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USAID-SIL MRA 2 – Soybean Agronomic and Production Research (Ghana)

Two (2) Year Activity Review Summary Report of SMART Farm In Ghana (2014 – 2015)

Feed the Future Innovation Lab for Soybean Value Chain Research (Soybean Innovation Lab, SIL)

Report Submitted: George Awuni, Postdoctoral Associate

Dan Reynolds,

Project PI, Professor of Weed Science, and Edgar E. and Winifred B. Hartwig Endowed Chair of Soybean Agronomy

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Contents

Title………………………………………………………………………………………………………………………………………………………..1

Contents…………………………………………………………………………………………………………………………………………………2

Summary………………………………………………………………………………………………………………………………………………..3

Research Progress Summary (2014 – 2015)……………………………………………………………………………….…………..3

Objective 1 Soil Sampling.…………………………………………………….…………………………………………………..4

1.1 Procedure ………..…………………………………………..……………………………………………………………………..4

1.2 Results of Soil Physiacal Anaysis …………………………………………………………………………………………..4

1.3 Results of Chemical Analysis…………………………………………………………………………………………………4

1.4 Soil Fertility Analysis …………………………………………………………………………………………………………….6

1.5 Phosphorus Sorption Isotherms.…………………………………………………………………………………………..7

1.6 Conclusion ………………………………………………………………………………………………..……………………….10

Objective 2 Seed Germination Test ………………………………………………………………………………………………………11

2.1. Procedure………………………………………………………………………………………………………………………….11

2.2 Seed Germination Results ………………………………………………………………………………………………….11

2.3 Conclusion …………………………………………………………………………………………………………………………12

Objective 3 Nutrient Amendment Trial ………………………………………………………………………………………………..12

3.1 Procedure ………………………………………………………………………………………………………………………….12

3.2 Yield Results……………………………………………………………………………………………………………………….12

3.3 Conclusion …………………………………………………………………………………………………………………………14

Objective 4 Variety Trial ……………………………………………………………………………………………………………………….14

4.1 Procedure…………………………………………………………………………………………………………………………..14

4.2 Yield Results ………………………………………………………………………………………………………………………14

4.3 Conclusion …………………………………………………………………………………………………………………………16

Objective 5 Planting Date Trial……………………………………………………………………………………………………………..16

5.1 Procedure ………………………………………………………………………………………………………………………….16

5.2 Yield Results ………………………………………………………………………………………………………………………16

5.3. Conclusion ………………………………………………………………………………………………………………………..18

6.0 Collaboration and Outrearch ………………………………………………………………………………………………………….18

7.0 Future Direction ……………………………………………………………………………………………………………………………..19

Appendices…………………………………………………………………………………………………………………………………………. 20

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I. Summary

Soybean Innovation Laboratory (SIL) Management Research Area (MRA) 2 tasked with soybean agronomic and production research, adopted Soybean Management by Application of Research and Technology (SMART) concept in soybean trials in northern Ghana for 2014 and 2015 cropping seasons. The SMART concept adopts a holistic approach confronting soybean production from soil fertility, seed germination, planting and nutrient stewardship, and other agronomic practices through to harvest. Results obtained are intended to provide stakeholders in the soybean production system with additional information to improve yields. The SMART approach were applied with standard agronomic practices in variety performance trial, soil amendment trial, and planting date trial in soybean production in 3 locations of northern Ghana. The locations included Nyankpala (Tolon District) in Northern Region, Manga (Bawku East District) in Upper East Region, and Bamahu (Wa Municipal) in Upper West Region.

The Nyanakpala soils were classified as loamy sand and clay loam for surface and subsoils, respectively. Manga soils were of loamy sand and sandy loam soils, while at Bamahu the soils were classified as loam. Soil pH ranged from moderately acid at Nyankpala and Bamahu sites to strongly acidic at Manga. Soil nutrient fertility rated across all 3 locations ranged mostly from very low to medium depending on nutrient element tested. Calculated cation exchange capacity was very low for Manga soils compared to Nyankpala and Bamahu. Lime and specific nutrient amendment recommendation were made for each location. Seed germination percentage depended on year and variety tested. However overall germination percentage was higher in 2015 than in 2014.

In the nutrient amendment trial, average yield of varieties across nutrient amendment was not significant for the 2 cropping seasons. The synergy of soybean inoculation and phosphorus (+I+P) application resulted in significant yield averaged across varieties. In the variety trial, average yields of varieties across locations was not significant in 2014. However, in 2015 varietal yield was depended on location. The planting date trial, varieties yields averages across planting dates was significant as well as planting date yield averaged across varieties in both seasons. Plots planted within the first week of July resulted in higher yields compared to late planting. These experiments will be repeated and expanded to other locations.

II. Research Progress Summary (2014 – 2015)

Research progress made during the reporting period achieved the benchmarks and results outlined in the SIL Performance Management Plan (PMP). The activities accomplished within the reporting period are outlined below according to the appropriate objectives. Whilst agronomic parameters such as days to flower, plant height, nodule count, plant biomass etc. were evaluated in each trial, only yields are reported at this time. In each objective, an attempt is made to summarize the procedure taken to achieve results and ends with a brief conclusion.

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Objective 1: Assess the soils at SMART Farm for physical and chemical analysis as baseline for conducting field experiments. 1.1 Procedure SMART farm fields were established each year in all three northern regions of Ghana at Nyankpala (Northern Region); Bamahu (Upper West Region); and Manga (Upper East Region). Coordinates, elevation and area of field locations were determined with Garmin GPS (Oregon 400t) (Appendices 1 and 2). Thirty (30) core samples were extracted from a field location with soil probe (AMS, 401.17, 2.86 cm × 60.96 cm SST) to 0-6ʺ (0-15cm) depth. Core samples were separated into 0-8 cm and 8-15 cm depths to form composite soil samples, except at Bamahu. Representative composite soil samples were processed, placed in standard soil sample bags and shipped to A & L Laboratories, Memphis for soil physical and chemical analysis (Appendices 3). 1.2 Results of Soil Physical Analysis

Soil textural classification are reported in Table 1 below.

In general, soils that consist of combinations of sand, silt, and clay particle size are termed loam. Based on the percentage proportions of sand, silt, and clay, the Nyankpala and Manga soils contain more sand at the surface, compared to the subsoils that tend to be clay loam and sandy loam, respectively. The Bamahu soils approximately equal amounts of soil properties (Table 1).

1.3. Results of Soil Chemical Analysis

Soil pH ranged from moderately acid for Nyankpala and Bamahu soils to strongly acidic for Manga soil (Table 2). Buffer pH was not significantly different among locations. Phosphorus was reported low for Nyankpala subsoil and Bamahu soils, medium for Nyankpala and Manga subsoils, and optimum for Manga topsoil. Potassium was very low or low for Nyankpala and Manga soils, but medium for Bamahu soils. Calcium ranged from medium for Nyankpala and Bamahu soils to low at Manga location. Magnesium ranged from medium to optimum for Nyankpala soil, low for Manga and optimum for Bahahu. Sulfur and Boron were low and very low, respectively for all locations. Copper content in the soil was rated medium for Nyankpala and Manga soils, but optimum for Bamahu soil. Iron and Manganese both ranged from medium to optimum for Nyankpala and Manga soils, but low for Manga soils. Iron was rated optimum

Table 1. Soil textural classification as reported by A & L Laboratories, Memphis, for Nyankpala, Manga, and Bamahu soils according to soil depth in northern Ghana LOCATION

Soil Depth (cm)

Sand (%)

Silt (%)

Clay (%)

Textural Classification

Nyankpala 0 – 8 75.2 16.7 8.1 Loamy sand Nyankpala 8 – 15 37.2 30.7 32.1 Clay loam Manga 0 – 8 79.2 14.7 6.1 Loamy sand Manga 8 – 15 55.2 30.7 14.1 Sandy loam Bamahu 0 – 15 47.2 32.7 20.1 Loam

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and manganese medium for Bamahu location. Zinc was optimum for Nyankpala and Bamahu locations, but medium for Manga location. Organic matter and estimated nitrogen release (ENR) was highest for soil of Nyankpala than Manga and Bamahu. Estimated available nitrogen in the form of nitrate in the soil form was greater for Manga location.

Table 2. Soil fertility rating as reported by A & L Laboratories, Memphis at 0 – 15 cm soil sample depth for soybean crop for Nyankpala, Bawku, and Wa locations in Northern Ghana INPUT

LOCATIONS Nyankpala

Manga

Bamahu

Extraction Method

0-8 (cm)

8 -15 (cm)

0 - 8 (cm)

8-15 (cm)

0-15 (cm)

Soil pH 1:1 6.1 5.7 5.1 4.9 6.0 Buffer pH - - 6.85 6.86 6.86 - Phosphorus (P) (ppm) M3 18 (M) 15 (L) 30 (O) 26 (M) 8 (L) Potassium (K) (ppm) M3 51 (VL) 66 (L) 39 (VL) 21 (VL) 76 (M) Calcium (Ca) (ppm) M3 847 (M) 546 (M) 174 (L) 155 (L) 416 (M) Magnesium (Mg) (ppm) M3 123 (M) 102 (O) 27 (L) 23 (L) 81 (O) Sulfur (S) (ppm) M3 10 (L) 8 (L) 9 (L) 8 (L) 7 (L) Boron (B) (ppm) M3 0.2 (VL) 0.1 (VL) 0.2 (VL) 0.1 (VL) 0.3 (L) Copper (Cu) (ppm) M3 2.3 (M) 2.3 (M) 1.9 (M) 2.2 (M) 2.8 (O) Iron (Fe) (ppm) M3 9.9 (M) 109 (O) 49 (L) 49 (L) 107 (O) Manganese (Mn) (ppm) M3 122 (M) 140 (O) 30 (L) 33 (L) 44 (M) Zinc (Zn) (ppm) M3 5.9 (O) 8.5 (O) 2.2 (M) 2.2 (M) 3.6 (O) Sodium (Na) (ppm) M3 20 18 24 19 33 Organic Matter (O.M)% LOI 1.5 1.4 0.4 0.4 1.1 ENR LOI 74 72 50 50 66 Nitrate Nitrogen (ppm) NO3N 13 10 19 11 6 M = medium; L = low; VL = very low; O = optimum; LOI = loss-on-ignition; ENR = Estimated Nitrogen Release; NO3N = Nitrate Nitrogen; M3 = Mehlich 3.

Calculated cation saturation refers to the proportion of the cation exchange capacity occupied by each cation (Table 3). Potassium and magnesium were highest for Bamahu location, while calcium was greatest for Nyankpala location. Hydrogen and sodium were greater at Manga location, while Bamahu location recorded the lowest neutralizable acidity (HMeq).

Table 3. Calculated cation saturation at 0 – 15 cm soil depth for soybean crop at Nyankpala, Bawku, and Wa locations in northern Ghana Cation (%)

Nyankpala

LOCATIONS Manga

Bamahu

0 – 8 (cm)

8 – 15 (cm)

0 – 8 (cm)

8 – 15 (cm)

0 – 15 (cm)

Potassium (P) 2.4 4.0 5.2 3.2 6.1 Calcium (Ca) 64.3 53.9 38.2 38.3 54.8 Magnesium (Mg) 18.1 19.6 11.5 11.0 20.7 Hydrogen (H) 14.1 21.1 37.2 45.3 15.2 Hmeg 0.7 0.8 0.7 0.7 0.5 Sodium (Na) 1.7 2.0 5.8 5.2 4.8

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Table 4. Calculated cation exchange capacity (CEC) at 0 – 15 cm soil depth from Nyankpala, Manga, and Bamahu sites in northern Ghana

Soil Depth (cm)

Nyankpala

LOCATIONS Manga

Bamahu

0 – 8 5.2 meq/100g 1.8 meq/100g 3.0 meq/100g

8– 15 4.0 meq/100g 1.6 meq/100g 3.0 meq/100g Meq = milli-equivalents (%)

The results indicate that cation exchange capacity (Table 4) of each soil site to hold positively charged nutrients was low. As reported, the lower the CEC the less clay or organic matter content in the soil. This implies the clay and organic matter content is higher in Nyankpala soils than Bamahu, with Manga being the least. As reported, the lower the CEC of a soil, the faster the soil pH will decrease over time. Additionally, soils with low CEC has the potential to develop potassium, magnesium and other cation deficiencies.

Table 5. Soil chemical rating at 0 – 15 cm soil depth for soybean crop in Nyankpala, Manga, and Bamahu locations on Northern Ghana Analysis

LOCATIONS Nyankpala

Manga

Bamahu

Extraction Method

0-8 (cm)

8-15 (cm)

0-8 (cm)

8-15 (cm)

0-15 (cm)

Buffer pH, SMP SMP Buffer pH 7.30 7.10 7.40 7.30 7.30 C/N Ratio Calculated 3:1 1:1 0.4:1 0.3:1 0.7:1 Calcium(Ca) (mg/kg) Ammonium acetate 695 432 135 132 331 Carbon, Total, % LECO 0.45 0.57 0.13 0.17 0.49 Magnesium (Mg), mg/kg Ammonium acetate 73.10 62.50 18.40 14.30 57.10 Total Organic Carbon (TOC %) WALK-BLACK 0.45 0.57 0.13 0.17 0.49 Potassium (K), mg/kg Ammonium acetate 38.80 44.80 33.70 17.40 58.20 Total N (Inorg + Org), % LECO 0.16 0.46 0.34 0.43 0.69 Sodium (Na), mg/kg Ammonium acetate 23.60 12.70 12.70 9.71 11.40 SMP = Shoemaker-McLean-Pratt;

Buffer pH as measured by SMP was the same for all locations (Table 5). Calculated C/N ratio, calcium, Total Carbon (%), Magnesium, Potassium as well as Total Organic Carbon (%) were lowest for Manga soils (Table 5).

1.4. Soil Fertility Recommendations

Soil fertility recommendation guidelines for a yield target of 50 bushels/acre (3,350 kg/ha) of soybean accompanied the soil report (Table 6). Nyankpala and Manga soils were recommended for lime application at 0.5 tons/acre and 1.5 tons/acre, respectively (Table 6). Nitrogen was not recommended for application in all 3 locations. Phosphorus was recommended at an average of

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84 P2O5 kg/ha for Nyankpala, 48.15 P2O5 kg/ha for Manga and 109.8 P2O5 kg/ha for Bamahu location. Potassium was also recommended at an average of 111.45 K2O kg/ha for Nyankpala, 120.95 K2O kg/ha for Manga and 90.7 K2O kg/ha for Bamahu location.

Table 6. Soil fertility recommendation at 0 – 15 cm soil depth for soybean crop in Nyankpala, Manga, and Bamahu locations Input

Nyankpala

LOCATION Bawku

Wa

0-8 (cm)

8-15 (cm)

0-8 (cm)

8-15 (cm)

0-15 (cm)

Lime (tons/acre) 0 1.0 1.5 1.5 0 Nitrogen (N) 0 0 0 0 0 Phosphorus (P2O5) (kg/ha) 80.6 87.4 33.6 62.7 109.8 Potassium (K2O) (kg/ha) 123.2 99.7 116.5 125.4 90.7 Magnesium (Mg) (kg/ha) 0 0 24.6 26.9 0 Sulfur (S) (kg/ha) 16.8 19.0 17.9 19.0 20.2 Boron (B) (kg/ha) 1.1 1.1 1.1 1.1 1.1 Copper (Cu) 0 0 0 0 0 Manganese (Mn) (kg/ha) 0 0 3.3 2.2 2.2 Zinc (Zn) 0 0 0 0 0 Iron (Fe) - - - - -

Yield goal: 50 bu/acre (3,350 kg/ha)

Magnesium was recommended for Manga only at an application rate of 25.75 mg kg/ha. Sulfur was recommended as one of the limiting nutrients and was recommended for application in all 3 locations at 17.9 S kg/ha for Nyankpala, 18.9S kg/ha for Manga and 20.2 S kg/ha for Bamahu. Other elements recommended include boron at 1.1 B kg/ha for each location and Manganese at 18.45 Mn kg/ha for Manga and 20.2 Mn kg/ha for Bamahu.

1.5. Phosphorus (P) Sorption Isotherms

P sorption isotherms of P sorbed (mg/ha) on Log P Remaining indicated considerably variability among locations (Fig. 1A, B, C, D, and E). The Nyankpala soils indicated a positive linear correlation for both surface soil 0-7.6 cm (R2 = 0.9852) and subsoil 7.6-15.2 cm (R2 = 0.8188). P sorbed increased as Log P Remaining increased (Fig. 1A and B). The Bawku soils indicated a non-linear poor correlation for 0-8 cm surface soil (R2 = 0.2861) and curvilinear correlation for 8 -15 cm (R2 = 0.725). In the Bawku soil, increasing Log P Remaining did not necessary result in increases in P sorbed (Fig. 1C & D). Initial increase in Log P remaining in from 1 to 1.6 for Bawku surface soil 0-7.5 cm resulted in P sorbed increase, but P sorbed decreased with increases in Log P Remaining. For Bawku surface soil 8-15 cm initial increase in Log P Remaining resulted in decreases in P sorbed to 1.4, but increased thereof as Log P remaining increased. The Wa soils was weakly correlation for surface soil 0-15 cm (R2 = 0.4129). Initial increases of Log P Remaining resulted in marginal response in P sorbed, but increased as Log P remaining increased (Fig. 1E).

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Fig. 1A. Polynomial best fit phosphorus (P) sorption isotherm curve with equation for Nyankpala surface soil (0-7.6 cm) of Log P remaining on Psorbed (mg/Kg)

Fig. 1B. Polynomial best fit phosphorus (P) sorption isotherm curve with equation for Nyankpala surface soil (7.6-15.2 cm) of Log P remaining on Psorbed (mg/kg)

0.5289167 67.20 1.222716471 146.00 1.505149978 171.00

1.86569606 193.00 2.243534102 253.00

0.596597096 61.50 1.26245109 130.00

1.580924976 110.00 1.901458321 130.00 2.243781916 252.00

y = 2.9157x2 + 95.392x + 18.187

R² = 0.9852

300

250

200

0 0.5 1 1.5 2 2.5

Log P Remaining

P so

rbed

(mg/

Kg)

y = 66.977x2 - 93.771x + 103.48

R² = 0.8188

300

250

200

0 0.5 1 1.5 2 2.5

Log P Remaining

P so

rbed

(mg/

Kg)

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Fig. 1C. Polynomial best fit phosphorus (P) sorption isotherm curve with equation for Bawku surface soil (0-7.5.2 cm) of Log P remaining on Psorbed (mg/Kg)

Fig. 1D. Polynomial best fit phosphorus (P) sorption isotherm curve with equation for Bawku surface soil (7.6-15.2 cm) of Log P remaining on Psorbed (mg/Kg)

0.943988875 13.10 1.444044796 35.00

1.62838893 66.00 1.963787827 7.00 2.296226287 27.00

0.920123326 17.80 1.462397998 23.00 1.666517981 27.00 1.962842681 9.00

2.27600199 117.00

y = -54.435x2 + 177.19x - 103.02

R² = 0.2861

70

60

50

40

30

20

0 0.5 1 1.5 2 2.5

Log P Remaining

P so

rbed

(mg/

Kg)

y = 109.99x2 - 295.12x + 202.48

R² = 0.725 140

120

100

80

60

40

0 0.5 1 1.5 2 2.5

Log P Remaining

P so

rbed

(mg/

Kg)

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Fig. 1E. Polynomial best fit phosphorus (P) sorption isotherm curve with equation for Wa surface soil (0-15.2 cm) of Log P remaining on Psorbed (mg/Kg).

1.6. Conclusion

The soil fertility analysis indicated that soils of all three locations are impoverished of nutrients. Soil pH, an important indicator of soil health ranged from moderately acidic at Nyankpala (5.7 – 6.1) and Bamahu (6.0) to strongly acidic for Manga (4.9 – 5.1). Soil pH of 6.0 – 6.5 is optimal for soybean production. Soil pH levels below this range as in the case of Manga soils can inhibit plant nutrient availability, impact activity of soil micro-organisms that effect key soil developments, and deterioration in soil health resulting in reduction of crop yield.

Phosphorus is one key element plants, including soybean need for flowering, fruiting and rooting. As indicated in the soil analysis, soil pH lower than 5.5 can inhibit availability of phosphate to plants. Liming to raise soil pH as recommended in the soil analysis could potentially beneficial by addition of calcium. However, in low CEC soils as observed in Manga soils, liming could be wasteful since the soil cannot hold on to all of the applied lime and the calcium can easily leached into the soil. Management strategies such as addition of good quality compost or use of cover crops may be the best option to increase soil CEC.

Other soil management options include applying phosphorus fertilizer in small amounts as opposed to one time application in large quantity. Band application may be good since soil test levels are low.

0.80685803 36.90 1.352182518 88.00 1.630427875 64.00 1.949390007 37.00 2.270678836 140.00

y = 41.918x2 - 83.304x + 88.469

R² = 0.4129 160

140

120

100

80

60 0 0.5 1 1.5 2 2.5

Log P Remaining

P so

rbed

(mg/

Kg)

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Objective 2: Assess seed germination percentage of commonly cultivated soybean varieties. Seed germination percentage was conducted in Year 1 (2014) and Year 2 (2015) of the SIL project across 14 soybean varieties (Table 6). Seeds were obtained from SARI (Nyankpala - Tamale) and the Crop Research Institute (CRI) (Fumensua - Kumasi) in Year 1. Nine (9) soybean varieties were obtained from SARI, and (five) were propagated in the 2014 SMART season and stored for Year 2. The objective was to evaluate the varieties to determine germination percentage before planting. 2.1. Procedure This experiment was conducted with two layers of blotted paper soaked in water not to dripping, and a 100 seed lot determined and placed on the 2 layer damp paper. A third soaked blotter was used over the 100 seed lot. The resulting contents were slightly folded on one edge along each length to form a tube. Each test variety had 6 replications of 100 seeds labelled with Noblet ink pencil by cultivar, test date, and seed number. Replicates of a variety was placed in Ziploc bags, partially closed and placed in plastic buckets at 84 ± 2ºF and 71% R. H. Fifteen (15) ml of water was added into each Ziploc bag to keep contents moist and observation daily. 2.2. Seed Germination Results Table 7. Mean percentage germination of fourteen (14) cultivars tested at Nyankpala during 2014 and 2015 cropping seasons Cultivar

Percentage germination (%) Mean 2014 2015

1. Afayak 70.7fghi 79.8def 75.2 2. Anidaso 83.6cde 85.2bcde 84.1 3. Jenguma 72.8fgh 92.0ab 82.4 4. Nangbar 91.5abc 93.5ab 92.5 5. Quarshie 77.5efg 93.0ab 85.2 6. Suong-Pungun 63.3ijk 85.7bcde 74.5 7. Salintuya I 72.8fgh 96.3a 84.6 8. Salintuya II 68.8ghij 89.2abcd 79.0 9. Songda 68.5ghijk 91.2abc 79.8 10. TGX 1448-2E 59.2k 86.5bcde 72.8 11. TGX 1805-8F 67.7hijk 91.5abc 79.6 12. TGX 1844-22E 59.7jk 88.5abcd 74.1 13. TGX 1903-7F 22.0l 30.2l 26.1 14. TGX 1987-14F 72.2fghi 70.5fghi 71.3 Mean 68.9 83.8

Means within a category and in the same row column with the same letter case group are not significantly different (α = 0.05).

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The results (Table 7) generally indicated that seed germination percentage was acceptable in 2015 compared to 2014. With the exception of TGX 1903-7F variety, Year 2015 expressed greater percentage germination of 70% or greater than in Year 2014. Therefore, seed germination percentage of varieties depended on year of harvest. Even though not evaluated in this study, seed storability over the storage year can impact on germination. 2.3. Conclusion The results from the 2 year study suggest that seed germination percentage of varieties was year depended. Year 2 of the study gave the greatest seed germination percentage. Seeds are not generally treated but storage over the dry season in readiness for the next cropping season to be used for planting. When not stored under the right temperature and humidity for this extended period, seed viability could be impacted. This study is considered a preliminary study and will be continued over a number seed sources to validate these results. Thus, the experiment will be repeated in Year 3 of the SIL project.

Objective 3: Determine the effect of nutrient amendment of phosphorus application and/or Bradyrhizobium inoculated with 5 soybean varieties commonly grown in Ghana. Replicated field trials were conducted at Nyankpala location in year 1 (2014) and year 2 (2015) cropping seasons to determine the effect of phosphorus application and /or soybean inoculated with Bradyrhzobium japonicium on 5 soybean varieties commonly grown in Ghana.

3.1. Procedure This trial was a 4 ×5 factorial experiment: 4 nutrient amendment levels over 5 soybean varieties with 4 replications in a randomized complete block design. This experiment was planted on July 1, 2014 (Year 1) and July 3, 2015 (Year 2). Soybean seeds were coated with Rizobin LF (Legume Technology Ltd; AGRO-PROFI s.r.o., Prague, Czech Republic) in Year 1 and NoduMax (IITA Business Incubation Platform, Nigeria) in Year 2 before planting per the manufacturer’s prescription. Planting was drill-seeded, and thinned to a density of 266,000 plants/ha at 2 leaf (V2) stage at 5 cm within rows and 75 cm between rows. The nutrient amendment levels applied were inoculum and phosphorus (+I+P); inoculum only (+I-P); phosphorus only (-I+P); and control (-I-P). The varieties planted included Afayak, Quarshie, Songda, Jenguma, and Suong-Pungun. Phosphorus was band applied in the form of triple superphosphate (P2O5) at 60 kg P2O5/ha. Plots had six rows with 5 m long × 4.5 m wide. Cultural and pest control management practices were followed for optimum yields. 3.2. Yield Results Yields from the 2 cropping seasons are indicated in Tables 8 and 9 below. Year was a significant (p< 0.5) factor in determining yield, consequently the data was analyzed by year. For the 2 cropping seasons, the simple main effect of variety by nutrient amendment was not significant (p>0.5).

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The main effect of variety on yield was not also significant (p>0.05), indicating that the mean yield of varieties averaged across levels of nutrient amendment were not significantly different for both cropping seasons.

Table 8. Yields of five (5) cultivars tested on phosphorus fertilizer (TSP)/or Bradyrhizobium inoculum at Nyankpala (2014) Variety

Nutrient Amendment Mean +I+P +I-P -I+P -I-P

Afayak 2816.7 2016.7 2516.7 1766.7 2279.2a Jenguma 2466.7 2250.0 1966.7 1783.3 2116.7a Quarshie 2300.0 1900.0 2133.3 1600.0 1983.3a Suong-Pungun 2250.0 2033.3 1800.0 1316.7 1850.0a Songda 2433.3 1833.3 2050.0 1583.3 1975.0a Mean 2453.3A 2006.7B 2093.3B 1610.0C

Means within a category and in the same row or column with the same letter case group are not significantly different (α = 0.05). Table 9. Yields (kg/ha) of five (5) cultivars tested on phosphorus fertilizer (TSP)/or Bradyrhizobium inoculum at Nyankpala (2015) Variety

Nutrient Amendment Mean +I+P +I-P -I+P -I-P

Afayak 1940.6 1506.4 1532.3 1391.1 1592.6a Jenguma 2058.6 1492.2 2055.2 1398.8 1751.2a Quarshie 2027.7 1787.7 1835.2 1374.1 1756.2a Suong-Pungun 1891.2 1230.9 1766.9 1278.0 1541.8a Songda 1730.3 1485.2 1460.1 1284.6 1490.1a Mean 1929.7A 1500.5BC 1729.9AB 1345.3C

Means within a category and in the same row or column with the same letter case group are not significantly different (α = 0.05).

The main effect of nutrient amendment on yield was significant (p<0.5), indicating that application of impacted significantly on yield averaged across varieties in both years. Results from the 2 year study suggest the synergy of soybean inoculation and phosphorus (+I+P) application had the highest soybean yield, which was not significantly different from phosphorus (-I+P) application only in 2015. For both years, the results also suggest that soybean yields were not significantly different between plots inoculated only (+I-P) and phosphorus application only (-I+P).

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3.3. Conclusion

The results from this 2 year study suggest that the synergy in soybean inoculation and phosphorus application gave the highest soybean yield. There seem to be no clear advantage between inoculation only and phosphorus application only from this study. This study will be continued over a number of locations to validate these results.

Objective 4: Evaluate ten (10) locally identified soybean varieties planted in Ghana for yield comparison and other growth parameters. Ten varieties were evaluated at the SMART farm across three location at Nyankpala, Bamahu and Manga for Year 1 (2014) and Year 2 (2015). These locations covered 2 agro-ecological zones of Ghana; the Sudan and Guinea Savanna zones. The varieties tested included Afayak, Anidaso, Jenguma, Quarshie, Salintuya I, Salintuya II, Songda, Suong-pungu, TGX 1448-2E, and TGX 1844-22E. 4.1. Procedure This trial was a one factor experiment with varieties as the main treatment. There were 10 varieties with 4 replications in a randomized complete block design (RCBD). The Manga fields were planted on June 26, 2014 (Year 1) and July 3, 2015 (Year 2). Planting was done at Bamahu on July 4, 2014 (Year 1) and July 17, 2015 (Year 2). In Nyankpala, planting was conducted on July 1, 2014 (Year 1) and July 4, 2015 (Year 2). Soybean seeds were inoculated with Rizobin LF (Year 1) and NoduMax (Year 2) per manufacturer’s prescription as base treatment across varieties before planting. Planting was drill-seeded, and thinned to 266,000 plants/ha at 2 leaf (V2) stage with a plant spacing of 5 cm within rows and 75 cm between rows across locations and years. Phosphorus was band applied as base treatment following thinning across varieties at 60 kg P2O5/ha. Plots had six rows with 5 m long × 4.5 m wide across locations and years. Cultural and pest control management practices were followed for optimum yields.

4.2. Yield Results

Year was significant (p<0.05), so data reported by year (Tables 10 and 11).

In year 1 (2014), the simple main effect of variety by location on yield was not significant (p>0.05) (Table 10), indicating independence of varieties on location. The main effect of variety on yield averaged across locations was not significant (p>0.05), indicating that varieties yielded similarly on average across locations. However, the main effect of location on yield was significant (p<0.05) when averaged across varieties. Bamahu and Nyankpala locations recorded the highest yield compared with yields from Manga.

15

In year 2 (2015), the simple main effect of variety at any given location on yield was significant (p<0.05) (Table 10), indicating variety response in yield was dependent on location. Afayak, TGX 1448-2E and TGX 1844-22E produced the greatest yield in Nyankpala and Bamahu. Quarshie, Salintuya I and Songda all had their highest yield recorded at Nyankpala, while Jenguma and Suong-pungun had their highest yield at Bamahu. Yields from Manga was the least regardless of variety. Soybean plants in this location were all infected with disease, hence the drastic reduction in yield loss.

Table 10. Yields (kg/ha) of ten (10) cultivars tested at Nyankpala, Bamahu, and Manga (2014) Variety

Location Nyankpala Bamahu Manga Mean

Afayak 2200.0 2600.0 1666.7 2155.5a Anidaso 1716.7 2066.7 1200.0 1661.1a Jenguma 2033.3 1666.7 1700.0 1800.0a Quarshie 3016.7 1933.3 1416.7 2122.2a Suong-Pungun 1866.7 1966.7 1700.0 1844.4a Salintuya I 1783.3 2166.7 1716.7 1888.9a Salintuya II 1883.3 2100.0 1800.0 1927.8a Songda 1750.0 1966.7 1366.7 1694.4a TGX 1448-2E 2016.7 1933.3 1366.7 1772.2a TGX 1844-22E 2050.0 2233.3 1733.3 2005.5a Mean 2031.7A 2063.3A 1566.7B


Table 11. Yields (kg/ha) of ten (10) cultivars tested at Nyankpala, Bamahu, and Manga (2015) Cultivar

Location Nyankpala Bamahu Manga Mean

Afayak 1582.1abcdef 1933.3ab - 1757.7 Anidaso 1468.2cdefg 1144.4g - 1306.3 Jenguma 1278.9fg 1677.8abcdef - 1478.3 Quarshie 1992.2a 1477.8cdefg - 1735.0 Suong-Pungun 1343.2efg 1888.9abc - 1616.0 Salintuya I 1822.8abcd 1500.0bcdefg - 1661.4 Salintuya II 1257.6fg 1244.4fg - 1251.0 Songda 1751.1abcde 1422.2defg - 1586.6 TGX 1448-2E 1789.4abcd 1933.3ab - 1861.3 TGX 1844-22E 1931.9ab 1988.9a - 1960.4 Mean 1621.7 1621.1 - 1621.4


16

4.3. Conclusion

The results in the variety test seem to indicate a reflection on soil fertility results for the 3 locations. The soils at Manga the most impoverished soil among the 3 locations, therefore not surprising the yields were lower from this location relative to the other 2 locations. In 2015, the plants were so diseased that yields are not reported.

Soil pH and CEC which are both important indicators of soil health were strongly acidic and very low at Manga. Strongly acidic soils can potentially inhibit plant nutrient availability, impact activity of soil micro-organisms that effect key soil developments, and deterioration of soil health resulting in yield reduction. Under these conditions, retention of essential nutrients for plant development can be limiting for example phosphorus, potassium and other cations. Liming to raise soil pH as recommended in the soil analysis could potentially be beneficial, but with CEC liming could be wasteful as the soil cannot support the retention calcium could easily be leached into the soil.

Application of phosphorus in small amounts, in addition to other management strategies such as addition of good quality compost or use of cover crops may an option to increase soil fertility. Also band application of fertilizer to reduce contact between the soil and source could be beneficial.

Objective 5: Determine the optimal planting dates for soybean in the savannah agro-ecological zone of Ghana Replicated field trials were conducted at Nyankpala location in 2014 (Year 1) and 2015 (Year 2) cropping years to determine the effect of planting date on 5 soybean varieties commonly grown in northern Ghana. 5.1 Procedure

This trial was designed as a 4 ×5 factorial experiment with 4 planting dates at weekly intervals by 5 varieties. The planting dates in Year 1 were on: July 2, July 9, July 17, and July 23, 2014; and in Year 2 on July 4, July 10, July 17, and July 24, 2015. The varieties planted included Afayak, Quarshie, Songda, Jenguma, and Suong-Pungun. Planting was by drill-seeded, and thinned to 266, 000 plants/ha at 2 leaf (V2) stage with a plant spacing of 5 cm within rows and 75 cm between rows. Soybean seeds were inoculated with Bradyrhizobium japonicium (RizobinLF and NoduMax) in Years 1 and 2, respectively as prescribed by the manufacturer before planting. Phosphorus was band applied in the form of triple superphosphate (P2O5) at 60 kg P2O5/ha as base treatment across varieties. Plots had six rows with 5 m long × 4.5 m wide. Cultural and pest control management practices were followed for optimum yields.

17

5.2. Yield Results

Yields for the cropping seasons are indicated in Tables 12 and 13 below. Year was significant, so data is reported by year. In both cropping seasons, the simple main effects of variety by planting dates were not significant (p>0.05), indicating the 2 factors were independent.

Table 12. Yields of five (5) cultivars evaluated at four (4) planting dates at weekly intervals at Nyankpala (2014) Cultivar

Planting Date (July Weeks) Mean First week Second week Third week Fourth week

Afayak 1916.7 1783.3 1583.3 1000.0 1570.8a Jenguma 2066.7 1633.3 1466.7 833.3 1500.0ab Quarshie 2383.3 1766.7 1583.3 866.7 1650.0a Suong-Pungun 1783.3 1316.7 1333.3 1050.0 1370.8ab Songda 1666.7 1216.7 1166.7 900.0 1237.5b Mean 1963.3A 1543.3B 1426.7B 930.0C


Table 13. Yields of five (5) cultivars evaluated at four (4) planting dates at weekly intervals at Nyankpala (2015) Cultivar

Planting Date (July Weeks) Mean First Week Second Week Third Week Fourth Week

Afayak 1603.7 1735.6 1505.3 1469.3 1578.5ab Jenguma 2092.3 1665.3 1309.0 1281.7 1587.1ab Quarshie 1903.6 1670.9 1356.9 1383.2 1578.7ab Suong-Pungun 1871.4 1806.0 1696.4 1560.6 1733.6a Songda 1661.4 1432.5 1372.7 1211.0 1419.4b Mean 1826.5A 1662.1A 1448.1B 1381.2B


In Year 1 (Table 12), the main effect of variety on yield averaged across the 4 planting dates was significant (p<0.05). Afayak and Quarshie were the highest yielding varieties, but was not significantly different from Jenguma and Suong-Pungun. Songda was the least yielding, and was not also significantly different from Jenguma and Suong-Pungun. The main effect of planting date on yield averaged across varieties was significant (p<0.05). Planting within the first week of July recorded the highest mean yield averaged across varieties. Planting within the second and

18

third weeks of July were not significantly different in yield. However, planting within the fourth week planting window significantly reduced yield.

In Year 2, (Table 13), the main effect of variety on yield averaged across 4 planting dates was significant (p<0.05). Suoun-Pungun had the highest yield, but did not differ significantly from Afayak, Jenguma, and Quarshie. Again, Songda was the least yielding averaged across planting dates, but the yields were not significantly different from Afayak, Jenguma, and Quarshie. The main effect of planting date on yield averaged across varieties was also significant (p<0.05). The yields recorded for the July first and second week planting windows were significantly higher than the third and fourth planting dates.

5.3. Conclusion

From the results above, planting within the first week of July gave the highest yield in both years. The results suggest soybean farmers to plant early not later than the second week of July to obtain maximum yield. The question of how early to plant is always the judgement of the farmer or researcher. The first planting dates was determined following adequate water moisture observed in the soil that could sustain seed germination and support seedling development. Farmers use similar observation methods and land marks to determine when to plant. Songda showed lower yields in both years compared to the 4 other varieties. This probably suggest lower yield potential than the 4 varieties over Songda.

Future work may want to experiment planting within isolated early rains (in June) to determine the nature of yields as compared to that planted in July.

6. Collaboration and Outreach

The following presentation (trainings)/ field days were organized/ conducted during the 2015 SMART growing season to transfer information to stakeholders interested in soybean production: 6. 1. Feb 9, 2015 – Volunteered oral presentation “An Overview of Year 1 SMART Farm in

Ghana”. Departmental Seminar, Department of Plant and Sciences at Green House Building. Audience: Students, Staff and Faculty

6. 2. June 10, 2015 – Volunteered oral presentation “An Overview of Year 1 SMART Farm: Success and Challenges” at SARI monthly seminar series at SARI conference room. Audience: SARI Staff and Research Scientists.

6. 3. July 8, 2015 – Invited oral presentation “The SMART Farm Concept in Sub-Saharan Africa (Reference to Ghana)” at the SARI Conference Block. Audience: Catholic Relief Services (CRS) led USA Faculty Fellowship Program Delegation to SARI, UDS Faculty and Staff, SARI Staff. The USA Faculty members included: Prof. Robin G. Vander – Xavier University of Louisiana; Prof. Nicky Santos – Marquette University; Prof. Amber Aubone – St. Mary’s University; Prof. Hal Culberton – University of Notre Dame; Asst. Prof. Meghan Clark – St. John’s University; and Dr. Mathew Johnson – Siena College.

19

6. 4. July 6, 2015: Visited with USAID/Resiliency in Northern Ghana (RING) in Tamale at the invitation of Project Coordinator, Mr. Yunus Abdulai and to familiarize with RING activities in Northern Ghana as a USAID development partner.

6. 5. July 10, 2015 – Invited oral presentation “An Overview of Year 1 SMART Farm: Success and Challenges” at SARI monthly seminar series at SARI conference room. Audience: SARI Staff and Research Scientists. Audience: RING staff and MOFA Extension Agents. RING indicated no pesticide and fertilizer use in their soybean project implementation.

6. 6. July 15, 2015: Attended a Regional Policy Dialogue Conference organized by URBANET Gh (Tamale based Local NGO). Conference theme “Ensuring Policy and Program Responsiveness for Competiveness of Smallholder Soybean Production”. There were over 30 participants (21 men, 9 women) from the private and public sectors, NGO’s, MOFA, researchers and farmers. The Northern Regional Director of MOFA made a presentation on ‘Policy efforts/actions and interventions in the region in promoting agriculture’. This conference was part of the USAID Feed the Future Initiative under the Agriculture Policy Support Project.

6. 7. August 4 - 6, 2015: Invited oral presentation “SIL and the SMART Farm in Northern Ghana” Presented at the Year 3 Planning Conference Workshop Session of the USAID Feed the Future Agriculture Technology Transfer (ATT) Project under IFDC in Kumasi. Venue: Golden Bean Hotel, Kumasi.

6. 8. Oct. 14, 2015: Soybean Kick-off Event “Enhancing Opportunity and Productivity through Research, Innovation and Technology” at Nyankpala (SARI). On-farm presentation of SMART agronomic practices organized for over 100 farmers and research partners during the soybean kick-off event.

6. 9. Oct. 15, 2015 – Attended the 5th Annual Advance Technology Transfer (ATT) Pre-harvest Event in Tamale. This event brings together stakeholders in the Agriculture Sector in Ghana for a pre-harvest assessment of interventions of three major crops (maize, rice and soybean) grown in northern Ghana.

6. 10. Oct. 20, 2015: Participated in SARI Researchers Field Day Event. Over 30 SARI research scientists and technicians were taken through the SMART Farm agronomic practices on the farm.

6. 11. Nov. 18, 2015 – Invited oral presentation “Effects of phosphorus fertilizer on soybean”

organized by N2Africa for stakeholder workshop on sustainable supply of legume inputs in Northern Ghana. Venue: Modern City Hotel, Tamale. Audience: Farmers, Research Development Partners, MOFA, and NGOs.

6. 12. Dec. 10, 2015 – Visited with ACDI/VOCA’s ADVANCE office at the invitation of Allan Paneda on discussions of possible future research collaboration.

7. Future Direction

7. 1. Continue to collaboration and strengthen working relationship with SARI research scientists to facilitate the transfer of information and also better utilize available resources. Collaborating partners will include Dr. Nicholas Denwar (SILs partner and SARI breeder), Dr. Ben Ahiabor

20

(SARI Microbiologist), Dr. S. S. Buah (Wa Station Research Scientist), Dr. R. L. Kanton (Bawku Station Research Scientists), and Dr. M. Askia (Soil Scientist).

7. 2. Repeat agronomic trials in an appropriate experimental design with four replications and, if resources permit, expand the efforts at the two off locations.

7. 3. Hold several presentations (training)/field days at the SMART farm to transfer information to stakeholders interested in soybean production.

Appendix 1a. 2014 SMART Farm co-ordinates, elevation and area – Nyankpala (Tamale).

N 09°24.371' W 00°57.185'

N 09°24.371' W 00°57.211'

N 09°24.292' W 00°57.184'

N 09°24.293' W 00°57.209'

Tamale

NyankpalaROAD

N 09°24.336' W 00°57.209'

N 09°24.321' W 00°57.209'

N 09°24.335 W 00°57.184'

N 09°24.320' W00°57.184'

Planting Date Trial Plots

32658.74 ft² (3034.1 m²)

Variety Test Plots

14351.70 ft² (1333.3 m²)

Inoculum/Phosphorus Plots

23596.07 ft² (2192.1 m²)

Elevation 102 m

21

Appendix 1b. 2014 SMART Farm Co-ordinates – Manga (Bawku)

N 11°01.027' W 000°15.704'

N 11°01.050' W 000°15.704'

N 11°01.039' W 000°15.714'

N 11°01.027' W 000°15.679'

ROAD From Manga To weather station

Variety Trial Plots 18818ft² (1748.2 m²)

Elevation: 100 m

22

SMART FARM

Variety Trial Plots

36765ft² (3415.6 m²)

Elevation: 99.4 m

N 09°59.187' W 002°28.173'

N 09°59.220' W 002°28.193'

N 09°59.195' W 002°28.151'

N 09°59.232' W 002°28.171'

From Tamale

To UDS Bamahu (Administration)

To Wa

SARI Soybean trial

23

Appendix 1c. 2014 SMART Farm Co-ordinates – Bamahu (Wa)

N 09°24.414’ W000°57.185’

N 09°24.290’ W 000°57.183’

N 09°24.417’ W 000°57.214’

N 09°24.290’ W000°57.210’

Nyankpala Field

Location: 2 miles from Nyankpala – Tamale road

Elevation: 102.4 m

Area: 11861 m2

Appendix 2a. 2015 SMART Farm Co-ordinates – Nyankpala

24

N 11°00.857’ W 000°15.983’

N 11°00.837’ W 000°15.930’

N 11°00.842’ W 000°15.994’

N 11°00.824’ W 000°15.937’

Manga Field site

Location: Manga

Elevation: 100 m

Area: 3411.6 m2

Appendix 2b. 2015 SMART Farm Co-ordinates – Manga (Bawku)

25

Wa Field site

Location: Bamahu

Elevation: 99.4 m

Area: 7025.1 m2

N 09°59.146’ W 002°28.149’

N 09°59.171’ W 002°28.108’

N 09°59.208’ W 002°28.131’

N 09°59.179’ W 002°28.170’

Appendix 2c. 2015 SMART Farm Co-ordinates – Bamahu (Wa)

26

Lab Number: 08371 Field Id: Sample Id: 01A

* Additional results to follow

Crop: Soybeans

SOIL FERTILITY GUIDELINES

Yield Goal: 50 bu/acre Rec Units: LB/ACRE Comments: Soybeans

. For soybeans on soils with a pH of 6.2 or less, apply limestone as recommended and plant seed treated with molybdenum. Apply 1-2 oz of sodium molybdate (0.4-0.8 oz of elemental molybdenum) per acre as a seed treatment. BPH - Lime Index M3 - Mehlich 3 NO3N - Nitrate-N LOI - Loss On Ignition 1:1 - Water pH Analysis prepared by: A&L Analytical Laboratories, Inc.

(lbs) LIME (tons) N P² O 5 K ²O Mg S B Cu Mn Zn Fe 0 0 0 72 110 0 15 1.0 0 0 0

Client : Mississippi State UniversityGeorge Awuni Department of Plant & Soil Sciences32 Creelman St, 117 Dorman HallMississippi State MS 39762

Grower : Dr. Don Reynolds

SOIL ANALYSIS Report No: 14-188-0685 Cust No: 13056 Date Printed: 07/08/2014

Date Received : PO: Page :

07/07/2014

1 of 5

1:1 6.1

M3 18 ppm

756

M3 51 ppm

331

M3 847 ppm

898

M3 123 ppm

945

M3 10 ppm

614

M3 0.2 ppm

378

M3 2.3 ppm

898

M3 99 ppm

992

M3 122 ppm

945

M3 5.9 ppm

1181

M3 20 ppm

1

LOI 1.5 % ENR 74 NO3N 13 ppm

SOIL TEST Test

Very Low Very High Soil pH Buffer pHPhosphorus (P)Potassium (K)Calcium (Ca) Magnesium (Mg) Sulfur (S)

Boron (B)

Copper (Cu)

Iron (Fe)

Manganese (Mn)Zinc (Zn)Sodium (Na)Soluble SaltsOrganic Matter Nitrate Nitrogen

Calculated Cation Exchange Capacity

5.2 meq/100g Calculated Cation

Saturation

%K %Ca %Mg

%H

%Na

2.4 64.3 18.1

14.1 0.7

1.7

K : Mg Ratio 0.13

Ca : Mg Ratio 3.55 Fizz Test

Appendix 3(01A) Soil Analysis – Topsoil (Nyankpala)

27

Lab Number: 08372 Field Id: Sample Id: 01B


Crop: Soybeans

SOIL FERTILITY GUIDELINES

Yield Goal: 50 bu/acre Rec Units: LB/ACRE (lbs) LIME (tons) N P² O 5 K ²O Mg S B Cu Mn Zn Fe 2000 1 0 78 89 0 17 1.0 0 0 0

Comments: Soybeans. For soybeans on soils with a pH of 6.2 or less, apply limestone as recommended and plant seed treated with molybdenum. Limestone application is targeted to bring soil pH to 6.0. Apply 1-2 oz of sodium molybdate (0.4-0.8 oz of elemental molybdenum) per acre as a seed treatment. BPH - Lime Index M3 - Mehlich 3 NO3N - Nitrate-N LOI - Loss On Ignition 1:1 - Water pH Analysis prepared by: A&L Analytical Laboratories, Inc.

Client : Mississippi State University George Awuni Department of Plant & Soil Sciences 32 Creelman St, 117 Dorman Hall Mississippi State MS 39762

Grower : Dr. Don Reynolds


Date Received : PO: Page :

07/07/2014

2 of 5

1:1 5.7 BPH 6.85 M3 15 ppm

709

M3 66 ppm

662

M3 546 ppm

756

M3 102 ppm

1370

M3 8 ppm

520

M3 0.1 ppm

189

M3 2.3 ppm

898

M3 109 ppm

1040

M3 140 ppm

992

M3 8.5 ppm M3 18 ppm

2


SOIL TEST

Test Very

Very

Soil pH Buffer pHPhosphorus (P)Potassium (K)Calcium (Ca) Magnesium (Mg) Sulfur (S)

Boron (B)

Copper (Cu)

Iron (Fe)



4.0 meq/100g

Calculated CationSaturation

%K %Ca %Mg

%H

%Na

4.0 53.9 19.6

21.1 0.8 2.0

K : Mg Ratio 0.20

Ca : Mg Ratio 2.75

Fizz Test

Appendix 3(01B) Soil Analysis – Subsoil (Nyankpala)

28

Lab Number: 08374 Field Id: Sample Id: 02A

* Additional results to follow Crop: Soybeans

SOIL FERTILITY GUIDELINES Yield Goal: 50 bu/acre Rec Units: LB/ACRE

(lbs) LIME (tons) N P² O 5 K ²O Mg S B Cu Mn Zn Fe 3000 1.5 0 30 104 22 16 1.0 0 3 0

Comments: Soybeans Limestone application is targeted to bring soil pH to 6.0.

· For soybeans on soils with a pH of 6.2 or less, apply limestone as recommended and plant seed treated with molybdenum. Apply 1-2 oz of sodium molybdate (0.4-0.8 oz of elemental molybdenum) per acre as a seed treatment.

BPH - Lime Index M3 - Mehlich 3 NO3N - Nitrate-N LOI - Loss On Ignition 1:1 - Water pH Analysis prepared by: A&L Analytical Laboratories, Inc.

Client: Mississippi State UniversityGeorge Awuni Department of Plant & Soil Sciences32 Creelman St, 117 Dorman HallMississippi State MS 39762

Grower: Dr. Don Reynolds

SOIL ANALYSIS Report No: 14-188-0685 Cust No: 13056 Date Printed: 07/08/2014 Date Received: PO: Page:

07/07/2014

3 of 5

1:1 5.1 BPH 6.86 M3 30 ppm

992

M3 39 ppm

331

M3 174 ppm

473

M3 27 ppm

425

M3 9 ppm

567

M3 0.2 ppm

378

M3 1.9 ppm

851

M3 49 ppm

662

M3 30 ppm

709

M3 2.2 ppm

803

M3 24 ppm

6


SOIL TEST

Test Very

Very


Boron (B)

Copper (Cu)

Iron (Fe)


Calculated Cation

Exchange Capacity


Saturation

%K %Ca %Mg

%H

%Na

5.2 38.2 11.5

37.2 0.7 5.8

K : Mg Ratio 0.44

Ca : Mg Ratio3.32

Fizz Test

Appendix 3(02A). Soil Analysis – Topsoil (Manga-Bawku)

29

Lab Number: 08375 Field Id: Sample Id: 02B

* Additional results to follow Crop: Soybeans SOIL FERTILITY GUIDELINES

Yield Goal: 50 bu/acre Rec Units: LB/ACRE (lbs) LIME (tons) N P² O 5 K ²O Mg S B Cu Mn Zn Fe 3000 1.5 0 56 112 24 17 1.0 0 2 0

Comments : Soybeans Limestone application is targeted to bring soil pH to 6.0.

· For soybeans on soils with a pH of 6.2 or less, apply limestone as recommended and plant seed treated with molybdenum. Apply 1-2 oz of sodium molybdate (0.4-0.8 oz of elemental molybdenum) per acre as a seed treatment.

BPH - Lime Index M3 - Mehlich 3 NO3N - Nitrate-N LOI - Loss On Ignition 1:1 - Water pH Analysis prepared by: A&L Analytical Laboratories, Inc

Client: Mississippi State UniversityGeorge Awuni Department of Plant & Soil Sciences 32 Creelman St, 117 Dorman HallMississippi State MS 39762



Date Received: PO: Page :

07/07/2014

4 of 5

1:1 4.9 BPH 6.86 M3 26 ppm

898

M3 21 ppm

189

M3 155 ppm

473

M3 23 ppm

425

M3 8 ppm

520

M3 0.1 ppm

189

M3 2.2 ppm

898

M3 49 ppm

662

M3 33 ppm

709

M3 2.2 ppm

803

M3 19 ppm

6


SOIL TEST Test Very

Very


Boron (B)

Copper (Cu)

Iron (Fe)


Calculated Cation

Exchange Capacity


Saturation

%K %Ca %Mg

%H

3.2 38.3 11.0

45.3 0.7

5.2

K : Mg Ratio 0.28

Ca : Mg Ratio 3.48

Appendix 3(02B). Soil Analysis – Subsoil (Manga-Bawku)

30

Lab Number: 08376 Field Id : Sample Id : 03A+B


Crop: Soybeans SOIL FERTILITY GUIDELINES

Yield Goal : 50 bu/acre Rec Units: LB/ACRE (lbs) LIME (tons) N P² O 5 K ²O Mg S B Cu Mn Zn Fe

0 0 0 98 81 0 18 1.0 0 2 0 Comments :

Soybeans · For soybeans on soils with a pH of 6.2 or less, apply limestone as recommended and plant seed treated with

molybdenum. Apply 1-2 oz of sodium molybdate (0.4-0.8 oz of elemental molybdenum) per acre as a seed treatment. BPH - Lime Index M3 - Mehlich 3 NO3N - Nitrate-N LOI - Loss On Ignition 1:1 - Water pH

1:1 6.0

M3 8 ppm

473

M3 76 ppm

756

M3 416 ppm

756

M3 81 ppm

1040

M3 7 ppm

473

M3 0.3 ppm

520

M3 2.8 ppm

992

M3 107 ppm

1040

M3 44 ppm

756

M3 3.6 ppm

1040

M3 33 ppm

5


SOIL TEST Test Very Low Very High


Boron (B)

Copper (Cu)

Iron (Fe)

Manganese (Mn)Zinc (Zn) Sodium (Na) Soluble Salts Organic Matter Nitrate Nitrogen



Saturation

%K %Ca %Mg

%H

%Na

6.1 54.8 20.7

15.2 0.5 4.8

K : Mg Ratio 0.29

Ca : Mg Ratio 2.65

Client: Mississippi State UniversityGeorge Awuni Department of Plant & Soil Sciences 32 Creelman St, 117 Dorman HallMississippi State MS 39762



Date Received: PO: Page:

07/07/2014

5 of 5

Appendix 3 (03A+B). Soil Analysis – Top and subsoils (Bamahu-Wa)

ThisdocumentismadepossiblebythegeneroussupportoftheAmericanpeoplethroughtheUnitedStatesAgencyforInternationalDevelopment. ThecontentsaretheresponsibilityoftheSoybeanInnovationLabanddonotnecessarilyreflecttheviewsofUSAIDortheUnitedStatesGovernment.

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USAID-SIL MRA 2 – Soybean Agronomic and Production ...soybeaninnovationlab.illinois.edu/sites/soybeaninnovationlab.illinois.edu/files/2 Year...The SMART concept adopts a holistic