EFFECT OF FERTILIZER AND GENOTYPE ON CROP QUALITY AND PROFITABILITY OF GROUNDNUT (Arachis hypogaea L.) IN MOROGORO, TANZANIA Abstract Objective: Soil fertility status is an important factor for agricultural productivity and the economic livelihood of smallholder farmers in developing countries. Degradation of soil fertility status has adverse effects on the quality and profitability of agricultural produce. Appropriate use of fertilizer resources enhances crop yield, thus enhancing quality and profitability of crops. Methodology: In an attempt to evaluate the response of groundnut to fertilizer with respect to crop quality and profitability, an experiment a split plot Randomized Complete Block Design (RCBD) with four replications in 2015 at the Sokoine University of Agriculture Morogoro, Tanzania. Three improved groundnut genotypes (Mangaka, Masasi and Pendo) were used as main plot factor Fertilizer was applied at 0 kg ha, 55 kg P/ha as DiAmmonium Phosphate and 125 kg Ca/ha as Minjingu mazao. Groundnut kernel obtained from the treated plots were used to assess crop quality, including 100-kernel weight, crude protein and oil contents. Whereas Value cost ratio was used to determine the profitability of fertilizer use in groundnut production. Data was subjected to analysis of GENSTAT 14th software and means separation were made using Least Significant Difference (LSD) at 5% significance level. Results: Results from the study showed significant effect of fertilizer and groundnut genotypes on crop quality and profitability. Genotype x fertilizer interactions showed significant influence of Minjingu on kernel size, protein and oil contents of all groundnut genotypes, whereas the application of P significantly influenced yield and profitability of groundnut. A VCR (>2.0) as obtained from the study is an indication that use of Phosphatic and calcium fertilizers enhances crop quality, hence profitability of groundnut. Conclusion: Further research involving higher P and Ca rates and treatment combination in multi-locational trials is suggested. Key words: Calcium, Phosphorus, Fertilizers, Crop Quality, Profitability 1.0 Introduction Groundnut (Arachis hypogaea L.) usually grown as a cash crop, also known as peanut, earthnut, monkey-nut or goober, is a self-pollinating, indeterminate, annual herbaceous legume crop (Adinya et al., 2010). As an important source of fats, protein and raw materials for the cosmetic and confectionary industries (Sorrensen et al., 2004; Okello et al., 2010). Poor soil fertility in Africa accounts for 75% yield losses in legumes as many smallholder farmers, growing groundnut do not have access to fertilizers to overcome this constraint Papanastassiou (2012). The average yield of groundnut in Tanzania, 0.96t/ha is far below the yield potential of 2 t/ha (FAOSTAT, 2013). Reducing the yield gap calls for an understanding of abiotic and socio- economic constraints including low fertility status of soils, poor agronomic practices irregular rainfall patterns as well as availability and access to fertilizer and improved seed that limit production(Pande and Narayana, 2002; Caliskan et al., 2008). Groundnut is an important oil crop in Tanzania; besides it serves as the source of raw materials for the confectionery industry, however, low production is likely to affect farmers’ income. Adoption of quality seed, cost effective technologies and sustainable agronomic practices including appropriate use of fertilizer resources are major steps in enhancing groundnut production among smallholder farmers. To enhance groundnut crop quality and profitability the research was conducted investigate the response of groundnut crop quality to Ca and P nutrition, hence the economic return on such practices. 2.0 Materials and Methods 2.1 Field layout and experiment design Field experiment was laid out at Sokoine University of Agriculture (SUA), Crop Museum situated at latitude 6° 45’’ South and longitude 37° 40” East at 525 m.a.s.l in Morogoro municipality characterized by kaolinitic clay soils, which are well drained and mostly clay (Semoka, 2003). The experiment was 9 factorial combination with four replications laid down in randomized complete block design. The factors were three groundnut genotypes (Mangaka, Masasi and Pendo) with P and Ca were applied at rates of ( 0, 55, and 125 kg/ha),respectively. Application of P was done at planting,while Ca was applied at pegging stage Soil samples were taken at the depth of 20 cm as described by Landon,1999 and sent to the Department of Soil and Geological Sciences Laboratory for physical and chemical analyses as prescribed by laboratory precedure,while land clearing and all agronomic practices were carried out as described by Kanyeka et al. (2007). 3.0 Data Collection Crop quality data including 100- kernel weigh was recorded whereas analyses for Crude protein and Oil content were done at the Food Science and Technology laboratory at SUA. A random selection of 100 air dried kernels at 15% moisture content were taken from the harvested plants for weighing thereafter; seed size was determined as described by (Acland, 1971). Crude protein (%CP) and Oil content: oil content (%fat) were determined by Kjeldahl method (Bremner and Mulvaney, 1982) and standard Soxhlet extraction procedure (AOAC, 1990), respectively. 3.1 Crop Profitability Value -Cost Ratio (VCR) as described by Bhatti,2006 was used to determine the ratio between the value of the additional crop yield and the cost of inputs taking into consideration the cost of seed, fertilizers, labor and the average price of groundnut on the local market. VCR = Ʃyi x p1 Ʃxi P2 Where: yi = extra yield produced due to input (kg/ha) P1 = value of extra yield produced ($/kg) xi = input applied (kg/ha) P2 = cost of input ($/kg). Value cost ratio was further rated as follow: VCR = 1: yield may be increased but no financial incentive to adopt new practice VCR = 2: farmers earn profits VCR = >2: Minimum acceptable level for adoption of new practice by farmers. Data Analyses Data collected were subjected to analysis of variance (ANOVA) using GENSTAT released version 14th edition and declared significant at P < 0.05 using the following statistical model as described by Gomez and Gomez (1984). The mean separation test was done using Duncan Multiple Range Test (DMRT) at P≤ 0.05. Results Detailed physico-chemical analyses of soil for the study are shown in Table 1. Table 1: Soil physio-chemical characteristics at experimental site Properties Result unit Remarks1 A. Physical Texture Sandy Clay Loam Sand 49.2 % Clay 42.72 % Silt 8.08 % B. Chemical pH 5.9 Moderately acid Organic Carbon 0.07 % Very low Total Nitrogen 0.18 % Very low Organic Matter 0.12 % Very low C : N ratio 1:2.5 Very low Extractable P 0.048 mg/kg-1 Low Exchangeable Cations Calcium 27.3 cmolc(+) kg-1 Very high Magnesium 186.6 cmolc(+) kg-1 Very high Potassium 2.16 cmolc(+) kg-1 High Sodium 5.4 cmolc(+) kg-1 Very high Micronutrients (mg/kg) Iron 31.7 mg/kg Very high Manganese 92.0 mg/kg Very high Cooper 13.0 mg/kg Very high Zinc 24.6 mg/kg Very high 1 According to Landon (1999 Crop quality Groundnut genotype significantly ( P=0.001) influenced 100- kernel weight with Masasi proving superior compared to the lowest as observed in Pendo. Whereas the application of P and Ca significantly (P=0.004) influenced 100- kernel weight Table 2. Crude protein (%CP) Results from the study revealed that groundnut genotypes had significant (P=0.001) effect on crude protein content. Pendo recorded 32.42% increase in crude protein content compared to Mangaka (28.50%) which differed significantly Table 2. Oil content (% Fat) Groundnut oil content as significantly (P=0.001) influenced by genotype and was recorded in the order of Pendo (44.24%), Masasi (43.38%) and Mangaka (41.42%). Whereas application fertilizer had no effect on oil content of groundnut Table 2. Genotype Factor (A) Kernel size (g) CP (%) Fat (%) Mangaka 47.23b* 28.50a 41.42a Masasi 76.60c 30.99b 43.38b Pendo 44.17a 32.42b 44.24c Mean 56.00 30.64 43.06 SE+ 1.05 0.77 0.10 CV(a) 1.9 22.4 11.6 P value (a) 0.001 0.001 0.001 Fertilizer Factor (B) Control 48.81a 30.55a 42.77a DAP 63.11c 30.47a 42.79a Minjingu Mazao 56.09b 30.90a 43.48b Mean 56.00 30.64 43.06 SE+ 0.66 0.77 0.10 CV(b) 1.2 6.1 3.25 P value (b) 0.001 0.835 0.001 Table 2: Influence of groundnut genotype and fertilizer on kernel size, protein, and oil content *Means in the same column and factor followed by the same letter are not significantly different according to Duncan Multiple Range P< 0.05 Table 3: Effect of Fertilizer Application and genotype on Yield and Profitability It was revealed from the study that the application of P made significant gain on yield,hence profitability as shown in Table 3. Table 3: Relative contribution of fertilizer type to groundnut kernel yield kg/ha net return and VCR VCR= Value cost ratio, Tsh = Tanzanian shillings; 1Fertilizer type, based on available sources of P and Ca 2Price based on the observed market price in the study area in USD ($), 3 Retail cost price charged for DAP and Minjingu mazao at local agricultural stores in 2015. 4Currency conversion was based on the banking exchange rate of US$1: 2000 Tanzanian Shillings s Treatment (Fertilizer type)1 Kernel yield (kg/ha) Average yield (kg/ha) Market price ($/kg)2 Gross income ($/kg) Fertilizer required (kg/ha) Fertilizer cost ($/kg)3 Total fertilizer cost ($/kg)4 Net income ($/ha) VCR Control 1327 0 1.63 2 163.0 0 0 0.00 2 163.0 0.00 DAP 1 760 433 1.63 2 868.9 55 16.36 900 1 968.9 2.2 Minjingu mazao 1 505 225 1.63 2 453.2 125 12.9 1612.5 840.7 0.5 Genotype x Fertilizer interaction : findings from the study showed significant interaction effect, with kernel weight of Masasi crude protein content of Mangaka and oil content of Pendo been influenced by Minjingu as shown in Table 4 SEQ Table \* ARABIC Table 4: Interaction effect of genotype and fertilizer type on kernel size, oil and protein contents Treatment effect Kernel weight (g) %Crude Protein %Fats Mangaka x control 46.50bcd 32.32c 43.18c Mangaka x DAP 46.80cd 40.50d 43.70d Mangaka x Minjingu mazao 48.40 d 40.60d 43.25cd Masasi x control 54.87e 28.80a 41.00 a Masasi x DAP Masasi x Minjingu mazao 98.45 g 76.47f 28.40a 28.30 a 40.90a 42.40 b Pendo x control Pendo x DAP Pendo x Minjingu mazao 43.15a 45.30abc 44.07ab 30.45 b 30.55 b 32.00 c 43.65d 44.15e 44.90f Mean SE + Cv (ab) % 56.0 1.71 3.1 32.43 0.45 1.45 43.01 0.30 0. 70 P- value 0.001 0.001 0.001 *Means in the same column and factor followed by the same letter are not significantly different at P ≤ 0.05 according to Duncan Multiple Range Test Discussion Soil Analysis:Soil analysis report from the study area revealed that the soil was sandy clay loam with a bulk density of 1.2g/cm3 which is considered an optimum bulk density for most crops (Lal and Shukla, 2004). Soil pH at the experimental site was 5.9, considered favourable for groundnuts (Murata, 2003). Nkot et al., 2011 reported poor groundnut nodulation and nitrogen fixation in acid soils of pH 3.6 -6.9. Low soil nitrogen content (0.18% T.N) at the experimental site was an indicator associated with the history of continuous cultivation with little or no addition of organic or inorganic fertilizers. Though not required in large quantities by legumes, soil available nitrogen is essential for vegetative growth as such, addition of nitrogen fertilizers at low rate as a starter dose to leguminous crops such as groundnut is necessary especially where soil nitrogen content is low (Tubbs et al., 2012). Kernel weight: Groundnut genotype and fertilizer had significant influence on kernel weight similar to findings by Alireza et al. (2012) who reported increased kernel weight with application of Ca (Table 2). Rezaul et al.,2013 reported that 50 and 110 kg/ha P and Ca, respectively had significant effect on crop quality and yield, increasing yield from 1000 to 3000 kg/ha. Significant genotype x fertilizer interaction was recorded with Masasi been significantly influenced by the application of P, which is validates findings by Kamara et al. (2011). Oil Content The study revealed significant influence of fertilizer and genotype on oil content of groundnut. Such findings are similar to findings made by Okello et al., 2010. The interaction effect of fertilizer x genotype observed that Pendo was significantly influenced by the application of Ca Protein Content: The result showed that fertilizer had no significant influence on protein content while significant effect of groundnut on protein content was observed in Pendo Table 2. The finding is contrary to findings from studies results by other researchers showing that fertilizer application increased the protein content of groundnut as observed by (Kamara et al., 2011; Madhan and Nigam 2013;Tarawali and Quee, 2014). Genotype x fertilizer observed from the study showed significant interaction effect of fertilizer on Mangaka with the application of Ca Table 4; which is in contrary to findings by Tarawali and Quee, 2014 who reported significant interaction effect of groundnut varieties and phosphorus. Profitability: VCR analysis was conducted focusing on the extra benefit derived from application of DAP and Minjingu mazao as sources of P and Ca respectively. Crop requirement for Ca and the cost of meeting crop nutrient demand outweighed the cost of 55 kg P/ha from DAP as the cost of P from DAP almost doubled the cost of Ca from Minjingu mazao (Table 3). Similarly, gross return and VCR increased with application of DAP whereas application of Minjingu mazao resulted into a lower gross return and VCR of $2 453.2and 0.5, respectively similar to findings by (Taruvinga, 2014). Conclusion: Plant nutrient availability is strongly affected by fertility status of the soil and it determines the quantity of nutrients to be supplied for optimum yield. Crop quality, including kernel size and oil content of all groundnut genotypes responded to fertilizer, crude protein content was not affected by application of either Ca or However genotype x fertilizer interaction showed the response of all genotype. Profitability of fertilizer use was heavily dependent on the application of P as it affected kernel yield and subsequently proved to be a limitation to groundnut profitability in the study area. Masasi and Pendo proved to show performance superiority. Recommendations: Treatment combination of both Ca and P at different rates/ratios could set the basis for evaluating and recommendation of genotype with high protein and oil contents as well as optimum fertilizer rates for enhanced productivity and profitability. References Acland, J. D. (1971). Groundnuts East African Crops. Food and Agriculture Organization, Rome, Italy. 133pp Adinya, I. B., Enun, E. E. and Ijoma, J. U. (2010). Exploring profitability potentials in groundnut production through agroforestry practices: a case study in Nigeria. Journal of Animal and Plant Sciences 20(2): 123 – 131. AOAC (1990). Association of Official Analytical Chemists Inc. Official Methods of analysis. (15th Edition). Washington DC. 1298pp. Bhatti, A. U. (2006). Statistical Procedures for Analysis of Agriculture Research Experiments. Department of Soil and Environmental Sciences, University Peshawar, Pakistan. 115pp. Bremner, J. M. and Mulvaney, C. S. (1982). Total nitrogen. In: Methods of Soil Analysis Part 2. Chemical and Microbiological Properties. (Edited by Page, A. L., Miller. R. H. and Keeney, D. R.), American Society of Agronomy and soil Science of America, Madison, Wisconsin. pp. 593 – 624. Caliskan, S., Caliskan, M. E., Arsian, M. and Arioglu, H. (2008). Effects of sowing date and growth duration in Mediterranean type environment in Turkey. Field Crops Research 15(2): 131 – 140. 62. FAOSTAT (2013). Database in crop production.[http:// faostat.fao.org/site/567/ DesktopDefau laspx?PageID=567#ancor] site visited on 5/08/2015. Gomez, A. K. and Gomez, A. A. (1984). Statistical Procedure for Agricultural Research. John Wiley and Sons, Inc., London. 680pp. Kamara, A. Y., Ekeleme, F., Kwari, J. D., Omoigui, L. O. and Chikoye, D. (2011). Phosphorus effect on growth and yield of groundnut varieties in the tropical savanna of North Eastern Nigeria. Journal of Tropical Africa 49(2): 24 – 30. Kamara, E. G., Olympio, N. S and Asibuo, J. Y. (2011). Effect of calcium and phosphorus on the growth and yield of groundnut (Arachis hypogaea L.). International Research Journal of Agricultural Science and Soil Science 1(8): 326 – 331. Kanyeka, E., Kamala, R. and Kasuga, R. (2007). Improved Agricultural Technologies in Tanzania. Ministry of Agriculture Food Security and Cooperatives, Dar es Salaam, Tanzania. 125pp. Lal, R. and Shukla, M. K. (2004). Principles of Soil Physics. The Ohio State University Columbus, Ohio, USA. 699pp. Landon, J. R. (1991). Booker Tropical Soil Manual. A Hand Book for Soil Survey and Agricultural Land Evaluation In The Tropics And Sub Tropics. Longman Publishers, New York. 474pp. Madhan, M. M. and Nigam, S. N. (2013). Principles and Practices for Groundnut Seed Production in India. Information Bulletin No. 94. International Crops Research Institute for the Semi-Arid Tropics, Andhra Pradesh, India. 64pp. Murata, M. R. (2003). The impact of soil acidity amelioration on groundnut production on sandy soils of Zimbabwe. Thesis for Award of PhD Degree at University of Pretoria, South Africa, 229pp. Nkot, L., Nwaga, D., Ngakou, A., Fankem, H. and Etoa, F. (2011). Variation in nodulation and growth of groundnut (Arachis hypogaea L.) on oxisols from land use systems of the humid forest zone in southern Cameroon. African Journal of Biotechnology 10(20): 3996 – 4004. Okello, D. K., Biruma, M. and Deom, C. M. (2010). Overview of groundnuts research in Uganda: Past, present and future. African Journal of Biotechnology 9(39): 6448 – 6459. 271pp. Pande, S. and Narayana, R. J. (2002). Effect of plant population densities on the severity of late leaf spot and rust of groundnut. Journal of Plant Pathology 18(5): 217 – 278. Papanastassiou, N.J. (2012). Crop-Environment Interactions in Sub-Saharan Africa. Environmental Policy Update 2012: Development Strategies and Environmental Policy in East Africa. Pp.42. Semoka, J. R. M. (2003). Research Report for Progress Rock Phosphate Project. Sokoine University of Agriculture, Morogoro, Tanzania. 24pp. Sorrensen, R., Butts, C., Lamb, M. and Rowland, D. (2004). Five Years of Subsurface Drip Irrigation on Peanut. Research and Extension Bulletin No. 2004. Tarawali, A. and Quee, D. (2014). Performance of groundnut varieties in two agro-ecologies in Sierra Leone. African Journal of Agricultural Research 9(19): 1442 – 1448. Taruvinga, B. (2014). Nutritional and soil fertility benefits: influence of fertilizers on groundnuts (Arachis hypogaea L.) yield and soil nitrogen contribution for smallholder farmers in Uganda. Dissertation for Award of MSc Degree at Wageningen University, Netherlands, 81pp. Tubbs, R. S., Harris, G. S., Smith, N. B. (2012). Effect of inoculation and nitrogen application at planting on peanut production in Georgia. [http:/scien cesocieties.org/publications/ cm/abstract] site visited on 4/11/2015.