare displays strong positive correlations with plant height (0.71), the number of branches (0.78), pods per plant (0.88), seed weight per plant (0.99), pod length (0.57), and TGW (0.98). These findings suggest that the use of bio-fertilizers and chemical fertilizers significantly influences the growth and yield of cowpea varieties, with positive correlations observed across multiple parameters.

      Figure 2. 

      Correlation among various growth and yield parameters of cowpea.

    • Both of the studied varieties show significant variation in terms of growth and yield parameters. In comparison to the stickless variety, Malepatan-1 exhibited superior traits such as increased plant height, seed weight, thousand grain weight, and overall yield when compared to the stickless variety. Despite the Stickless variety exhibiting a higher number of branches plant−1 and a greater number of pods plant−1, its yield is significantly lower compared to the Malepatan-1 variety. This difference in yield can be attributed to the significantly greater seed weight observed in the Malepatan variety. This observation highlights the crucial role of seed weight in determining the overall yield of cowpea varieties. It is important to note that the environmental conditions and nutrient availability were consistent for both varieties during the study; therefore, the discrepancy in seed weight and subsequent yield can be attributed to the inherent genetic makeup of the varieties. These findings are in accordance with the findings of Bhattarai et al.[4] and Jannat[37], who observed significant variation among varieties in terms of growth and yield parameters except for pod length. These variations might be due to the genetic causes existing within different varieties[4].

      The application of mycorrhiza + rhizobium + RDF demonstrated favorable outcomes, including increased plant height, a higher number of branches plant-1, a greater number of pods plant−1, and higher seed weight plant−1. However, when considering thousand seed weight and yield, the combined application of biofertilizers (mycorrhiza + rhizobium) and the combined application of RDF, mycorrhiza, and rhizobium yielded the highest results. Cowpea, like other legumes, benefits from nitrogen fixation by rhizobium bacteria. When combined with mycorrhiza, which enhances nutrient absorption, it ensures an ample supply of essential nutrients for plant growth and reproductive development, leading to increased pod production and seed weight[3840]. It is noteworthy that the individual application of either biofertilizers or chemical fertilizers did not lead to significant improvements in growth and yield parameters compared to the control plot. The combined application of mycorrhiza, rhizobium, and RDF likely created a synergistic effect on plant growth. Mycorrhiza can improve nutrient uptake[41], rhizobium facilitates nitrogen fixation[42,43], and RDF provides essential macro and micronutrients. Together, these factors promote better plant development, resulting in higher pod number and seed weight. The higher seed weight per plant might be due to the combined application of bio-fertilizer and inorganic fertilizers might be due to the translocation of essential metabolites and photosynthates to the economic parts of plant. Furthermore, there was no significant difference in yield between the plots that received the combined application of biofertilizers and the plots that received the combined application of biofertilizers and inorganic fertilizers. Therefore, it is advisable to apply only the combination of biofertilizers, as the additional cost of chemical fertilizers does not justify the same yield as achieved without their application.

      Molla & Solaiman[34] also reported the findings for mung bean, who observed that dual inoculation of mycorrhiza and rhizobium with N, P fertilizers increases growth parameters, nodulation, and enhances nutrient uptake. Also, our findings are in accordance with the findings of Yadav et al.[35], who demonstrated that there was a significant increment in vegetative growth, yield attributes, yield, and test weight of Vigna Mungo due to the inoculation of PSB, VAM along with phosphorus. Researchers such as Channaveerswami[44] in groundnut and Ghimire et al.[7] in bitter gourd have found that the combination of organic and inorganic fertilizers yielded better outcomes compared to the use of inorganic fertilizers only. This synergistic effect can be attributed to the fact that organic fertilizers contain essential nutrients, growth-promoting substances, and beneficial microflora, which, when combined with inorganic fertilizers, create favorable soil conditions that enhance nutrient use efficiency[45].

      Mycorrhizal fungi form symbiotic relationships with plant roots, extending the root system and increasing the plant's ability to access nutrients and water[4648]. This enhanced root development likely contributed to the observed improvements in yield parameters. Biofertilizers have been recognized for their ability to enhance soil organic matter content, leading to reduced bulk density and decreased compaction[49,50]. This, in turn, creates a favorable growing environment for plants, promoting improved growth and development. The improved plant height observed in certain studies can be attributed to enhanced nodulation and nutrient uptake facilitated by the inoculation of biofertilizers[51]. The increase in the number of branches may be attributed to the mineralization and easy solubilization of nutrients by biofertilizers, leading to excessive vegetative growth and an increased number of branches plant−1[52]. Additionally, Sharma & Jaga[33] found that the combined application of vesicular-arbuscular mycorrhiza, rhizobium, phosphate-solubilizing bacteria, and 75% NPK fertilizer resulted in a higher number of leaves plant−1, increased leaf area, improved photosynthesis efficiency, and ultimately higher yield and yield attributes. The combined application of mycorrhiza and rhizobium with NPK fertilizer, along with the effective utilization of inorganic fertilizers, can account for the improved yield attributes such as the number of pods plant−1, seed weight plant−1, overall yield, and thousand seed weight. The higher in thousands seed weight for treatment F5 might be due to the dual inoculation of mycorrhiza and rhizobium and their synergistic effect on cowpea plant. This combination may facilitate the translocation of essential metabolites and photosynthates to the economically important parts of the plant[33].

      The mycorrhiza and rhizobium treatment, excluding chemical fertilizer (RDF), has demonstrated a higher BCR, primarily owing to two crucial factors. Firstly, the reduced treatment costs contribute to this outcome, and secondly, the heightened crop yields play a pivotal role. The combination of biofertilizers ensures a balanced and synergistic nutrient supply to crops, effectively enhancing their growth and maximizing yield potential. As a result, this approach frequently results in increased crop productivity when compared to the use of individual fertilizer types, as noted in previous studies[45]. The results indicate the feasibility of cowpea cultivation under diverse conditions, encompassing both favorable and unfavorable scenarios. The calculated BCR exceeding 1 underscores the economic viability of cowpea cultivation. The positive net return further substantiates its profitability within the specified geographic area. Furthermore, a rigorous sensitivity analysis of mycorrhiza and rhizobium treatment, involving a 10% increase in variable costs and a corresponding 10% decrease in benefits, was conducted. Remarkably, the BCR ratio remained above 1 even under these altered conditions, affirming the robust feasibility of the enterprise, particularly in less favorable circumstances. The sensitivity analysis demonstrates the resilience of cowpea cultivation with the mycorrhiza + rhizobium treatment, as evidenced by sustained positive net returns and BCR values across various altered conditions.

    • Cowpea, being a leguminous nitrogen-fixing plant, requires a relatively low amount of fertilizers, particularly chemical fertilizers. Based on the obtained results, it can be concluded that the application of a combination of rhizobium and mycorrhiza would be more desirable. This approach gives a yield equivalent to those achieved through the combined application of chemical fertilizers with pronounced growth and yield attributes and biofertilizers while also significantly reducing fertilizer costs, making it a more economical choice. Mycorrhiza + rhizobium achieved the highest BCR, surpassing the BCR obtained with the combined application of biofertilizers and chemical treatments, making it more environmentally friendly and economically sound. Furthermore, the Malepatan-1 variety outperforms the stickless variety across various growth parameters, yield attributes, and seed yield. Consequently, it is strongly recommended for cultivation for maximizing cowpea production. Thus, the cultivation of the Malepatan-1 cowpea variety with the application of a combination of biofertilizers is the most suitable approach in terms of both production outcomes and economic viability. Notwithstanding the favorable outcomes achieved, it is imperative to emphasize that the effectiveness of diverse fertilizers and cultivars must undergo comprehensive evaluation on a broader scale, encompassing various ecological regions.

    • The authors confirm contribution to the paper as follows: study conception and design, data collection, analysis and interpretation of results: Gautam N, Ghimire S, Kafle S, Dawadi B; draft manuscript preparation: Ghimire S, Gautam N. All authors reviewed the results and approved the final version of the manuscript.

    • The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

    • The authors are thankful to the Agriculture and Forestry University, Chitwan, Nepal, Prime Minister Agriculture Modernization Project, Nepal and Assistant Professor Tulsi Parajuli for continuous support during the research work.

      • The authors declare that they have no conflict of interest.

      • Copyright: © 2024 by the author(s). Published by Maximum Academic Press, Fayetteville, GA. This article is an open access article distributed under Creative Commons Attribution License (CC BY 4.0), visit https://creativecommons.org/licenses/by/4.0/.
    Figure (2)  Table (6) References (52)
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    Gautam N, Ghimire S, Kafle S, Dawadi B. 2024. Efficacy of bio-fertilizers and chemical fertilizers on growth and yield of cowpea varieties. Technology in Agronomy 4: e007 doi: 10.48130/tia-0024-0004
    Gautam N, Ghimire S, Kafle S, Dawadi B. 2024. Efficacy of bio-fertilizers and chemical fertilizers on growth and yield of cowpea varieties. Technology in Agronomy 4: e007 doi: 10.48130/tia-0024-0004

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