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Conservation agriculture (CA) practices are being widely promoted in many areas in sub-Saharan Africa to recuperate degraded soils and improve ecosystem services. This study examined the effects of three tillage practices [conventional moldboard plowing (CT), hand hoeing (MT) and no-tillage (NT)], and three cropping systems (continuous maize, soybean–maize annual rotation, and soybean/maize intercropping) on soil quality, crop productivity, and profitability in researcher and farmer managed on-farm trials from 2010 to 2013 in northwestern Ghana. In the researcher managed mother trial, the CA practices of NT, residue retention and crop rotation/intercropping maintained higher soil organic carbon, and total soil N compared to conventional tillage practices after 4 years. Soil bulk density was higher under NT than under CT soils in the researcher managed mother trails or farmers managed baby trials after 4 years. In the researcher managed mother trial, there was no significant difference between tillage systems or cropping systems in maize or soybean yields in the first three seasons. In the fourth season, crop rotation had the greatest impact on maize yields with CT maize following soybean increasing yields by 41 and 49% compared to MT and NT maize, respectively. In the farmers’ managed trials, maize yield ranged from 520 to 2700 kg ha-1 and 300 to 2000 kg ha-1 for CT and NT, respectively, reflecting differences in experience of farmers with NT. Averaged across farmers, CT cropping systems increased maize and soybean yield ranging from 23 to 39% compared with NT cropping systems. Partial budget analysis showed that the cost of producing maize or soybean is 20–29% cheaper with NT systems and gives higher returns to labor compared to CT practice. Benefit-to-cost ratios also show that NT cropping systems are more profitable than CT systems. We conclude that with time, implementation of CA practices involving NT, crop rotation, intercropping of maize and soybean along with crop residue retention presents a win–win scenario due to improved crop yield, increased economic return, and trends of increasing soil fertility. The biggest challenge, however, remains with producing enough biomass and retaining same on the field.
Smallholder farming dominates agriculture in Sub-Saharan African (SSA) operating on less than 2 hectares in total land holding. These are the farmers that supply the urban population with food as well as contribute to the national economies of their individual countries. Yet, smallholder agriculture is constrained by many inter-related factors including low soil fertility, frequent dry spells, drought and unsustainable management practices. Traditional agricultural practices have diminished soil productivity to the extent that many agricultural soils are depleted of nutrients and unable to naturally sustain crop productivity. In the coming decades, a crucial challenge for agriculture in SSA will be meeting food demands without undermining further the environment. Increasing productivity and economic returns to smallholder farming in a sustainable manner is a central challenge to achieving global poverty reduction and environmental management objectives (
In Eastern and Southern Africa, considerable research has been done on CA with variable impacts on crop yield reported. In Malawi, no-till and residue retention increased maize yields in two out of five districts after 3 years (
In Northern Ghana, continuous cropping and inadequate replacement of nutrients removed in harvested materials, or on site burning of crop residues, and through erosion have hastened soil degradation. Besides low soil fertility, drought, erratic rainfall, and climate change are frequently mentioned by farmers’ as constraints to crop production. One available solution to rebuilding the degraded soils and mitigating the effects of low or erratic rainfall is the development of conservation agricultural practices (CAPs) in intensively managed cropping systems. The goals of such a cropping system must be to increase ecosystem services while simultaneously increasing crop yields and subsequent profitability at the farm level. Improving ecosystem services, with a focus on soil quality, will require the adoption of intensive crop rotations that employ CAPs such as legumes to fix nitrogen, reduced tillage, practices that maintain as much crop residue in the system as possible and integrated nutrient, water and pest management practices. Very little research has been done to illustrate the effects of intensive cropping systems, the use of legumes to fix nitrogen, and the impact of conservation tillage practices on soil quality and crop productivity in Northern Ghana. The objective of this study was to evaluate the short term effects of CAPs that are based on minimum tillage, retention of crop residue, and crop rotation on soil quality, cropping system productivity and profitability of smallholder farmers in Northern Ghana.
The experiments were conducted during the 2010 to 2013 cropping seasons at Nyoli, a farming community located approximately 38 km Southwest of Wa (9°45′ N and 2°30′ W) in the Upper West Region of Ghana. The area has a mono-modal rainfall pattern of about 5–6 months beginning from May to October, with a long term mean annual rainfall of 1026 mm. During the dry season (November–April), the study area is under the influence of the dry south-eastern trade winds (harmattan). The natural vegetation is Guinea Savanna. The major soil type on which agriculture is practiced falls on Ferric lixisols (FAO) or Alfisols (USDA) (
In order to make technology development and dissemination demand driven and farmer centered, we carried out participatory technology development (PTD) workshops in the community before the start of the study. The purpose of the PTD workshops was to document the community’s livelihoods, major crops cultivated and cropping systems, indigenous CAPs, perceptions of CA, constraints to production, and coping strategies. Details of the baseline survey were published by
The mother trial was conducted on-farm but was managed by researchers. Treatments were a factorial combination of three tillage methods and three cropping systems. Tillage systems were CT using tractor to plow the land, manual tillage (MT) using hoes (farmer’s practice) and NT. In the NT treatment, after the first rains, annual and perennial weeds were killed by 2.5 l ha-1 of glyphosate [
To foster and advance the rapid adoption of CAPs by farmers, 12 farmers’ tested a sub-set of the mother trial treatments in their fields (fully managed by farmers). The baby trials treatments were a factorial combination of two tillage systems (conventional and no-till), and two cropping systems (continuous maize cropping and soybean–maize annual rotation). In the CT treatment, the plots were disk plowed using tractor while in the NT plots glyphosate was applied to kill all vegetation before sowing into the trash using cutlasses. The experimental design was randomized complete block with farmers as replicates. Each treatment plot size was 50 m × 20 m.
Initial soil samples were collected in 2010 at the 0–0.15, 0.15–0.30, and 0–0.30 m soil depth of each treatment plot of the mother trial and farmers’ fields (baby trials) for determination of texture, soil pH, SOC, total soil nitrogen (TSN) and mineral nitrogen prior to the establishment of the experiments. In May 2014, soil samples were taken again for SOC, TSN, and mineral N contents analyses at the soil depth intervals of 0–0.15 and 0.15–0.30 m. Using a soil auger, 10 cores per plot were taken and bulked to make a composite sample. The samples were air dried and a portion used for the determination of soil texture. The remaining soil samples were ground and sieved to 2 mm for determination of pH, SOC, and TSN. Particle size distribution was determined by the hydrometer method. Soil bulk density was measured in 2010 and 2014 by taking soil samples from the 0–0.10 m soil depth using metal core samplers of known weight and volume. Soil bulk density was determined by taking undisturbed soil cores, oven drying at 105°C for 48 h. Bulk density was calculated as mass of oven dry soil core divided by volume of the core (
The mother trial was managed by researchers with the support of the local farmers in carrying out operations such as sowing, weeding, fertilizer application and harvesting. The baby trials were managed by farmers themselves with technical support from researchers and the village extension agent. In both mother and baby trials, improved maize (Zea
At final harvest each year in the mother trial, maize ears from the middle four rows (90 m2) of each plot were harvested for grain yield assessment. For intercrops, the inner two rows (45 m2) of each crop were harvested for grain yield assessment. Aboveground maize crop residue was estimated by cutting and weighing all the stover from each plot after all maize ears were removed. A sub-sample of plants was taken weighed and oven dried at 70°C until constant weight. Sample dry weights were used to convert total maize stover from each plot to dry matter on an area basis. The remaining maize stover was left on the plots as mulch after weighing. For soybeans, all the plants were pulled off by hand, placed on a tarpaulin and threshed and grain yield determined. In the mother trial, the stover was uniformly spread on the soil surface of each plot. After threshing of soybean on tarpaulins, the residue was returned to the respective plots. In the baby trials, maize ears from the middle four rows (150 m2) of each treatment plot were harvested for grain yield assessment. The ears were air dried, shelled, and the grain weighed. For soybean, plants from the whole plot (500 m2) were harvested, air dried on bare ground, threshed manually and the grain weighed. Aboveground maize crop residue was assessed on five farmers’ fields as described for the mother trial. Farmers’ were encouraged to also leave the maize crop residues on the plots. Soybean crop residue could not be assessed because of the method of harvesting and processing for grain. Daily rainfall was measured with a rainfall gauge installed in the village.
Costs and benefits of each CA practice were compared using partial budgeting which included only costs and benefits. The costs included land preparation either by tractor or herbicide, fertilizers, and labor costs for sowing, weeding, application of herbicide and fertilizer. The gross margin (
where
All agronomic data from the mother trial were analyzed using a two factor (tillage and cropping systems) split-plot design with Duncan’s Multiple Range Test (DMRT) at 5% level of significance for separation of means. Agronomic data from the baby trials (farmers’ fields) were analyzed as two factors randomized complete block design with 12 farmers’ fields as replicates. Soil carbon, total nitrogen, and mineral nitrogen data from both mother and baby trials were analyzed as three factors (tillage, cropping system, and soil depth) randomized complete block designs. All ANOVA was done in SigmaPlot 11.0 statistical package. All data passed the normality and homogeneity of variances test (see Supplementary Material Data Sheet
Total rainfall and its distribution within the season varied from year-to-year (
Rainfall distribution during the growing season from 2010 to 2013.
Measurements made in 2014 showed significant differences between tillage systems in bulk density in the mother trial. NT increased bulk density compared to MT and CT practices (
Soil bulk density (g cm-3) as affected by tillage and cropping system in 2014.
Cropping system |
|||||
---|---|---|---|---|---|
Experiment | Tillage system | CMZ | SB–MZ | SB/MZ | Mean |
Mother trial site | CT | 1.50a | 1.52a | 1.45a | 1.49A |
MT | 1.62a | 1.65a | 1.51a | 1.59AB | |
NT | 1.66a | 1.79a | 1.68a | 1.71B | |
Mean | 1.59a | 1.65a | 1.54a | ||
Baby trials ( |
CT | 1.56a | 1.50a | 1.53A | |
NT | 1.69a | 1.66a | 1.68B | ||
Mean | 1.63a | 1.58a |
In the mother trial, there was a significant (
Soil organic carbon, total nitrogen, and mineral nitrogen averaged across soil layers, as affected by tillage and cropping system in 2014 in the mother trial.
Cropping system |
||||
---|---|---|---|---|
Tillage system | Sole maize | SB–MZ | SB/MZ | Mean |
CT | 3.42aA | 4.26bA | 4.82acA | 4.17A |
MT | 4.14aB | 5.29aA | 4.52aAB | 4.65A |
NT | 5.40aAB | 5.39bA | 5.20bcB | 5.33B |
Mean | 4.32a | 4.98b | 4.85b | |
CT | 0.37aA | 0.41bA | 0.43bA | 0.40A |
MT | 0.54aA | 0.62bA | 0.64bA | 0.60B |
NT | 0.59aA | 0.71bA | 0.66bA | 0.65B |
Mean | 0.50a | 0.58b | 0.58b | |
CT | 20.3aA | 26.6bA | 24.0bA | 23.6A |
MT | 40.5acA | 33.8bB | 32.2cA | 35.5B |
NT | 35.1aA | 51.1bcB | 47.4cA | 44.5C |
Mean | 31.9a | 37.2a | 34.5a |
Total soil N content followed a similar trend as SOC. There were significant main effects of tillage and cropping system on TSN (
There was significant (
There was no significant differences between tillage or cropping systems on the amount of crop residues produced and returned to the soil in 2010 (
Tillage and cropping system effects on maize crop residues returned to the soil in
In 2010, which was the first year of the experiment, there was no rotation effect and so results are presented for maize grain yield of sole maize and soybean/maize intercrop and soybean grain yield from sole soybean and soybean/maize intercrop. As with crop residue production, there was no significant interaction of tillage and cropping system on maize grain yield (
Tillage and cropping system effects on grain yields of maize
In 2011, there were no differences between tillage or cropping systems or their interaction on maize grain yield although maize following soybean tended to be higher than sole or intercropped maize (
Tillage and cropping system effect on maize grain yield in
Averaged across cropping systems, NT resulted in significantly higher bulk density compared to CT (
Soil organic carbon, total nitrogen, and mineral nitrogen contents averaged over farmers’ fields in 2014.
Cropping system |
|||
---|---|---|---|
Tillage system | CMZ | SB–MZ | Mean |
CT | 3.68aA | 4.02aA | 3.85A |
NT | 4.04aA | 3.90aA | 3.97A |
Mean | 3.86a | 3.96a | |
CT | 0.33aA | 0.36aA | 0.34A |
NT | 0.36aA | 0.35aA | 0.35A |
Mean | 0.34a | 0.35a | |
CT | 20.6aA | 23.0aA | 21.8A |
NT | 20.3aA | 23.1aA | 21.7A |
Mean | 20.5a | 23.0a |
In 2010, sole maize crop residue produced ranged from 520 to 2180 kg ha-1 in CT plots and from 580 to 2240 kg ha-1 in NT plots. Averaged for all farms, there was no significant difference between tillage systems in maize crop residue production (
Tillage and cropping systems effect on amount of maize crop residues produced and returned to the soil in the baby trials during
As expected in on-farm trials, there was wide range in maize and soybean grain yield. In 2010 season, maize grain yields on farmers’ fields ranged from 520 to 2700 kg ha-1 under CT and from 400 to 1820 kg ha-1 with NT. Averaged across farms, CT produced significantly higher maize grain yields compared to NT, translating to 23% more yield than in NT (
Tillage effects on sole maize
Soybean grain yields ranged from 180 to 2257 kg ha-1 and from 298 to 3000 kg ha-1 with CT and NT, respectively, in 2010 cropping season. There was no difference between tillage systems in soybean grain yields when averaged for all farms (
In 2011 and 2013 seasons, averaged across farms, CT produced significantly higher maize grain yield compared to NT (
Tillage and cropping system effect on maize grain yield in the baby trials during
Cost-benefit analyses averaged across farmers’ fields for each year are given in
Comparison of conventional and no-tillage cost and benefits for smallholder farmers’ maize and soybean production from 2010 to 2013 cropping seasons in Nyoli, Ghana.
Maize | Soybean–maize | |||
---|---|---|---|---|
monocropping |
annual rotation | |||
Costs | CT | NT | CT | NT |
Labor | 60.54 | 58.48 | 112.69 | 112.69 |
Purchased inputs | 318.54 | 242.18 | 103.20 | 4059 |
Total variable cost | 379.09 | 300.66 | 215.89 | 153.29 |
Revenue (US$) | 462.94 | 356.33 | 432.89 | 417.86 |
Gross margin (US$) | 83.85 | 55.67 | 217.00 | 264.58 |
Benefit/cost ratio | 0.22 | 0.19 | 1.01 | 1.73 |
Returns to labor | 7.65 | 6.09 | 3.84 | 3.71 |
Labor productivity | 21.57 | 16.60 | 20.17 | 19.47 |
Labor | 59.43 | 59.43 | 116.28 | 116.28 |
Purchased inputs | 312.02 | 229.98 | 109.82 | 51.03 |
Total variable cost | 371.45 | 289.41 | 226.10 | 167.31 |
Revenue (US$) | 689.66 | 445.09 | 739.38 | 453.01 |
Gross margin (US$) | 318.21 | 155.69 | 513.28 | 285.69 |
Benefit/cost ratio | 0.86 | 0.54 | 2.27 | 1.71 |
Returns to labor | 11.60 | 7.49 | 6.36 | 3.90 |
Labor productivity | 32.95 | 21.67 | 34.68 | 21.25 |
Labor | 66.56 | 66.04 | 105.98 | 105.98 |
Purchased inputs | 261.56 | 203.84 | 98.80 | 41.08 |
Total variable cost | 328.12 | 269.88 | 204.78 | 147.06 |
Revenue (US$) | 477.26 | 299.60 | 412.09 | 310.42 |
Gross margin (US$) | 149.14 | 29.72 | 207.31 | 163.36 |
Benefit/cost ratio | 0.45 | 0.11 | 1.01 | 1.11 |
Returns to labor | 7.17 | 4.54 | 3.89 | 2.93 |
Labor productivity | 29.42 | 18.47 | 25.40 | 19.13 |
Labor | 72.36 | 68.24 | 102.50 | 93.24 |
Purchased inputs | 463.00 | 178.62 | 96.18 | 45.34 |
Total variable cost | 535.36 | 246.86 | 198.68 | 138.68 |
Revenue (US$) | 557.89 | 335.21 | 360.22 | 347.71 |
Gross margin (US$) | 22.53 | 88.35 | 161.54 | 209.03 |
Benefit/cost ratio | 0.04 | 0.36 | 0.81 | 1.51 |
Returns to labor | 7.71 | 4.91 | 3.51 | 3.73 |
Labor productivity | 31.23 | 18.77 | 20.17 | 19.47 |
In 2010, the average variable cost per hectare of producing soybeans was estimated as $216 and $153 for CT and NT, respectively. This implies a reduction in cost of production per hectare of about 29%. The gross margins per hectare for CT and NT are, respectively, estimated to be $217 and $265. The results show an increase of about 22% in gross margin for NT compared to CT. The benefit-cost ratio per hectare for CT and NT are about 1.00 and 1.7, respectively. This implies NT under farmers’ condition is more profitable for soybeans than CT. the returns to labor for both CT and NT are higher with labor productivity also higher for both technologies.
In 2011, total variable costs of continuous maize production per hectare were estimated to be $371 and $289 for CT and NT, respectively. This represents a production cost reduction of 22% for NT compared to CT. The gross margin for continuous maize production with CT is also higher than with NT. However, the benefit cost ratio for both CT and NT are less than unity. Total variable costs of production of maize following soybean in rotation in 2011 were estimated to be $226 and $167 for CT and NT, respectively. This represents a 26% reduction in cost of production per hectare for NT. Gross margins are estimated to be $513 and $286 per hectare for CT and NT, respectively. The benefit-cost ratios for CT and NT are both greater than 1. The results also show higher returns to labor and labor productivity.
In 2012 cropping season, the average costs of production per hectare of maize were estimated to be about $328 and $270 for CT and NT, respectively. This represents about 18% reduction in cost of production with NT. The gross margin for CT is, however, 80% higher than with NT. The benefit-cost ratio for CT and NT are, however, less than 1. Returns to labor and labor productivity are, however, high for the tillage systems. The total variable cost of production per hectare of soybean with CT and NT were estimated to be about $205 and $147, respectively. This represents a 28% reduction in cost of production per hectare for NT. Gross margins on the other hand were 21% higher with CT compared to NT. The benefit-cost ratio for both CT and NT are slightly greater than 1.
In 2013, total variable costs of continuous maize production per hectare with CT and NT were estimated to be $535 and $247, respectively. The reduction per hectare is about 53% for NT. The gross margins for CT and NT per hectare were estimated to be $22 and $88, respectively. This represents a 200% increase in gross margins for NT compared to CT. However, the benefit-cost ratios for both tillage systems are less than 1. Total variable costs of maize following soybean production were estimated to be $199 and $139, respectively, for CT and NT. This represents a 30% reduction in cost of production per hectare for NT compared to CT. The benefit-cost ratio for NT is greater than 1 but less than 1 for CT.
Retention of crop residue on the soil surface as mulch is an essential component of CA intended to increase carbon inputs and enhance ecosystems benefits such as soil fertility, improved soil water relations, and biological properties (
In the researcher managed mother trial, our results show that there were no significant differences between the CA practices of MT and NT and CT in maize grain yield in the first three seasons although CT tended to have higher absolute values. Averaged across cropping systems, CT increased maize grain yield by 11 and 29% in 2010, 22 and 15% in 2011 season, and 41 and 37% in 2012 season compared to MT and NT, respectively, in each year. In 2013, CT had the largest impact on maize yields, increasing yields over MT and NT by 41 and 49%. These results agree with previous studies in southern and eastern Africa which found either no yield benefits of CA over CT in the initial years (
Cropping system had no significant impact on maize grain yield in all years although maize following soybean tended to have higher yields. The yield advantages of crop rotation over continuous maize cropping were 243, 270, and 215 kg ha-1 in 2011 while in 2013 season, yield advantages were 431, 192, 182 kg ha-1 for CT, MT, and NT, respectively, in each year. The small but insignificant yield advantage of crop rotation may be attributed to fixation of atmospheric N and other rotation effects. Inclusion of legumes in a rotation, either sole-cropped or intercropped, can increase maize yields, soil N and fertilizer-use efficiency (
In contrast to the researcher managed mother trial, CT had the greatest impact on maize and soybean yields in the farmer managed baby trials irrespective of cropping system, increasing yields over NT in all 4 years. Crop rotation had no effect on yields irrespective of the tillage system. There were small but insignificant yield advantages of crop rotation over monocropping with CT but was not consistent with NT. The lower yields with no-till in farmers’ fields was largely due to lack of experience by some farmers in the initial years and ineffective herbicide application leading to competition from weeds. Additionally, no-till systems without adequate residue retention can decrease crop yields compared to CT systems (
Conservation agriculture influences soil physical properties such as bulk density and porosity as well as chemical and biological properties (
Cropping system can affect soil C by increased biomass production and carbon inputs from the different crops in the system, among others (
In the farmers’ fields (baby trials), the difference in either SOC or total N content between no-till and CT plots were not significant after 4 years. However, the data showed an increasing trend in both SOC and total N contents with NT soybean–maize rotation and intercropping compared with CT plots. Statistical insignificance in SOC and TSN contents in response to tillage and cropping systems was likely due to the low crop residue production coupled with removal of all soybean plants from the field for threshing. In farmers’ fields, since crop residues were left in the field after each harvest and not protected, a large portion would be consumed by free roaming livestock, termites and other soil arthropods during the long dry season. Consequently the amount of residue being incorporated at the beginning of the rainy season may have been insufficient to produce a measurable beneficial effect.
There must be positive net economic or other benefits to induce a farmer to use a technology. Farmers are most likely to adopt CA when it reduces production costs and/or increases yields, and also when it reduces or at least does not increase risk. In all cropping seasons and cropping systems, total variable costs of production of either maize or soybean were 20–29% lower with NT compared with CT due to lower cost of herbicide for land preparation and weed control and higher cost of plowing. Even though cost of production was lower with NT, average gross benefits for NT sole maize production were lower in the first 3 years when compared to CT. In the fourth year, gross benefit for NT maize production was higher than CT maize production. However, the benefit-to-cost ratios show that both CT and NT continuous maize production were not profitable. For the soybean–maize rotation cropping system, the benefit-to-cost ratios show that in 2010 and 2012, NT sole soybean was more profitable than CT sole soybean. For maize following soybean in the rotation, NT was less profitable in 2011 but more profitable in 2013 when compared to CT. The higher gross margins and profitability of sole soybean when compared to sole maize was because of ready market and higher price offered by the NGO that introduced the crop to the farmers. In 2011 and 2013, CT and NT maize following soybean in the rotation were 2–3 times more profitable than continuous maize cropping under either conventional or NT production. This was due to higher grain yield as a result of the legume benefit to the succeeding maize crop. Hence, it appears that NT is profitable over time for continuous maize and maize following soybean in the rotation.
The impact of NT, CT and cropping systems on soil quality and crop productivity was measured during four seasons under researcher and farmer managed conditions. In the researcher managed mother trial, the results showed that the CA practices of NT, residue retention and crop rotation/intercropping can maintain higher soil quality compared to conventional practices. The higher SOC and TNC contents under NT suggest that switching from conventional moldboard plowing to NT can maintain or improve SOC. No significant increase in soil quality indicators was detected in farmers’ fields mainly due to insufficient biomass production, difficulty in residue retention and the practice of removing all soybean plants for threshing outside the fields. Our results showed that in the researcher managed mother trial, tillage and cropping systems did not have a significant impact on maize or soybean yields in the first three seasons. Crop rotation had the greatest impact on maize yields in 2013 with CT rotations increasing maize yields compared to NT maize. In the farmers’ managed trials, CT crop rotation increased maize and soybean yield compared with CA practice of NT and crop rotation. The results suggests that rotation should be an integral part of farmers’ cropping practices and thus for the full benefits of CA to be achieved farmers need to move from continuous mono-cropping to rotations that include legumes. Although our results show a yield advantage of CT cropping systems over NT cropping systems, partial budget analysis showed that the cost of producing maize or soybean is cheaper with NT systems and earns more than double returns to labor than with CT practice. Benefit-to-cost ratios also show that continuous NT soybean and NT soybean–maize rotations are more profitable than CT systems. We conclude that with time, implementation of CA practices involving crop rotation and intercropping of maize and soybean and NT along with crop residue retention presents a win-win scenario due to improved crop yield, increased economic return, and trends of increasing soil fertility. Thus farmers are more likely to adopt NT cropping systems than CT cropping systems. Indeed adoption studies carried out in 2014 showed that 60% of farmers who participated in the on-farm trials adopted the NT and soybean–maize rotation with crop residue retention. For non-participating farmers, the adoption rate was 50%. The average acreage under no-till adoption was found to be 3 acres among all the adopters (
JN, conceived, designed and conducted the experiment and wrote the manuscript. GM, conducted the experiment and contributed to writing manuscript. IY, conducted economic analysis and contributed to writing manuscript. PP, conceived and designed the experiment, and edited the manuscript.
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
We would like to thank the smallholder farmers of Nyoli community for their provision of land and assistance with routine operations in this project. We also thank Messers Hashim Ibrahim, Mohammed Naafiu, Clement Daatare, and Godwin Opoku for technical support.
The Supplementary Material for this article can be found online at: