EGOS MSc Thesis February 02 2024

RESPONSE OF SWEET CORN (Zea mays L. var. saccharata) TO THE COMBINED APPLICATION OF ORGANIC AND INORGANIC FERTILIZERS UNDER DIFFERENT METHODS OF CROP ESTABLISHMENT ARMAN QUIRAN EGOS A THESIS OUTLINE SUBMITTED TO THE FACULTY OF THE GRADUATE SCHOOL VISAYAS STATE UNIVERSITY, VISCA, BAYBAY CITY, LEYTE IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE (Agronomy) FEBRUARY 2024 CHAPTER I INTRODUCTION Nature and Importance of the Study Sweet corn (Zea mays L. var. saccharata) is a widely popular crop with the same morphological characteristics and cultivation methods as other corn varieties (Gavric & Omerbegovic 2021). Crop establishment method and fertilizer application are fundamental management strategies that significantly augment the yield of sweet corn cultivation (Tampus & Escasinas 2019). In the Philippines, the conventional method of cultivating sweet corn is direct seeding. Rattin et al (2010) demonstrates that transplanting produces yields comparable to direct seeding. Likewise, transplanting method serves as a widely employed strategy in cultivating crops when direct seeding becomes challenging due to unfavorable conditions, particularly where the presence of birds poses a risk to emerging seedlings (Fanadzo et al 2009). FAO (2003) reported that maize transplanting is predominantly practiced in Korea. Fanadzo et al (2009) reported that transplanting of corn resulted in a significantly higher crop stand of 96% compared to direct seeding, which achieved 78%. In addition, transplanting corn can shortened growth duration in the field, reaching flowering stage 11 to 15 days earlier than direct seeded. Vermicompost is a type of solid organic fertilizer generated by composting organic materials with the aid of diverse earthworm species (Ramnarain et al 2009). Piya et al (2018) reported that the utilization of vermicompost resulted in favorable effects on soil quality, plant growth, and crop yields while also enhancing the nutritional 2 value of crops. The utilization of vermicompost in potato (Solanum tuberosum L.) crop at a rate of 10 ha-1 demonstrated comparable efficacy to that of 15, 20, and 25 tons ha 1 of application (Fahrurrozi et al 2019). According to Villaver (2020), sweet corn yields treated solely with vermicompost were not comparable to their treated with inorganic fertilizer. Hence, Shahid et al (2015) emphasized the significance of integrated nutrient management in sweet corn cultivation suggested a balanced application of organic and inorganic fertilizers. Studies indicated that combining organic and inorganic fertilizers produced a higher yield in sweet corn (Zhang et al 2016), however, the effect of vermicompost with inorganic fertilizer to provide maximum productivity on sweet corn has yet to be fully understood, especially under Eastern Visayas conditions. Hence, the conduct of this research undertaking. Objectives of the Study This study aims to: 1. Determine the effect of the combined application of vermicompost and inorganic fertilizers on the growth and yield of sweet corn; 2. Evaluate the performance of sweet corn to combined application of organic and inorganic fertilizers under different crop establishment methods; 3. Determine the amount of organic and inorganic fertilizer applications for maximizing the growth and yield of sweet corn under the methods of crop establishment; 4. Assess the profitability of sweet corn production with combined application of organic and inorganic fertilizers under different methods of crop establishment. 3 Time and Place of the Study This research will be conducted at the Department of Agronomy, Visayas State University (VSU), Visca, Baybay City, Leyte, Philippines from ___________ to ___________. CHAPTER II REVIEW OF LITERATURE Production of Sweet Corn in the Philippines Sweet corn is widely grown in the Philippines due to its high demand in both domestic and international markets. The country's sweet corn production is concentrated in the Central Luzon, Southern Tagalog, and Bicol regions, which account for more than 70% of total production (Rillo 2020). According to the Philippine Statistics Authority (PSA), the country's sweet corn production in 2020 is expected to be 336.18 thousand metric tons, a 7.6% increase over the previous year (PSA 2021). According to Zarraga et al (2019), farmers in the Bicol region, one of the top sweet corn-producing regions in the country, faced challenges in sweet corn production due to the prevalence of pests and diseases. The study suggested using integrated pest management (IPM) practices to reduce the impact of these factors. Current Production of Sweet Corn in the Philippines According to the Philippine Statistics Authority (PSA), yellow corn production, which includes sweet corn, reached 1.47 million metric tons in the second quarter of 2022, representing a 10.9 percent increase over the same period last year, 2021 (PSA 2022). According to the Department of Agriculture (DA), sweet corn production in the Philippines increased by 16.4 percent in the first quarter of 2022 compared to the same period in 2021 (Department of Agriculture 2022). The DA also stated that sweet corn is one of the country's high-value crops due to rising demand from both domestic and export markets. 5 Methods of Crop Establishment of Sweet Corn The two most common methods for establishing sweet corn in the field are direct seeding and transplanting. Soil type, climate, and resource availability (labor and equipment) determine the method to choose. In areas with warm soils and adequate moisture, direct seeding sweet corn is a standard method of planting. This method involves sowing them directly into the field. Direct seeding is generally faster than transplanting since plants are not subjected to stress and requires less labor and equipment. Direct seeding, on the other hand, has some potential drawbacks. Lower germination rates, for example, can be caused by soil crusting, seedling diseases, and insect damage. Furthermore, direct seeding can result in uneven emergence and eventually plant spacing thus lowering yields. Direct seeding sweet corn yielded higher than transplanting (Muhammad et al 2016). As direct seeding had lower seedling mortality rates and lower labor requirements compared to transplanting. Transplanting sweet corn entails raising seedlings in a nursery and then planting them into the field when they are a few weeks old. This method is most commonly used in areas with cool soil temperatures or when planting is postponed due to weather. Transplanting resulting in more uniform crop growth and higher yields. However, it is more time-consuming and labor-intensive. It also increase the risk of seedling shock and damage in transplanting operation. Nevertheless, Sharma and Singh (2019), transplanting sweet corn resulted in significantly higher yields at about 17.66 tons ha-1 than direct seeding. They also found that transplanting resulted in more uniform plant growth and better weed control. In general, the choice of method in establishing sweet corn depends on soil type, climate, and availability of resources. While direct seeding 6 may be faster since seedlings are not subjected to stress and require less labor and equipment, transplanting may result in more uniform crop growth and higher yields. Organic Sweet Corn Production in the Philippines There is limited research on organic sweet corn production in the Philippines, but there are studies on organic agriculture in general and sweet corn production in the country. Sibayan et al (2015) found that organic agriculture is gaining popularity in the Philippines due to increasing awareness of the negative impacts of conventional agriculture on the environment and human health. However, organic agriculture still needs help, such as a lack of market access and limited government support. De Leon et al (2018) stipulated that sweet corn is one of the major vegetable crops produced in the Philippines. The study found a high demand for sweet corn in the local and export markets. Banayo et al (2018), highlighted the importance of using organic inputs such as compost and vermicast in sweet corn production to improve soil fertility and crop yield. The authors emphasized integrated pest management practices in organic sweet corn production to control pests and diseases. Moreover, Reyes et al (2017) state that there is a growing market for organic produce in the Philippines, particularly in urban areas. The authors suggested that organic sweet corn production could be profitable for smallholder farmers if they have access to markets that value organic produce. Combined Application of Organic and Inorganic Fertilizers in Sweet Corn Sweet corn is an important crop grown worldwide for its sweet and succulent kernels. Farmers often apply fertilizers to the soil to achieve high yields to enhance plant growth and development. In recent years, there has been a growing interest in combining organic and inorganic fertilizers to improve soil health and crop 7 productivity. Studies on combining organic and inorganic fertilizers in sweet corn production significantly increased yield at about 29% and 23% respectively (Fahrurrozi et al 2021). Regarding soil health, Zhou et al (2022) discovered that combining organic and inorganic fertilizers improved soil microbial biomass, enzyme activity, and soil organic matter content at about 54.7% to 110.6% than to using only organic or inorganic fertilizers. Similarly, Mi et al (2018) reported that combining organic and inorganic fertilizers improved soil chemical properties such as higher soil pH (0.16–0.29 units), cation exchange capacity (CEC) (17.4–21.9%), and lower exchangeable acidity and Al3+ concentrations at soil depths of 0–20 cm. Organic Fertilizer Organic fertilizer is a combination of natural materials such as animal manure, plant residues, and other organic materials like household garbage. It is becoming more popular because it improve soil quality, increased plant growth, and reduced pollution. Meena et al (2017) reported that organic fertilizers improve soil structure, microbial activity, and nutrient availability. In addition, compost and manure increased available water content of soils by 86 and 56%, respectively (Celik et al 2004). Khaliq et al (2018) found that organic fertilizers significantly improved maize growth and yield. Liu et al (2018) also found that organic fertilizers can improve soil quality, reduce fertilizer runoff, and reduce greenhouse gas emissions. Benefits of Organic Fertilizer Natural materials such as animal manure, plant-based materials, and compost are used to make organic fertilizers. They have grown in popularity among farmers and 8 gardeners due to their potential benefits for soil health, plant growth, and environmental sustainability. Organic fertilizers slowly and steadily release nutrients, providing plants with a consistent source of nutrients. According to Zhang et al (2018), organic fertilizers have higher nutrient availability and lower nutrient losses than chemical fertilizers. Mockeviciene et al (2022) found that organic fertilizers improve soil health by increasing organic matter at about 0.1–0.4%, improving soil structure, and promoting beneficial microorganisms. According to Zaller (2018), organic fertilizers significantly improved soil quality and nutrient cycling. Organic fertilizers can improve soil fertility and nutrient uptake of N, P, and K at about 36.1, 129.0, and 65.20% when applied with 6.5 tons-1 of farm yard manure and increasing plant growth and yield (Chand et al 2006). According to a study by Efthimiadou et al (2009), organic fertilizers increase crop yield at about 1593 kg ha-1 - 6104 kg ha-1 and increase soil fertility. These organic fertilizers are environmentally friendly because they are derived from natural sources and do not contain synthetic chemicals. According to a review by Pimentel et al (2005), organic farming can mitigate the adverse effects of conventional farming on soil, water, and biodiversity by improving soil health with the use of natural methods to enhance soil fertility and control pests. However, according to Canali et al (2010), slow-release organic fertilizers provide nutrients in a balanced manner, which is critical for plant growth and development. Vermicompost as Organic Fertilizer Vermicomposting is derived when earthworms convert organic waste into vermicompost, a nutrient-rich fertilizer. Vermicompost contains more nitrogen, 9 phosphorus, potassium, and calcium (Atiyeh et al 2002; Ndegwa & Thompson 2001) than traditional compost. The high nutrient content is attributed to the digestive process of earthworms, which breaks down organic matter into more available and plantfriendly forms. Studies have shown that vermicompost can improve plant growth and yield. Pandey et al (2015) found that vermicompost increased the growth and yield of tomato plants. Vermicompost can improved the growth and yield of black grams (Bhat et al 2020). Furthermore, vermicomposting has been discovered to enhance soil health by augmenting soil organic matter, enhancing soil structure, and stimulating favorable microbial activity (Singh et al 2014; Yadav et al 2017). These improvements can help reduce soil erosion, increase water-holding capacity, and promote soil fertility. Vermicompost has also been found to can suppress soil-borne diseases such as root rot, damping-off, and fusarium wilt (Edwards & Arancon 2004; Zaller 2006). And also deter aphids, mites, and thrips (Atiyeh et al 2000; Subler et al 1998). Vermicompost typically contains higher micronutrients such as zinc and copper (Atiyeh et al 2002; Edwards & Arancon 2004) than traditional. The nutrient content of vermicompost however vary depending on the type of feedstock used, the worm species, and the prevailing conditions (Gajalakshmi & Abbasi 2008; Tomati et al 2008). In addition to nutrients, vermicompost contains beneficial microorganisms such as bacteria, fungi, and actinomycetes, which can help to suppress plant diseases and improve soil health (Nogales et al 2010; Pandey & Sati 2016). CHAPTER III MATERIALS AND METHODS Study Site This research will be conducted at the experimental area of the Department of Agronomy, Visayas State University (VSU), geographically located at 100 45’ N and 1240 47’37” E, in Visca, Baybay City Leyte, Philippines. According to the most recent climate data provided by the Philippine Atmospheric, Geophysical and Astronomical Services Administration (PAG-ASA), Visayas State University has been classified as Type IV corona climate classification, which suggests that the region does not undergo a clearly defined dry season and instead experiences relatively uniform precipitation levels throughout the year. Land Preparation The experimental area of 1,331.25 m2 will be cleared of weeds before planting. The field will be plowed twice in one-week intervals to allow the weed seeds to germinate and the residues to rot. Harrowing will be done twice every after plowing to pulverize and level the soil. Furrows will be set 75 cm apart. Soil Analysis Ten soil samples will be randomly collected from the entire experimental area at 0-20 cm depth before set up of the experiment (Smith & Johnson 2010). These will be composited, air-dried, and sieved using 2.0-mm wire mesh. These will be submitted to the Central Analytical Service Laboratory (CASL), Philippine Root Crops Research 11 Center (PhilRootcrops), Visayas State University, Visca, Baybay City, Leyte for the determination of soil pH, organic matter (%) (Modified Walkley-Black Method; PCARR 1980), total N (%) (Modified Kjeldahl Method, PCARR 1980), available phosphorus (Modified Olsen Method, Olsen, and Sommer 1982) and exchangeable potassium content (Ammonium Acetate Method, PCARR 1980). After harvest, soil samples will be gathered for final analysis. Samples will be collected per treatment plot at 0-20 cm depth samples from the three (3) replications will be composited to determine the same soil parameters mentioned above. Experimental Design and Treatments The experiment will be laid out in a split plot with three replications arranged in a Randomized Complete Block Design (RCBD). Treatments will be designated as follows: Main Plot – Methods of Crop Establishment M1 – Direct seeding method M2 – Transplanting method Sub-plot – Integrated Fertilizer Management T0 - No fertilizer application (control) T1 - 90-60-60 kg ha-1 N, P2O5, K2O (Inorganic fertilizer) T2 - 10 t ha-1 of Vermicompost T3 - 67.5-45-45 kg ha-1 N, P2O5, K2O + 2.5 t ha -1 of Vermicompost T4 - 45-30-30 kg ha-1 N, P2O5, K2O + 5 t ha-1 Vermicompost T5 - 22.5-15-15 kg ha-1 N, P2O5, K2O + 7.5 t ha -1 of Vermicompost 12 Each replication consists of twelve (12) treatment combinations, and each treatment plot measures 5 m x 4.5 m (Appendix Fig. 1). There will be 36 plots in the experiment. An alleyway of 2 meters will be provided between replications and 1.5 meters between treatment plots to facilitate farm operations and data gathering. Fertilizer Application The different rates of organic fertilizer will be applied in designated plots uniformly in the furrows two (2) weeks before planting (WBP). On the other hand, different rates of complete fertilizer (14-14-14) will be sidedressed ten (10) days after planting (DAP). Moreover, various rates of Urea (46-0-0) will also be sidedressed thirty (30) days after planting (DAP) using the side-dressed method. The actual amount of organic and inorganic fertilizers applied per plot is indicated in Table 1. 13 Table 1. Amount of organic and inorganic fertilizers applied per plot SUBPLOT TREATMENTS VERMICOMPOST (kg plot-1) COMPLETE 1414-14 (kg plot-1) UREA 46-0-0 (kg plot-1) T0 – No fertilizer application (control) 0 0 0 0 0.96 0.15 22.50 0 0 5.63 0.72 0.11 11.25 0.48 0.073 16.87 0.24 0.037 T1 - 90-60-60 kg ha-1 N, P2O5, K2O Inorganic fertilizer T2 - 10 t Vermicompost ha-1 of T3 - 67.7-45-45 kg ha-1 N, P2O5, K2O + 2.5 t ha -1 of Vermicompost T4 - 45-30-30 kg ha-1 N, P2O5, K2O + 5 t ha-1 Vermicompost T5 - 22.5-15-15 kg ha-1 N, P2O5, K2O + 7.5 t ha -1 of Vermicompost Sweetcorn Variety and its Characteristics Macho F1 will be the sweet corn variety used in this study. This variety produced long cylindrical ears with 14-18 kernel rows and well-filled tips. Its green husk made it appear more appealing to buyers. This cultivar is not seasonal. Economically, it is a high-yielding hybrid with broad market potential due to its suitability for fresh and processed markets. According to a study conducted by Asebedo et al (2019), the Macho F1 variety of sweet corn had a higher yield than other varieties tested. The study found that the Macho F1 variety had an average yield of 22.50 tons per acre, significantly higher than 19.60 tons per acre for other varieties. Furthermore, Foyer et al (2015) 14 stated that the Macho F1 variety of sweet corn was found to have high-quality ears with large, uniform, and well-filled kernels. The study also found that the Macho F1 variety had a high percentage of marketable ears, which is vital for commercial growers. Moreover, Gauthier et al (2017) stated that the Macho F1 variety showed a high resistance to pests and diseases, which can help reduce the need for chemical treatments. Furthermore, Wang et al (2019), stated that the Macho F1 variety had a higher sugar content than other sweet corn varieties tested, which can contribute to its popularity among consumers. Seedling Establishment For the transplanting method of sweet corn, seeds will be sown in standard seedling tray with a dimension of 54 cm x 28 cm with 128 cells. The soil media will be compost and field soil with a ratio of 2:1 (Dhananchezhiyan et al 2013). The seedling trays will be placed beside the experimental area. Moreover, daily monitoring will be done to assess the seedling's progress, and watering will be employed. Planting and thinning In the transplanting method, seeds will be sown in seedling trays and will be transplanted in the field seven days after, and planting will be done at the rate of one seedling per hill with a distance of 75 cm x 25 cm. On the otherhand, for the direct seeding method, seeds will be sown in the furrow on the same day seeds were sown in seedling tray for the transplanting method. The rate will be 2 seeds per hill, with a distance of 75 cm between rows and 25 cm between hills. Thinning will be done 15 days after planting, leaving only one plant per hill with the desired population of 53,333 plants-1. Replanting will be done for the missing hill one week after planting. 15 Cultivation and Maintenance Management Off-barring will done 20 days after planting (DAP) using carabao-drawn implement. Hilling up will be implemented approximately thirty (30) days after planting to conceal the side dressed fertilizer. Hand weeding will be implemented on the 7th, 21st, and 35th days after planting (DAP). Drainage canal will be established both around the experimental area and between replications to prevent waterlogging during periods of heavy precipitation. Control of insect pests and diseases will be done by biweekly application of Panyawan (Tinosphora rumphii B.) botanical pesticide, commencing at the V3 stage of the vegetative phase until the ear formation stage. Regular monitoring of the experiment will be conducted to evaluate the occurrence of insect pest infestations, specifically corn stem borers. Harvesting Sweet corn will be harvested at the green cob stage when 80% of the crop population has reached the R4 stage or when the dough grain has formed and the kernel interior resembles dough. Corn silks at this stage also dry out, as evidenced by their senesced brown color. All sample plants from the harvestable area will be taken excluding the end hills of each row and one row from each side. Data to be Gathered A. Agronomic characteristics 1. Number of days from planting to the tasselling stage - This will be determined by counting the number of days from planting to when 80% of the population in the plot has tasseled. 16 2. Number of days from planting to the silking stage - This will be measured by counting the days from planting until 80% of the crop population reaches the silking stage. 3. Number of days from planting to green cob stage - This will be measured by counting the days from planting until 80% of the crop population has reached the green cob stage. 4. Plant height (cm) - This will be determined by measuring the ten sample plants randomly selected in each plot from ground level to the tip of the highest plant part with a meter stick. This will be done biweekly, beginning fourteen (14) days after planting, to closely monitor crop growth and development. 5. Fresh Stover Yield (t ha-1) - This will be determined by weighing the stalks of corn plants from the harvestable area in each treatment plot within the four inner rows after removing the ears. Stover Yield (kg) Stover Yield (t ha ) = -----------------------------------Harvestable Area (13.5 m2) -1 x 10,000 m2 ha-1 -------------------1,000 kg t-1 B. Physiological parameters 1. Leaf area index - In each treatment plot, ten sample plants will be chosen at random. During the R1 stage or approximately 55 days after planting (DAP) where corn already consists of eight or more fully-expanded leaves, LAI will be computed by measuring using the number of eight leaf lengths and the maximum width of the crop. The width will be measured at the leaf's broadest part, while the length will be measured from the base to the tip. And the leaf area index will be calculated using the formula below: 17 Length × width × 0.75 × 9.39 LAI = ------------------------------------------The ground area allotted per plant where: 9.39 - correction factor for the eighth leaf L - Length of leaf no. 8 W - Width of leaf no. 8 measured at the broadest part. C. Yield and yield components 1. Number of ears plant-1 - This will be determined by counting the developed ears of ten sample plants within the harvestable area of each treatment plot. 2. Ear length (cm) - This will be determined by measuring ten sample ears from base to tip using a ruler at harvest. 3. Ear diameter (cm) - This will be determined by measuring the diameter of the most considerable portion of each ear (ten sample ears per plot) using a vernier caliper. 4. Number of kernel rows - This will be determined by counting the number of kernel rows per ear of the ten sample ears. 5. Number of marketable ears plot-1 - This will be obtained by counting the dehusked marketable ears within the harvestable area in each treatment plot. This will be calculated using the formula: No. of marketable ears No. of marketable ears (plot-1) = ------------------------------- x No. of hills (72) No. of hills harvested 6. Number of non-marketable ears plot-1 - This will be obtained by counting those dehusked ears that did not qualify as marketable in each treatment plot. 18 7. Weight of marketable ears (t ha-1) - This will be obtained by weighing the dehusked marketable ears within the harvestable area in each treatment plot. The weight of marketable ears in kilogram ha-1 will be converted using the formula: Weight of marketable ears (kg/plot-1) 10,000 m2 Wt. of marketable ears (t ha ) = --------------------------------------------- x -------------Harvestable area (13.5 m2) 1,000 kg ha-1 -1 8. Weight of non-marketable ears (t ha-1) - This will be the weight obtained from those not classified as marketable ears from each treatment plot at harvest. This will be calculated using the same formula used to calculate the weight of marketable ears. 9. Total ear yield (t ha-1) - The weights of marketable and non-marketable ears (t ha-1) will be summed up to obtain the total yield. The total ear yield (t ha-1) will then be converted using the formula below: Weight of total ear yield (kg/plot -1) 10,000 m2 Yield (t ha ) = --------------------------------------------- x ---------------------Harvestable area (13.5 m2) 1,000 kg ha-1 -1 D. Insect Pest and Diseases Incidence - incidence of pests and diseases will be determined by adopting the following rating scale on the degree of damage or infestation (CIMMYT 1989): 0- No damage 1- Few pin holes 2- Few shot holes on a few leaves 3- Several shot holes on leaves (<50%) 4- Several shot holes on leaves (>50%) or small lesions (< 2cm long) 5- Elongated lesions (>2 cm long) on a few leaves 6- Elongated lesions on several leaves 19 7- Several leaves with long lesions with leaf tattering 8- Several leaves with long lesions with severe leaf tattering 9- Plant dying due to death of growing points (dead-hearts) E. Harvest Index is the ratio of a crop's economic yield and biological yield. The dehusked ears and herbage of three sample plants from each treatment plot will be weighed separately to obtain the harvest index using the formula below: Economic yield Fresh green cob yield (dehusked) Harvest Index = ------------------------ = -------------------------------------------------------Biological yield Fresh herbage plus green cob yield (dehusked) F. Measurement of N uptake. After harvesting the ear for every treatment, the representative samples from leaves will be taken separately from each treatment and analyzed for N uptake. Nitrogen (%) will be measured using the Kjeldahl method (Nelson & Sommers 1973). In addition, nutrient uptake (kg/ha) of sweet corn will be calculated using the formula: N uptake (kg/ha) = Nutrient concentration (%) x oven dry weight (ODW) of leaves G. Initial Soil Physicochemical Properties 1. Electrical Conductivity (EC) - This will be estimated by an EC meter, maintaining the ratio of soil to water of 1:5. Then, the result will be converted to the ratio of 1:1 (soil: water) (USDA 2004). 2. Soil pH - This will be measured using a pH meter, maintaining a ratio of soil to water 1:2.5 (FAO 2021). 3. Organic Carbon - This will be determined by Walkley Black’s Wet Oxidation method (FAO 2019). 20 4. Organic Matter - This will be calculated by multiplying the percent value of organic carbon with the conventional Van-Bemmelene factor of 1.724 (Heaton et al 2016). 5. Cation Exchange Capacity (CEC) - This will be determined by extracting the soil with neutral ammonium acetate solution (NH4OAc, pH-7) by replacing the ammonium in the exchange complex with a 1N KCl solution, and the result will be recorded by the flame photometric method (Miller et al 2017). 6. Total Nitrogen – This will be determined following the Kjeldahl digestion procedure (Bremner & Mulvaney 1982). 7. Available Phosphorus – This will be colorimetrically determined by the Bray II method (Olsen & Sommers 1982). 8. Exchangeable Potassium – This will be determined by Ammonium Acetate Extraction Method (PCARR 1980). H. Meteorological Data Total weekly rainfall (mm), average daily minimum and maximum temperatures (0C), and relative humidity (%) throughout the conduct of the study will be taken from the records of the Philippine Atmospheric Geophysical and Astronomical Services (PAGASA) Station, Visayas State University, Visca, Baybay City, Leyte. 21 I. Statistical Analysis The data collected will be consolidated and means will be statistically analyzed using Statistical Tool for Agricultural Research (STAR) version 2.0.1 2014, Biometrics and Breeding Informatics, Plant Breeding Genetics and Biotechnology Division, International Rice Research Institute, Los Baños, Laguna (IRRI 2014). Treatment means comparison will be done using the Tukey’s or Honestly Significant Difference (HSD) test. J. Marginal Cost and Return Analysis The variable cost will be determined by recording all the expenses incurred throughout the study, from land preparation to harvesting. These include fertilizers, materials, and labor that were used in the conduct of the experiment. The total variable cost (material, labor, etc.) will be subtracted from the gross margin to obtain the net margin. The gross margin will be determined by multiplying the marketable ear yield of each treatment plot by the current market price of corn per kilogram. The gross margin, net margin, and return on investment will be determined using the following formula: Gross Margin = Total marketable ear yield (t ha-1) x current market price per kilogram Net Margin = Gross Margin – Total Variable Cost Net Margin ROI = ------------------------------ x 100 Cost of Investment LITERATURE CITED Asebedo JR, Dhakal K, Ramasamy P, Schapaugh WT & Thapa RB. 2019. Evaluation of sweet corn varieties for yield and quality in Kansas. 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Frontiers in Environmental Science, 10, 2292 8 APPENDICES 9 REP 1 REP 2 REP 3 M2 M1 M1 M2 M1 M2 R1M2T1 R1M1T0 R2M1T2 R2M2T2 R3M1T2 R3M2T2 R1M2T3 R1M1T2 R2M1T1 R2M2T1 R3M1T0 R3M2T5 R1M2T5 R1M1T3 R2M1T4 R2M2T5 R3M1T3 R3M2T4 37.5m 5m R1M2T4 R1M1T5 R2M1T0 R2M2T4 R3M1T1 R3M2T0 R1M2T2 R1M1T4 R2M1T3 R2M2T0 R3M1T5 R3M2T1 R1M2T0 R1M1T1 R2M1T5 R2M2T3 R3M1T4 R3M2T3 4.5m 1.5m 2m 35.5m Total Area: 1,331.25 m2 Appendix Figure 1. Field Layout in Split Plot in RCBD with three replications Total Area of the Field = LW = 37.5 m X 35.5 m = 1,331.25 m2 Plot Area = 5 m x 4.50 m = 22.5 m2 Distance between replications = 2 m Distance between treatments = 1.5 m 10 4.5m 0.25m 3m 0.75m 4.5m 4.5m 0.75m 5m Harvestable Area 13.5 m2 3m 0.25m Appendix Figure 2. Schematic presentation of the harvestable area Calculations of total plot and harvestable area and their plant population Plot Area = L X W = 5 m X 4.5 m = 22.5 m2 Length: Width: = 5 m / 0.25 m = 4.5 m / 0.75 m = 20 hills = 6 rows 11 Plant Population Plot -1 with borders = Hills X Rows = 20 X 6 = 120, or Area 22.5 m2 Plant population plot = -------------------------- = ----------------- = 120 hills Planting distance 0.1875 m2 -1 Harvestable Area per Plot = L X W = 4.5 m X 3 m = 13.5 m2 Length: Width: = 4.5 m / 0.25 m = 3 m / 0.75 m = 18 hills = 4 rows Plant Population per Harvestable Area = Hills X Rows = 18 X 4 = 72, or Area 13.5 m2 Plant population harvestable area -1 = -------------------------- = ----------------- = 72 hills Planting distance 0.1875 m2 Border Plants per Plot = Excluded (2) end hill per rows + Excluded (2) end rows = (2 X 6) + (20 – 2) (2) = 12 + 18 (2) = 48 plants Plants for Destructive Sampling = 4 inner rows X 18 hills = 72 plants 12 Appendix Table 1. Amount of fertilizer applied per treatment (kg plot-1) Treatments T0 – Control (No fertilizer applied) Amount of fertilizers (kg/plot-1) No Application T1 – 90-60-60 kg ha-1 N, P2O5, K2O 0.96 kg of complete fertilizer [will be sidedressed 10 days after planting (DAP)] + 0.15 kg of Urea (will be sidedressed 30 DAP) T2– 10 tons/ha of vermicompost 22.50 kilograms of vermicompost will be applied [2 weeks before planting (WBP)] 0.72 kg of complete fertilizer [will be sidedressed 10 days after planting (DAP)] + 0.11 kg of Urea (will be sidedressed 30 DAP) + 5.63 kilograms of vermicompost will be applied [2 weeks before planting (WBP)] 0.48 kg of complete fertilizer [will be sidedressed 10 days after planting (DAP)] + 0.073 kg of Urea (will be sidedressed 30 DAP) + 11.25 kilograms of vermicompost will be applied (2 WBP) 0.24 kg of complete fertilizer [will be sidedressed 10 days after planting (DAP)] + 0.037 kg of Urea (will be sidedressed 30 DAP) + 16.68 kilograms of vermicompost will be applied [2 weeks before planting (WBP)] T3 – 67.5-45-45 kg ha-1 N, P2O5, K2O + 2.5 tons/ha of vermicompost T4 – 45-30-30 kg ha-1 N, P2O5, K2O + 5 tons/ha of vermicompost T5 – 22.5-15-15 kg ha-1 N, P2O5, K2O + 7.5 tons/ha of vermicompost Fertilizer Computation: Treatment 1: 90-60-60 kg/ha N, P2O5, K2O 60 kg Amount of Complete fertilizer (14 -14 -14) = -------------- X 100 = 428.57 kg/ha 14 428.57 kg X 22.5 m2/plot ------------------------------------ = 0.96 kg/plot 10,000 m2 90 – 60 – 60 - 60 – 60 – 60 ---------------30 – 0 – 0 13 30 kg Amount of Urea (46-0-0) = -----------X 100 = 65.22 kg/ha 46 65.22 kg X 22.5 m2/plot ---------------------------------- = 0.15 kg/plot 10,000 m2 ------------------------------------------------------------------------------------------------------Treatment 2: 10 tons/ha of vermicompost 10,000 kg Amount of vermicompost = ------------------- x 22.5 = 22.50 kg 10,000 m2 ------------------------------------------------------------------------------------------------------Treatment 3: 67.6-45-45 kg/ha N, P2O5, K2O + 2.5 tons/ha of vermicompost 45kg Amount of Complete fertilizer (14 – 14 – 14) = --------- X 100 = 321.43 kg/ha 14 321.43 kg x 22.m2/plot ---------------------------- = 0.72 kg/plot 10,000 m2 67.5 – 45 – 45 - 45 – 45 – 45 -----------------22.5 – 0 – 0 22.5 kg Amount of Urea (46 – 0 – 0) = ------------------- X 100 = 48.91 kg/ha 46 48.91 kg/ha x 22.5 m2/plot --------------------------------- = 0.11kg/plot 10,000 m2 2,500 kg Amount of vermicompost = -------------------- x 22.5= 5.625 or 5.63kg 10,000 m2 ------------------------------------------------------------------------------------------------------- 14 ------------------------------------------------------------------------------------------------------Treatment 4: 45-30-30 kg/ha N, P2O5, K2O + 5 tons/ha of vermicompost 30 kg Amount of Complete fertilizer (14-14-14) = ----------- X 100 = 214.29 kg/ha 14 214.29 kg X 22.5 m2/plot -------------------------------- = 0.48 kg/plot 10,000 m2 45 – 30 – 30 - 30 – 30 – 30 -------------------15 – 0 – 0 15 kg Amount of Urea (46 – 0 – 0) = ------------- X 100 = 32.60 kg/ha 46 32.60 kg X 22.5 m2/plot -------------------------------- = 0.073 kg/plot 10,000 m2 5,000 kg Amount of vermicompost = -------------------- X 22.5= 11.25 kg 10,000 m2 ------------------------------------------------------------------------------------------------------Treatment 5: 22.5-15-15 kg/ha N, P2O5, K2O + 7.5 tons/ha of vermicompost 15 kg Amount of Complete fertilizer (14 – 14 – 14) = -------------- X 100 = 107.14 kg/ha 14 107.14 kg X 22.5 m2/plot --------------------------------- = 0.24 kg/plot 10,000 m2 15 22.5 – 15 – 15 - 15 – 15 – 15 ------------------7.5 – 0 – 0 7.5 kg Amount of Urea (46 – 0 – 0) = ----------------- X 100 = 16.30 kg/ha 46 16.30 kg X 22.5 m2/plot -------------------------------- = 0.036 or 0.037 kg/plot 10,000 m2 7,500 kg Amount of Vermicompost = --------------- x 22.5 = 16.87 kg/plot 10,000 m2 16 BUDGETARY REQUIREMENTS I. COST OF LABOR A. Land Preparation Under brushing Plowing Harrowing Sub-total B. Maintenance Cost Planting Weeding Off-barring Hilling-up Sub-total II. SUPPLIES & MATERIALS A. Office supplies Ball pen Bond paper (A4) Record book Measuring tape Meter stick Paint Straw Sub-total B. Farm Supplies Seedling Trays Sweet Corn Seeds Vermicompost Complete (14-14-14) fertilizer Urea (46-0-0) fertilizer Sub-total III. Laboratory Analysis A. Soil Analysis 1. pH 2. Organic Matter 3. Total Nitrogen 4. Available P 5. Exch. K 6. EC 7. Organic Carbon 8. CEC B. Tissue Analysis 1. Nitrogen Uptake Quantity Unit Unit Price (Php) Total (Php) 3 1 1 Man/day Tractor Tractor 500.00 6,000.00 3,000.00 1,500.00 6,000.00 3,000.00 10,500.00 10 3 2 2 Man/day Man/day Man/day Man/day 500.00 500.00 750.00 750.00 5,000.00 1,500.00 1,500.00 1,500.00 9,500.00 3 6 2 1 1 1 1 pcs reams pcs pc pc liter roll 15.00 300.00 150.00 300.00 25.00 400.00 200.00 45.00 1,800.00 300.00 300.00 25.00 400.00 200.00 3,070.00 17 2 7 15 3 pcs kgs sacks kgs kgs 300.00 2,900.00 700.00 43.00 45.00 5,100.00 5,800.00 4,900.00 645.00 135.00 16,580.00 2 2 2 2 2 1 1 1 samples samples samples samples samples sample sample sample 50.00 150.00 150.00 200.00 200.00 200.00 200.00 200.00 100.00 300.00 300.00 400.00 400.00 200.00 200.00 200.00 36 samples 150.00 5,400.00 17 C. 1. 2. 3. 4. 5. Organic Fertilizer Analysis pH Total N Total P OM Potassium Sub-total IV. MANUSCRIPT PREPARATION Book binding Sub-total V. CONTINGENCY GRAND TOTAL 1 1 1 1 1 sample sample sample sample sample 50.00 150.00 200.00 150.00 200.00 50.00 150.00 200.00 150.00 200.00 8,250.00 9 pcs 300.00 2,700.00 2,700.00 4,000.00 54,600.00 18 CALENDAR OF ACTIVITIES Date Activities October 29, 2023 Clearing the area October 31, 2023 Soil sampling (Initial) November 06, 2023 Procurement of materials November 10, 2023 1st plowing and 1st harrowing January 05, 2024 2nd harrowing January 12, 2024 Furrowing January 14, 2024 Layout of plots January 15, 2024 Vermicompost application January 29, 2024 Planting (Main Plot 1) February 05, 2024 Transplanting (Main Plot 2)