Diversifying conservation agriculture and conventional tillage cropping systems to improve the wellbeing of smallholder farmers in Malawi

Agricultural Systems 171 (2019) 23–35

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Agricultural Systems journal homepage: www.elsevier.com/locate/agsy

Diversifying conservation agriculture and conventional tillage cropping systems to improve the wellbeing of smallholder farmers in Malawi

T

⁎

Dan TerAvesta, , Philip R. Wandschneiderb, Christian Thierfelderc, John P. Reganolda a

Department of Crop and Soil Sciences, Washington State University, P.O. Box 646420, Pullman, WA 99164-6420, USA School of Economic Sciences, Washington State University, P.O. Box 646210, Pullman, WA 99164-6210, USA c CIMMYT, P.O. Box MP 163, Mount Pleasant, Harare, Zimbabwe b

A R T I C LE I N FO

A B S T R A C T

Keywords: Conservation agriculture Crop rotation Smallholder wellbeing Tillage Residue retention

Food production and the wellbeing of smallholder farmers are constrained by their limited financial resources, poor market access, and inadequate institutional support in southern and eastern Africa. Conservation agriculture (CA)–minimal soil disturbance, year-round ground cover, and diverse crop rotations–is being promoted to sustainably boost crop production, increase household income, and diversify diets for better nutrition. In this study, three cropping systems–continuous no-till maize, CA rotation, and conventional tillage rotation–were established on smallholder farms in the Nkhotakota and Dowa districts, two distinct agroecological zones in Malawi. Diverse three-year crop rotations in CA and conventional tillage systems included the alternative food crops sweet potato and cassava and the grain legumes common bean, soybean, cowpea, and pigeonpea. The effects of cropping system on labor use and financial returns, which served as a rough indicator of feasibility and farmer wellbeing, were analyzed for three years from 2011 to 2014. Over the three years of the study, continuous no-till maize produced the greatest gross and net revenues, despite also having greater production costs than CA and conventional systems. Although substantially less profitable than continuous no-till maize, the diversified CA and conventional tillage rotations were profitable for smallholder farmers, partially due to lower production costs. Sensitivity analysis was used to test the robustness of each cropping system under varying labor, input, and output price scenarios. Altering farmgate prices had the greatest impact on profitability, regardless of the crop grown. The input and output prices for maize were stable over the course of the study so that continuous no-till maize was the most robust cropping system. In contrast, high input cost and output price variability for alternative crops increased risk compared to maize, which may reduce their appeal to smallholder farmers. Reducing the risk of conservation agriculture rotations could provide smallholder farmers with more diversified diets and greater ecosystem services, such as greater rainwater infiltration and storage to withstand dry spells. Based on the results of this study, policies that reduce input price variability and increase farmgate prices of alternative food crops would have the greatest impact on the adoption of diverse crop rotations in Malawi.

1. Introduction Sustainable agriculture is a complex and multidimensional subject in any setting. It is especially critical for the viability of African smallholder farms and the well-being of these households. Generally, the issues and decision makers are different at various levels–e.g., from field and farm to landscape, nation, and world. Recently, the discussion at global levels (especially among researchers and decision-makers) has centered on the possibilities of combining increased agricultural production with enhancing ecological dimensions, also known as sustainable intensification (SI) (Tilman et al., 2011). The SI approach promises

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to address local farm viability while tackling food and ecosystems problems at all levels. While not clearly defined, the general principles of SI are to emphasize increased production on existing lands rather than expanding acreage, reducing negative environmental impacts, and adopting more ecological principles in production agriculture (Pretty et al., 2011; Royal Society, 2009). Food and ecosystem security problems are particularly acute in subSaharan Africa (van Ittersum et al., 2016; Lipper et al., 2014). To improve the wellbeing of smallholder farmers in sub-Saharan Africa, conservation agriculture (CA)–minimal soil disturbance, year-round ground cover, and diverse crop rotations (FAO, 2002) –is being

Corresponding author. E-mail address: [email protected] (D. TerAvest).

https://doi.org/10.1016/j.agsy.2019.01.004 Received 4 August 2018; Received in revised form 14 January 2019; Accepted 16 January 2019 0308-521X/ © 2019 Elsevier Ltd. All rights reserved.

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level benefits (income) imply positive impacts on household wellbeing and farm viability. Positive farm-level outcomes predict potential for farmer adoption. The hypothesis of this study was that smallholder farmers would improve their profitability and wellbeing by shifting from continuous maize-based no-till cropping systems to diverse CA or conventional tillage rotations. To test our hypothesis, we established three cropping systems–continuous no-till maize, CA rotation, and conventional tillage rotation–on smallholder farms in the Nkhotakota and Dowa districts, two distinct agroecological zones in Malawi. Three-year maize-based crop rotations in CA and conventional tillage included two years of different combinations of sweet potato, cassava, common bean, cowpea, soybean, and pigeonpea and one year of maize. The effects of cropping system on labor use and financial returns, which served as a rough indicator of farmer wellbeing, were analyzed for three years from 2011 to 2014. We addressed our research hypothesis using two economic analyses: (i) a financial analysis evaluating gross returns, total costs, and gross margins of each of the three cropping systems assuming prices were explicit; and (ii) a sensitivity analysis, sometimes referred to as a “whatif” analysis, using different input costs and output prices to test their effect on profitability, since both crop prices and agro-climatological conditions can vary each growing season. Such economic analyses not only measure farmer profitability and wellbeing but can also show what might or might not be adopted as well as help reveal what practices contribute to social goals and what policy “nudges” might encourage adoption of desired practices.

promoted by international and non-governmental organizations as a strategy of sustainable intensification (Corbeels et al., 2013; Mafongoya et al., 2006; Wall et al., 2013). When smallholder farmers in southern and eastern Africa have adopted CA principles, most have adopted no-till and residue retention, with few adopting diverse crop rotations (Mazvimavi and Twomlow, 2009; Ngwira et al., 2014). However, CA tends to have a greater impact on crop yields when all three CA principles are implemented (Pittelkow et al., 2014). Adoption of diverse crop rotations, in either CA or conventional tillage systems, will require cropping systems that take into account smallholder farmers' endowment of land, labor, and financial resources and their output goals. Usually, the first priority of smallholder farmers is to produce sufficient food for household consumption (Pannell et al., 2014). This can limit their ability to divert land to alternative crops in rotation when landholdings are small (Dowswell et al., 1996; Ellis et al., 2003; Thierfelder et al., 2014). Even if crop rotations increase yields in the cereal phase of rotation, these benefits may be offset by reduced crop production or revenue generation in the non-cereal phase of the rotation, making rotations less attractive to smallholder farmers (Pannell et al., 2014; Thierfelder et al., 2013). Besides their desired output mix (subsistence versus marketable outputs), smallholder farmers' choice of alternative crops to rotate with maize will be influenced by their resource availability, production costs, access to markets for inputs and outputs, availability of extension services for rotation crops, and the potential for rotation crops to improve soil fertility (Bezner-Kerr et al., 2007; Lukanu et al., 2009; Zingore et al., 2009). Zingore et al., (2009) found that smallholder farmers with fewer resources were more likely to choose crops with low-input requirements, even if they had poor market prices. Conversely, farmers with greater access to resources, who were also less risk averse, were willing to pay higher production costs to grow highvalue cash crops (Zingore et al., 2009). Grain legumes are a common choice for smallholder farmers who adopt rotations, despite lower grain yields, as they help increase soil N, improve household diets and provide marketable grains, with market prices that are often 2–4 times higher than maize prices (Bezner-Kerr et al., 2007; Franke et al., 2014; Thierfelder et al., 2014). The aforementioned studies tend to focus on the farm and field level, without much consideration for global level goals and strategies. In fact, discussions and literature of SI and CA at global and local levels can be independent and sometimes mutually oblivious. Yet, global goals (food security and global ecosystem health) cannot be met without compatible local level goals and decisions. There are several possible mechanisms for linking these levels. From the top down, researchers and agencies have attempted to list and embed appropriate farm-level practices within global strategies. Thus, farm-level strategies, such as conservation agriculture, agroforestry, and other cropping system improvements, are placed within the overall SI strategy (Pretty et al., 2011; Royal Society, 2009). From this top level, farm-level practices can be seen as the tools for implementing global strategies. However, listing ideal practices does not make them happen. Field- and farm-level actions are the domain of the farmers. Research in SI at the field and farm level focuses on cultivation practices, local economics, yield potential, and environmental conditions rather than global strategies. Farmer decisions can be influenced by the policies created by top levels, but some operational linkage is required. In this paper we contribute to this linkage by applying an economic framework to a detailed, three-year study of smallholder farm practices in two locations of Malawi, where about 65% of the population works in the agricultural sector and about 84% of the population lives in rural areas (World Bank, 2018). Economic values can be a link between farmlevel decisions and goals and national and global goals and policies. Economic analyses can indicate potential farm viability and household wellbeing and provide operational information relevant to social goals and decisions. Specifically, prices (economic values) at the local level measure the benefits and costs at the farm level, and positive net farm-

2. Materials and methods 2.1. Experimental sites The field work that underpins this economic analysis was carried out during the 2011/12, 2012/13, and 2013/14 growing seasons in the Central region of Malawi, a subtropical country in southeastern Africa with a sub-humid climate. Maize (Zea mays L.) is the predominant food crop grown on up to 80% of the land (Dowswell et al., 1996). Additional important food, legume, and cash crops grown in the region include cassava (Manihot esculenta Crantz), sweet potato (Ipomea batatas L.), soybean (Glycine max L.), cowpea (Vigna unguiculata L. Walp.), common bean (Phaseolus vulgaris L.), groundnut (Arachis hypogaea L.), pigeonpea (Cajanus cajan L. Millsp.), tobacco (Nicotiana tabacum L.), cotton (Gossypium hirsutum L.), and rice (Oryza sativa L.). Research sites were established in the districts of Nkhotakota (−13.06 S, 34.3 E; Altitude: 498 masl), near Nkhotakota town, and Dowa (−13.47 S, 33.71 E; Altitude: 1146 masl), in Kachipande village (Fig. 1). During the study, daily temperatures averaged 26.6 °C at the Nkhotakota research site and 21 °C at the Dowa research site. Rainfall distribution at the research sites is unimodal, lasting from November to April. The Nkhotakota research site received 1369 mm, 1809 mm, and 1172 mm of rainfall in 2011/12, 2012/13, and 2013/14 (November 1 to October 31), respectively. The Dowa research site received 801 mm, 720 mm, and 981 mm of rainfall in 2011/12, 2012/13, and 2013/14, respectively. At the Nkhotakota site, the soil was classified as a coarsetextured haplic Luvisol and at the Dowa site, the soil was classified as a coarse-textured haplic Lixisols (WRB, 1998). 2.2. Experimental design Research plots were established on four smallholder farms in each district in November 2011. Representative smallholder farms were identified with the help of Total LandCare, a regional non-governmental organization headquartered in Malawi (www.totallandcare. org). On each farm three plots were established: continuous no-till maize (NTM), conservation agriculture rotation (CAR), and conventional tillage rotation (CTR). The three plots on each farm were chosen 24

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2.3. Economic analyses 2.3.1. Wellbeing and notional financial analysis The proper measure of success at the farm level is contribution to the farm household's wellbeing. Measures of wellbeing can be divided into two general approaches: subjective and material. Subjective wellbeing is often equated with life satisfaction or happiness. Material wellbeing is generally associated with the quantity and quality of physical goods and services. Clearly these are related, having a full stomach and a home protected from the elements are generally considered part of a good life. Studies have repeatedly found that across nations there is a significant relationship between how rich a nation is and how happy its citizens are (Diener and Biswas-Diener, 2002). Within a given country, the relationship between income and happiness is generally small if the country is wealthy and larger if the country is poorer (Diener and Biswas-Diener, 2002). This may be due in part to the ability of greater income in poorer countries to help meet basic needs. In sum, income is a direct measure of material well-being, and an indirect measure of life satisfaction (via provision of needs). Here we use the economic concept of income to measure wellbeing. The smallholder farms in this study are only partially integrated into the market economy and do not have explicit market prices for many of the inputs and outputs. The values for marketed outputs and inputs are starting points even where output items are consumed by the home rather than sold, an example of using “related market goods” as value proxies. A greater challenge is the value of labor, probably the most common unpriced farm input. Here we use the opportunity cost principle. Where the (family) farm worker has replaced a paid laborer, the market analogy can again be used. Alternatively, the value that labor could have earned off-farm can be used to proxy the value of on-farm labor, where the (family) farm worker has foregone the opportunity to work off-farm. Another example of opportunity cost is that the use of post-harvest crop residues as mulch incurs the opportunity cost of giving up its use as cattle feed (and vice versa). Hence the cost of mulching with residue can be proxied by the value of equivalent feed. Since both economic values (prices) and agro-climatological conditions vary, we apply sensitivity analysis to our data. The results will be from a notional financial analysis–results that would be obtained if prices were explicit. The notional financial net revenue (profit) provides an indicator of feasibility and wellbeing because we assume a Malawian farmer, like any other enterprise manager, will endeavor to maximize “profits”. However, it is only an approximate indicator because the subsistence farmer will have a more complex goal function in which the physical dimensions of the output will matter. For instance, food should comprise a desired “diet” –a set of nutrients (carbohydrates, protein) and tastes that meet family goals. It is a rough indicator of wellbeing because it estimates the purchasing power available to the farmer in monetary equivalents. In fact, much of the returns are realized “in kind” as food or inputs for other household activities. Moreover, where farm families supply all of the labor, the total income of the farm family is the sum of the labor costs and net returns (alternatively, gross returns less purchased inputs). The value of using notional financial analysis is that it transforms results into common units (opportunity cost prices), allowing comparison of input and output prices across many different farm types.

Fig. 1. Map of Central Malawi. Includes Nkhotakota and Dowa field sites and the surrounding large towns.

so that they each had the same microclimate, slope, soil profile, and soil type (Reganold, 2013). Individual research plots were small–0.13 ha in Nkhotakota and 0.25 ha in Dowa–due to the already limited landholding size farmers typically possess in Malawi (Ellis et al., 2003). In the continuous no-till maize (NTM) treatment, maize was planted into the previous season's residue and weeds were chemically controlled with a mixture of Roundup® and Harness®. After planting, weeds were either hand-pulled or scrapped with hand hoes disturbing only the upper 1–2 cm of soil. The conservation agriculture rotations (CAR) were three years of cassava, cowpea, and maize in Nkhotakota and three years of sweet potato, bean, and maize in Dowa. Crops were usually planted into the previous season's residue and cassava and sweet potato were intercropped with pigeonpea. After planting, weeds were either hand-pulled or scrapped with hand hoes, disturbing only the upper 1–2 cm of soil. The conventional tillage rotations (CTR) were three years of cassava, soybean, and maize in Nkhotakota and three years of sweet potato, bean, and maize in Dowa. Prior to planting, most crop residues were either cleared or burned in situ. Weeds were controlled by hand-hoeing. At maturity grain and tubers were harvested from subplots and measured yields were extrapolated to an area basis. Grain and tuber subsamples were collected and oven-dried to determine total dry weight and normalize yields. Smallholder farmers in Malawi also harvest sweet potato, cassava, cowpea, and bean leaves for vegetables, remove cassava stems and sweet potato vines for transplanting materials, and harvest the woody portions of pigeonpea and cassava stems for fuel. Farmers recorded how often they harvested fresh leaves from the field and samples of leaf harvests were collected to determine dry weight. At harvest, all planting materials and firewood that was removed from the field was weighed and extrapolated to an area basis. In order to reduce risk to participating smallholder farmers, all inputs (seed and planting materials, fertilizer, herbicides) were provided to the farmers, while farmers provided all the necessary labor. Crop variety, plant spacing, planting date, and inorganic fertilizer applications are outlined in Table 1.

2.3.2. Costs, net benefits, and gross margins Labor costs were based on time. Some labor time was measured directly (e.g., planting, applying fertilizer, spraying herbicides and pesticides, and harvesting crops and firewood), while other time was determined through farmer interviews (e.g., cultivating ridges, laying out crop residue, and hand-weeding). Labor costs were based on Malawi's official minimum daily wage and converted from the Malawi kwacha to US dollars. The minimum daily wage was about $1.00 per 8h day ($1.02, $0.98, and $1.07, in years 1, 2 and 3, respectively). This rate was used as the base value for both hired casual and household 25

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Table 1 Crop, variety, planting date, plant spacing, and fertilizer application by plot and season in Nkhotakota and Dowa. District

Plot

Season

Crop

Variety

Planting Date

Plant spacing

Seeds per station

Fertilizer (kg N/P ha−1)

Nkhotakota

NTMa

2011/12 2012/13 2013/14 2011/12

Maize Maize Maize Cassava Pigeon Pea Cowpea Pigeon Peab Maize Cassava Soybean Maize Maize Maize Maize Sweet Potato Pigeon Pea Bean Maize Sweet Potato Bean Maize

DK 9089 DK 9089 DK 9089 Manyakola Mwaiwathu alimi IT82 E16

Dec. 19–21 Dec. 10–15, Dec. 16–18 Jan. 17–18

25 cm × 75 cm 25 cm × 75 cm 25 cm × 75 cm 90 cm × 90 cm 90 cm × 90 cm 15 cm × 37.5 cm

1 1 1 1 2 2

103/31c 103/31 103/31 21/19d

25 cm × 75 cm 90 cm × 90 cm 5 cm × 75 cm 25 cm × 75 cm 25 cm × 75 cm 25 cm × 75 cm 25 cm × 75 cm 30 cm × 90 cm 60 cm × 180 cm 15 cm × 60 cm 25 cm × 75 cm 30 cm × 90 cm 15 cm × 75 cm 25 cm × 75 cm

1 1 1 1 1 1 1 1 2 2 1 1 2 1

CAR

2012/13

CTR

Dowa

NTM

CAR

CTR

2013/14 2011/12 2012/13 2013/14 2011/12 2012/13 2013/14 2011/12 2012/13 2013/14 2011/12 2012/13 2013/14

DK 9089 Manyakola Nasoko DK 9089 DK 9089 DK 9089 DK 9089 Mugamba Mwaiwathu alimi Khulophete DK 9089 Mugamba Khulophete DK 9089

Feb. 18–20 Dec. 16–18 Jan. 17–18 Dec. 20–21 Dec. 16–18 Jan. 4–6 Dec. 17–19 Dec. 19–21 Jan. 23-Feb.3 Feb. 1–2 Dec. 19–21 Jan. 23–Feb.3 Feb. 1–2 Dec. 19–21

0/0 103/31 21/19 0/0 103/31 103/31 103/31 103/31 28/26 0/0 103/31 28/26 0/0 103/31

a

NTM = continuous no-till maize, CAR = conservation agriculture rotation, CTR = conventional tillage rotation. In November 2012, pigeon pea from 2011/12 was coppiced and allowed to grow a second year. c Fertilizer was split into a basal application of 23:21:0 + 4 s (34 kg N ha−1 and 31 kg of P ha−1) and a top-dress application of Urea (46:0:0) 4–5 weeks after planting (69 kg N ha−1). d Cassava and sweet potato were fertilized with 23:21:0 + 4 s at planting. b

labor. Since farm households provide 50–80% of the labor, this is primarily an opportunity cost measure. Market and market analogue prices were based on input and output price surveys conducted at agricultural retailers and markets in the communities near research plots as well as from markets and wholesale distributers in Lilongwe, the largest regional city and the capital of Malawi. Output price surveys for storable crops took place at harvest, 2 months after harvest, and in November, when most smallholder farmers sell any remaining produce in order to purchase inputs for the subsequent season. These prices were used directly for products sold and as opportunity cost based inferred values for output eaten or retained for seed. Prices for storable crops were based on prices at probable sale times and prices for non-storable crops were based on prices at harvest times. Storable crops in this study were maize, pigeonpea, bean, cowpea, soybean, and cassava. Most farmers “store” cassava by leaving it in the field until they are ready to sell or consume it. Non-storable outputs included sweet potato tubers, stems and vines used for planting materials. Finally, the prices (economic value) of nontraded goods, firewood, and green leaves harvested as vegetables were based on farmer interviews. Price means were used as base values and maximum and minimum prices were used for sensitivity analysis. Additional input costs included backpack sprayers for herbicide and pesticide application. Transport costs were calculated using farmer interviews and the cost of time required to transport inputs was calculated using the minimum daily wage. Financial returns to land and management were calculated using prices inferred as described above. Net revenue, labor productivity, and gross margins were calculated for each year and for each cropping system. Net revenue was calculated as gross revenue minus total production costs. Gross margins were calculated as a percent by dividing net revenue by gross revenue and were calculated both with and without incorporating the opportunity cost of labor into the total production costs. Gross margins are rough indicators of the “profit” rate but are “gross” since they leave out fixed costs and or labor and management costs. They are “returns” to the omitted cost factors. Labor productivity (LP) was calculated using the following equation, where GR is gross revenue, IC is total input costs, and LD is labor days ha−1 (Fagerstroem et al., 2001):

LP =

GR − IC LD

2.3.3. Sensitivity analysis Sensitivity analysis was conducted to test the robustness of each cropping system. Since each alternative crop–cassava, sweet potato, cowpea, soybean, and bean–was only grown for one season, actual crop yields may not reflect the yields that smallholder farmers would receive in a typical year. Yearly variations in climate and crop management would affect crop yields in CAR and CTR. To account for yield variations of alternative crops over time, financial returns were calculated using two alternative yield scenarios. One yield scenario assumed farmers received yields equal to Malawi's national yield averages. For cowpea, soybean, and bean, the mean of the national average yields from 2006 to 2013 was considered the national average (FAOSTAT database, 2008). For cassava, yields of 12,000 kg ha−1 are common for local cassava varieties, such as the variety grown in this study, when they are harvested after 15 months (Alene et al., 2013). This value was reduced by 25% to 9000 kg ha−1 to account for the early harvest of cassava tubers in this study, which were harvested after 10 months. An average yield of 10,200 kg ha−1 was used for sweet potato, based on the average yields for similar sweet potato varieties in Malawi as reported by Kathabwalika et al. (2013). The second yield scenario used the mean of observed and national average yields for each crop to take into account potential management effects. In both scenarios, production costs and the value of intercrops and co-products were not altered. The opportunity cost of labor, input prices, and output prices can vary depending on the time of the season and smallholder farmers' market access. Sensitivity analysis was conducted to test the effect of each of these factors on profitability. In the first scenario, labor price was increased to reflect higher labor costs that would result from hiring off-farm labor for planting, applying fertilizer, spraying herbicides, and hand-weeding during peak times of the growing season. The cost of hiring off-farm labor during these periods was recorded and was on average 65% higher than Malawi's minimum daily wage. The next two scenarios analyzed the effect of farmers paying either the minimum or maximum input price on profitability. The final two scenarios examined the effect of farmers receiving either the minimum or maximum output 26

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Table 2 Input costs ($ ha−1) by cropping system and year in Nkhotakota.

Year 1 Crops Seed Maize Cassava Pigeon pea Fertilizer 23:21:0 + 4 s 46:0:0 Herbicide Roundup Harness Transport Equipment Total input costs Year 2 Crops Seed Maize Cowpea Soybean Fertilizer 23:21:0 + 4 s 46:0:0 Herbicide/pesticide Roundup Dimethoate Transport Equipment Total input costs Year 3 Crops Seed Maize Fertilizer 23:21:0 + 4 s 46:0:0 Herbicide Roundup Harness Transport Equipment Total input costs

Unit

Unit

No-till maize

Size

Price

Units

Cost

Maize Kg Bundle Kg

1.68 1.43 1.73

25

50 kg 50 kg

34.03 34.03

3 3

L L

10.61 9.96

2.5 1

Conservation agriculture

Conventional tillage

Units

Units

Cost

Cassava Pigeon pea

Cost

Cassava

41.89 70 4

100.00 6.94

70

100.00

102.09 102.09

1.8

61.26

1.8

61.26

26.53 9.96 6.17 10.63 299.36

2.5

26.53

Maize

3.16 10.63 208.51 Cowpea Pigeon pea

kg kg kg

1.50 1.45 1.76

25

50 kg 50 kg

37.34 36.95

3 3

112.01 110.86

L 100 ml

10.03 4.93

2.5

25.09

3.16 164.42 Soybean

37.40 54

78.41 35

2.5 1

6.17 10.63 302.15 Maize

25.09 4.93 1.23 10.63 115.35

Maize

61.69

1.23 62.92 Maize

kg

1.83

25

45.73

25

45.73

25

45.73

50 kg 50 kg

39.71 37.97

3 3

119.13 113.90

3 3

119.13 113.90

3 3

119.13 113.90

L L

9.09 10.34

2.5 1

22.71 10.34 6.17 10.63 328.60

2.5 1

22.71 10.34 6.17 10.63 328.60

6.17

657.39 219.13

512.27 170.76

2011–2014 Total input costs Average input costs

930.11 310.04

284.93

sweet potato was planted. While bean seed costs were high, fertilizer was not used, so input costs were lower for bean plots compared to maize or sweet potato treatments. Adding costs for herbicides and equipment in the NTM and CAR treatments, their total input costs over three years were similar and 19–22% higher than CTR in Dowa. Table 4 presents labor costs for both locations and all three years. In Nkhotakota, NTM was more labor intensive than CAR and CTR in every year of the study. Conversely, in Dowa labor costs were similar across all cropping systems in years 1 and 3 and higher in NTM than CAR and CTR in year 2. Time spent hand-weeding was roughly the same for all three cropping systems in years 1 and 3. In year 2, hand-weeding CAR used less than half the labor required by NTM or CTR in Nkhotakota and weeding maize in Dowa required twice has much labor has weeding beans. The time required for each fertilizer application, plus more fertilizer applications, contributed to higher labor costs in NTM compared to CAR and CTR. Another major difference was the cost of cultivating ridges in CTR. Averaged across all cropping systems, total labor use and labor costs were lower in Dowa than in Nkhotakota. Over the three years of the study, NTM had the highest total labor costs in

price on profitability.

3. Results 3.1. Variable input and labor costs Input costs are shown in Table 2 for Nkhotakota and Table 3 for Dowa. In Nkhotakota, input costs were greatest for continuous no-till maize (NTM). While maize seed was less expensive than planting material for other crops, fertilizer was more expensive. In CAR, cowpea production was almost twice as expensive as soybean production. Overall production costs were greatest in NTM, intermediate in CAR, and lowest in CTR. Herbicides and equipment added costs to the NTM and CAR treatments. Over the three years of the study, total input costs in NTM were 41% and 82% higher than CAR and CTR, respectively, in Nkhotakota. In Dowa, sweet potato vines and bean seed were 5–6 times more expensive than maize seed. Since sweet potatoes also required fertilizer inputs, overall input costs were highest in the two treatments where 27

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Table 3 Input costs ($ ha−1) by cropping system and year in Dowa. Unit

Unit

No-till maize

size

Price

Units

Year 1 Crops Seed Maize Sweet potato Pigeon pea Fertilizer 23:21:0 + 4 s 46:0:0 Herbicide Roundup Harness Transport Equipment Total input costs Year 2 Crops Seed Maize Bean Fertilizer 23:21:0 + 4 s 46:0:0 Herbicide Roundup Transport Equipment Total input costs Year 3 Crops Seed Maize Fertilizer 23:21:0 + 4 s 46:0:0 Herbicide Roundup Harness Transport Equipment Total input costs

Cost

Maize

kg Bundle kg

1.68 1.43 1.73

25

50 kg 50 kg

34.03 34.03

3 3

L L

10.61 9.96

2.5 1

Conservation agriculture

Conventional tillage

Units

Units

Cost

Sweet potato Pigeon pea

Cost

Sweet potato

41.89 154 4

220.00 6.94

154

220.00

102.09 102.09

2.4

81.67

2.4

81.67

26.53 9.96 6.17 10.63 299.36

2.5

26.53

Maize

8.23 10.63 354.00 Bean

kg kg

1.50 2.33

25

50 kg 50 kg

37.34 36.95

3 3

112.01 110.86

L

10.03

2.5

23.97 6.17 10.63 302.15

8.23 309.91 Bean

37.40

Maize

100

232.88

2.5

25.09 1.23 10.63 269.82

Maize

80

186.30

1.23 187.53 Maize

kg

1.83

25

45.73

25

45.73

25

45.73

50 kg 50 kg

39.71 37.97

3 3

119.13 113.90

3 3

119.13 113.90

3 3

119.13 113.90

L L

9.09 10.34

2.5 1

22.71 10.34 6.17 10.63 328.60

2.5 1

22.71 10.34 6.17 10.63 328.60

6.17

952.42 317.47

782.37 260.79

2011–2014 Total input costs Average input costs

930.11 310.04

284.93

In Dowa, sweet potato in CTR generated the highest gross revenue in year 1 (Table 6). Sweet potatoes in CTR had higher net revenues than maize in NTM and both CTR and NTM were more profitable than the intercropped sweet potato-pigeonpea in CAR. In year 2, the CAR and CTR rotations had poor returns with beans, while NTM (in maize) had strong financial returns, generating labor productivity over $7 per day (Table 6). Contributing to these low returns, beans were planted late in CAR and CTR and only 180 mm of rain fell between planting and harvesting. Bean yields were similar in CAR and CTR, but gross revenue was not sufficient to cover production costs in CAR. In year 3, all three rotations planted maize, with yields and, thus, financial returns being lowest in NTM. Maize generated slightly higher yields in CAR than CTR, but both had financial returns over double those of NTM (Table 6). Accordingly, labor productivity was considerably higher in CAR at $8.71 day−1 and CRT at $7.57 day−1 than in NTM at $3.76 day−1. Over the three years of the study, NTM had higher cumulative gross revenue and production costs in each location (Table 7). Cumulative net revenues were roughly similar in NTM in both locations and CTR in Dowa. Labor productivity in Dowa was higher than in Nkhotakota due partly to higher labor-use levels in Nkhotakota. Generally, input costs

both locations. However, total labor costs were almost as high for CTR as for NTM in Dowa due to the relatively high labor costs of sweet potatoes in CTR. 3.2. Outputs and financial returns to management Maize in NTM returned higher gross revenues than CTR and CAR in years 1 and 2 in Nkhotakota (Table 5). In year 1, cassava tuber yields were over twice as great in CTR as those in CAR. Both CAR and CTR derived revenue from primary products (cassava tubers and pigeonpea grain) and co-products (cassava leaves and stems and firewood), with co-products producing more revenue than primary products in CAR. High cassava revenue and low costs gave CTR net revenues almost as high as NTM, and greater gross margins and labor productivity. Labor productivity and gross margins, with and without factoring in the opportunity cost of labor, were much greater in NTM and CTR than CAR. In year 2, co-products from cowpea and pigeonpea helped CAR generate a positive return while gross revenue in CTR did not cover production costs. When all three rotations grew maize in year 3, CAR had the highest gross revenue due to lower yields in NTM and CTR. 28

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Table 4 Labor days ha−1 for each farm operation, total labor days, and total labor costs by cropping system and year in Nkhotakota and Dowa districts. Nkhotakota

Dowa

NTM

CAR

CTR

NTM

CAR

CTR

Year 1 Crops

Maize

Cassava

Maize

– 6.8 34.4 – 20.0 1.1 60.2 19.9 – 142.4 145.29

34.1 – 10.9 – 2.6 – 60.4 10.9 – 118.9 121.30

– 0 21.6 – 17.4 0.7 37.0 17.6 – 94.2 96.16

Sweet potato Pigeon pea – 0 20.6 3.3 5.5 1.1 46.4 18.8 1.3 97.0 98.94

Sweet potato

Cultivate ridges Lay out residues Plant Primary Crop Plant intercrop Fertilizer Application Herbicide application Hand-weeding Harvest primary crop Harvest intercrop/firewood Total labor days Total labor cost

Cassava Pigeon pea – 6.7 20.3 8.9 4.6 1.0 67.0 6.6 10.7 125.7 128.31

26.8 – 16.1 – 5.5 – 41.7 15.1 – 105.3 107.40

Year 2 Crops

Maize

Cultivate ridges Lay out residues Plant Primary Crop Coppice intercrop Fertilizer Application Herbicide/Pesticide application Hand-weeding Harvest primary crop Harvest intercrop/firewood Total labor days Total labor cost Year 3 Crops Cultivate ridges Lay out residues Plant Primary Crop Plant intercrop Fertilizer Application Herbicide application Hand-weeding Harvest primary crop Harvest intercrop/firewood Total labor days Total labor costs Total labor days (2011–2014) Total labor cost (2011–2014) Average labor days yr–1 Average labor cost yr–1

Soybean

Maize

Bean

Bean

– 5.8 26.0 – 29.7 1.1 66.4 26.6 – 155.6 153.21

Cowpea Pigeon pea – 0 32.1 3.4 – 1.6 25.3 49.0 20.3 131.7 129.63

20.5 – 9.9 – – – 63.3 29.2 – 122.9 120.97

– 1.8 13.8 – 33.9 0.7 20.7 28.8 – 99.6 98.09

– 0 19.3 – – 0.9 9.5 27.3 57.0 56.15

16.0 – 11.1 – – – 7.6 28.0 – 62.8 61.82

Maize – 4.9 25.1 – 22.9 1.1 63.8 23.3 – 141.1 151.16 439.0 449.66 146.3 149.89

Maize – 0 25.1 – 22.9 1.1 57.5 23.3 – 129.9 139.15 387.3 397.09 129.1 132.36

Maize 15.7 – 16.9 – 17.25684 – 53.5 23.3 – 126.6 135.62 368.3 377.89 122.8 125.97

Maize – 2.0 14.4 – 24.0 0.9 17.0 24.1 – 82.5 88.36 276.3 282.61 92.1 94.20

Maize – 0 14.4 – 24.0 0.9 14.6 24.1 – 78.0 83.60 232 238.69 77.3 79.56

Maize 19.4 – 11.1 – 18.0 – 15.6 24.1 – 88.2 94.51 256.2 263.73 85.4 87.91

rotation, both CAR and CTR systems had similar gross margins and labor productivity. Furthermore, increasing cassava, cowpea, and soybean yields to the mean adjusted yield results in gross margins and labor productivity in CAR and CTR similar to NTM's gross margins (47%) and labor productivity ($3.84 labor day−1), and greater financial returns than NTM at national average yields. In Dowa, financial returns from sweet potato were better in CTR than CAR at mean adjusted yields, while net revenue and gross margins would be similar at national average yields (Table 8). Financial returns from beans would be greater in CTR than CAR in both yield scenarios. In CAR, a 10% increase in actual bean yields would be sufficient for smallholder farmers to break even. Over the course of the rotation, adjusting sweet potato and bean yields to the mean adjusted yields would result in similar financial returns to NTM, while at national average yield levels, CAR and CTR with these alternative crops would provide greater financial returns. Sensitivity analysis was conducted by varying labor costs and input and output prices, with five scenarios and their underlying assumptions outlined in Table 9 and their financial projections in Table 10. In scenario 1, increasing labor costs would have a greater impact on net

were higher in NTM and CAR than in CTR. In Dowa, CTR had the best labor productivity and gross margins of all three cropping systems, regardless of whether labor costs were included. The CA rotation with alternative crops had the worst labor productivity and gross margins in both locations.

3.3. Sensitivity analysis Adjusted crop yields of cassava, sweet potato, cowpea, soybean, and bean had a significant impact on their profitability using two alternative yield scenarios. In Nkhotakota, cassava in both CAR and CTR would be very profitable for smallholder farmers at both mean adjusted and national average yields, but the impact was much larger in CAR, which had lower actual yields (Table 8). Soybean had a higher national average yield than cowpea, which would result in higher financial returns compared to cowpea in CTR in Nkhotakota, when adjusting to national yield averages. In CTR, increasing the actual soybean yield by 29% to 480 kg ha−1 would have been sufficient to cover production costs in year 2 (Table 8). When mean adjusted yield or national average yield is incorporated into the financial analysis of the three-year 29

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Table 5 Outputs, gross revenue, and financial returns (ha−1) by cropping system and year in Nkhotakota. Unit

Unit

No-till maize

Size

Price

Units

Cost

Maize 4174

1022.17

Year 1 Crops Maize kg Cassava kg Pigeon pea kg Cassava leaves 400 g Cassava stems Bundle Firewood kg Gross revenue $ Total Costs $ Net revenue $ Labor productivity ($ labor day−1) Gross Margins (%) With opportunity cost of labor Without opportunity cost of labor Year 2 Crops Maize kg Cowpea kg Cowpea leaves 400 g Soybean kg Pigeon pea kg Firewood kg Gross revenue $ Total Costs $ Net revenue $ Labor productivity ($ labor day−1) Gross Margins (%) With opportunity cost of labor Without opportunity cost of labor Year 3 Crops Maize Revenue kg Total Costs $ Net revenue $ Labor productivity ($ labor day−1) Gross Margins (%) With opportunity cost of labor Without opportunity cost of labor

0.24 0.10 0.86 0.16 1.43 0.08

0.26 0.44 0.27 0.38 0.49 0.08

0.15

Maize 3676

Conservation agriculture

Conventional tillage

Units

Units

Cost

Cassava + Pigeon pea

Cassava

2447 81 219 115 378

5310

541.82

219 115 351

35.74 163.92 28.65 770.13 285.72 484.42 5.10

1022.17 444.65 577.52 5.08

249.68 69.19 35.74 163.92 30.86 549.39 336.82 212.57 2.71

56 71

39 62 Cowpea + Pigeon pea

63 79 Soybean

961.32 443 97

194.19 26.45

129 937 961.32 455.36 505.97 4.24

63.53 77.05 361.23 249.91 111.31 1.83

143.24 183.89 −40.65 0.65

53 69

31 67

−28 56

373

Maize 4320

Cost

632.27 479.77 152.50 2.15

Maize 5684

24 48

831.80 467.76 364.05 3.88 44 60

Maize 4789

143.24

700.80 420.55 280.25 3.29 40 59

the maximum price would sell their produce for double what farmers selling at the minimum price would receive.

revenue in Nkhotakota than in Dowa (Table 10). In scenarios 2a and 2b, varying input prices would have a more dramatic effect on net revenue in CAR, followed by CTR and then NTM in both districts (Table 10). The change from minimum to maximum input prices for maize seed, inorganic fertilizers, and herbicides was fairly low, generally less than 40% (Table 11). Conversely, the maximum price for seed and planting material costs for alternative crops ranged from 2.5 to 7 times greater than the minimum price. Altering output prices in scenarios 3a and 3b would have greater impact on smallholder farm profitability than altering labor or input costs (Table 10). Farmers in both districts receiving the lowest output prices would have net revenues reduced by 99–367%. Farmers in Nkhotakota would have received cumulative net revenues of only $195.92 and $154.89 in CAR and CTR, respectively, compared to $513.65 in NTM. Net revenue would have increased by a factor of 8.4 and 6.07 when comparing net revenue at the maximum output price to the minimum in CTR and CAR, respectively. Conversely, NTM was much more robust, with only a 3.8 factor increase from the minimum to maximum output price. In Dowa, CAR was the most sensitive to shifting output prices, with a maximum-to-minimum ratio of 3.91 compared to NTM (3.16) and CTR (2.99). Net revenue would increase by 33–44% in both districts if farmers were able to receive the maximum output price. In year 1, the prices of all outputs were highly variable and were most variable for cassava and firewood (Table 11). In year 2, output price variability was greatest for pigeonpea and bean, and farmers receiving

4. Discussion 4.1. Cropping systems and wellbeing Although NTM was the most profitable cropping system in each district, it also had the greatest production costs, which can be an issue for smallholder farmers. Producing grain legumes can reduce production costs and risk on resource-constrained smallholder farms in southern and eastern Africa compared to continuous maize (Kihara et al., 2009; Zingore et al., 2009). In this study, cassava, cowpea, soybean, and bean had lower production costs than maize and sweet potato, regardless of cropping system (CAR and CTR). Reduced production costs were largely driven by lower fertilizer and labor costs, as the planting material and seed for alternative crops were much more expensive than maize seed. Production costs in CTR were further reduced compared to NTM and CAR because CTR did not require herbicides or backpack sprayers, which is consistent with other studies (Ito et al., 2006; Ngwira et al., 2011, 2012). Net revenue, labor productivity, and gross margins were greatest in NTM in Nkhotakota and similar in NTM and CTR in Dowa. In CAR, intercropping with pigeonpea provided additional revenue from grain and firewood, but this additional revenue was not sufficient to improve 30

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Table 6 Outputs, gross revenue, and financial returns (ha−1) by cropping system and year in Dowa. Unit

Unit

No-till maize

Size

Price

Units

Year 1 Crops

Cost

Maize

Maize Kg Sweet potato Kg Pigeon pea Kg Sweet potato leaves 400 g Sweet potato vines Bundle Gross Revenue $ Total Costs $ Net revenue $ Labor productivity ($ labor day−1) Gross Margins (%) With opportunity cost of labor Without opportunity cost of labor

0.24 0.11 0.86 0.16 1.43

Year 2 Crops Maize Kg Bean Kg Bean leaves 400 g Gross Revenue $ Total Costs $ Net revenue $ Labor productivity ($ labor day−1) Gross Margins (%) With opportunity cost of labor Without opportunity cost of labor

3751

Conventional tillage

Units

Units

Cost

Sweet potato Pigeon pea

Maize 3884

Maize 4364

Sweet potato

918.62 395.52 523.09 6.57

760.69 21.54 18.13 56.02 856.37 452.94 403.43 5.18

57 67

47 59

8854

1011.89

111 39

18.13 56.02 1086.03 417.31 668.72 7.37 62 71

Bean

Bean

1015.81 383 6

0.15

Cost

918.62 6656 25 111 39

0.26 0.77 0.27

Year 3 Crops Maize revenue Kg Total Costs $ Net revenue $ Labor productivity ($ labor day−1) Gross Margins (%) With opportunity cost of labor Without opportunity cost of labor

Conservation agriculture

1015.81 400.24 615.57 7.16

294.00 1.55 295.55 325.97 −30.42 0.45

61 70

−10 9 Maize 6889

638.57 416.97 221.61 3.76

319.07 1.55 320.62 249.35 71.26 2.12 22 42

1008.17 412.20 595.96 8.71

35 49

416 6

Maize 6509

952.50 379.44 573.07 7.57

59 67

financial returns compared to NTM and CTR. In CAR and CTR, a sizeable portion of the revenue was derived from co-products, leaf vegetables, planting materials, and firewood. The additional value provided by co-products could make these crops more attractive to smallholder farmers and help drive their adoption (Snapp et al., 1998). Positive net revenue from notional financial analysis suggests that each cropping system was feasible and could increase wellbeing for smallholder farmers. Additionally, labor productivity was 2–3 times greater than Malawi's minimum daily wage in Nkhotakota and 5–6 times greater in Dowa, regardless of cropping system. Therefore, any of the cropping systems in this study have the potential to provide smallholder farmers with greater wellbeing than casual off-farm work at, or near, the minimum daily wage. Furthermore, as the majority of

60 70

labor was provided by participating households in both districts, we can consider a large percentage of the opportunity cost of labor ($240–450 over the course of the three-year rotation) to be additional income for the households. These results indicate that some CA practices can compete with traditional cultivation on smallholder farms. This result is not trivial since traditional cultivation practices have evolved over long periods of trial and error. From the farmer perspective, they are default “best practices” and farmers are justifiably skeptical of proposed alternatives. Low yields from alternative crops reduced their profitability in this study. Cassava and sweet potato yields were lower than the national average and lower in CAR than CTR. No-till has been reported to have a negative effect on cassava and sweet potato yields compared to

Table 7 Cumulative gross revenue, total cost, and financial returns by cropping system in Nkhotakota and Dowa from 2011 to 2014. Nkhotakota

Gross Revenue ($ ha−1) Labor Cost ($ ha−1) Input Costs ($ ha−1) Total Cost ($ ha−1) Net Revenue ($ ha−1) Labor productivity ($ labor day−1) Gross Margins (%) With opportunity cost of labor Without opportunity cost of labor

Dowa

No-till maize

Conservation agriculture

Conventional tillage

No-till maize

Conservation agriculture

Conventional tillage

2615.76 449.66 930.11 1379.77 1235.99 3.84

1742.42 397.09 657.39 1054.49 687.93 2.80

1614.17 377.90 512.27 890.16 724.01 2.99

2573.00 282.61 930.11 1212.73 1360.27 5.95

2160.09 238.69 952.42 1191.11 968.97 5.21

2359.15 263.73 782.37 1046.10 1313.06 6.15

47 64

39 62

45 68

53 64

45 56

56 67

31

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Table 8 The effects of adjusting the yields of cassava, sweet potato, cowpea, soybean, and beans in conservation agriculture and conventional tillage on financial returns (ha−1) by crop and the cumulative returns of the 3-year crop rotations. Conservation agriculture Actual yield Nkhotakota Crop Average yield (kg) Net revenue ($) Gross margins (%) Labor productivity ($ day−1) Crop Average yield (kg) Net revenue ($) Gross margins (%) Labor productivity ($ day−1) Cumulative Returns Net revenue ($) Gross margins (%) Labor productivity ($ day−1) Dowa Crop Average yield (kg) Net revenue ($) Gross margins (%) Labor productivity ($ day−1) Crop Average yield (kg) Net revenue ($) Gross margins (%) Labor productivity ($ day−1) Cumulative Returns Net revenue ($) Gross margins (%) Labor productivity ($ day−1)

Cassava 2447 212.57 39 2.71 Cowpea 443 111.31 31 1.83 678.93 39 2.80 Sweet potato 6656 403.43 47 5.18 Bean 383 −30.41 −10 0.45 968.97 45 5.21

Conventional tillage

Mean adjusted yield

National average yield

5723 546.92 62 5.37

9000 881.26 72 8.03

478 126.66 34 1.95

Actual yield

Mean adjusted yield

National average Yield

7155 672.69 70 6.68

9000 860.97 75 8.26

513 142.00 36 2.06

Cassava 5310 484.42 63 5.10 Soybean 373 −40.65 −28 0.65

656 67.81 27 1.54

939 176.27 49 2.42

1037.62 50 3.70

1387.31 57 4.61

724.01 45 2.99

1020.75 53 3.80

1317.49 60 4.60

8428 605.94 57 7.27

10,200 808.45 64 9.36

469 35.08 10 1.60 1236.98 51 6.36

9527 745.64 64 8.10

10,200 822.55 66 8.84

554 100.57 24 2.75

Sweet potato 8854 668.72 62 7.37 Bean 416 71.27 22 2.12

485 124.22 33 2.96

554 177.18 42 3.81

1504.98 56 7.52

1313.06 56 6.15

1442.93 58 6.66

1572.80 60 7.17

becomes as feasible as continuous no-till maize for smallholder farmers. If farmers were able to boost alternative crop yields to equal national yield averages, then farmer wellbeing would be maximized by adopting cassava, sweet potato, cowpea, soybean, and bean in diversified crop rotations. In addition to maximizing farmer wellbeing, diversifying crop rotations on smallholder farms can result in a more diverse and nutritious diet compared to farms that lack crop diversity (Jones et al., 2014). The development of high yielding varieties and best-bet management practices for alternative crops in both CA and conventional tillage systems could increase crop yields from the low levels observed in this study. Increased investment in research and extension services to develop and disseminate high yielding and disease resistant cultivars of cassava has been reported to increase adoption and economic returns in Malawi and Zambia (Alene et al., 2013; Rusike et al., 2009). Additionally, farmers' choice of rotation crops will be influenced by access to extension services specific to alternative crops (Lukanu et al., 2009). To date, the majority of research on CA systems in southern and eastern Africa has focused on staple grains, with little research on alternative crops (Brouder and Gomez-Macpherson, 2013; Wall et al., 2013). Due to the short duration of this study, the indicators of feasibility and wellbeing presented focus on “profits” as a function of in-kind or

conventional tillage (Agbede, 2010; Odjugo, 2008). Reduced yields in no-till systems have been partially attributed to higher bulk density in no-till soils, which was also observed at our (TerAvest et al., 2015) and other (Agbede, 2010; Odjugo, 2008) research sites. Low grain legume yields are common in southern and eastern Africa and can reduce profitability (Franke et al., 2014). Poor availability or access to inputs (i.e., quality seed, fertilizer, and soil inoculants for legumes) and widespread soil acidity and low available P can limit N fixation and reduce grain legume yields (Chalk et al., 2009; Thierfelder et al., 2014; Wall et al., 2013). Despite low yields, the cowpea-pigeonpea intercrop in CAR in Nkhotakota and common bean in CTR in Dowa were profitable. Since this study only includes one rotation cycle and each alternative crop was grown only once, it is difficult to estimate alternative crop productivity. For example, bean and cowpea were planted late and rainfall was poor in year 2, which may have reduced yields compared to what a smallholder farmer might receive in an “average” year. To address this, we also analyzed the impact of alternative crops on farmer wellbeing at two additional yield levels. If alternative crop yields could be improved to the mean adjusted yield levels used in sensitivity analysis, farmer wellbeing would be similar among all three cropping systems. Under this scenario, diversification of crop production systems

Table 9 Scenarios and assumptions for sensitivity analysis of the effects of labor costs and input and output prices on cropping system profitability. Scenario

Parameter

Value

Assumptions

1 2a 2b 3a 3b

Labor costs Input prices

High Minimum Maximum Minimum Maximum

Labor shortage causes farmers to hire labor during peak labor demand periods Good market access allows farmers can shop to lowest input prices, most likely near large towns and cities Poor market access, high transport costs drive up input costs and there are fewer options Poor market access or high demand for cash forces households to sell outputs at low prices Good market access or capacity for storage allows farmers to find favorable market conditions

Output prices

32

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Table 10 Sensitivity analysis of the effect of varying labor cost, input prices, and output prices on net revenue ($ ha−1) of the 3-year cropping sequence by cropping system in Nkhotakota and Dowa. Base Case

Scenario 1

Scenario 2

Labor price

Input price

Max/

Scenario 3

Max/

Output price

Net

Net

%

Net revenue

% Change

Net revenue

% Change

Revenue

Revenue

Change

Min (a)

Max (b)

Min

Max

Min

Min (a)

Max (b)

Min

Max

Min

Nkhotakota No-till maize Conservation agriculture Conventional tillage

1235.99 687.93 724.01

1001.76 506.28 567.10

−23 −36 −28

1147.92 532.59 621.66

1311.19 823.63 833.28

−8 −29 −16

6 17 13

1.14 1.55 1.34

513.65 195.92 154.89

1964.83 1188.50 1300.34

−141 −251 −367

37 42 44

3.83 6.07 8.40

Dowa No-till maize Conservation agriculture Conventional tillage

1360.27 968.97 1313.06

1226.04 861.43 1227.94

−11 −12 −7

1272.21 731.17 1118.95

1435.47 1278.38 1573.84

−7 −33 −17

5 24 17

1.13 1.75 1.41

655.44 396.56 659.91

2071.67 1551.76 1976.00

−108 −144 −99

34 38 34

3.16 3.91 2.99

Table 11 Yearly minimum and maximum input and output prices from agricultural retailers and output markets in Central Malawi. Unit Size

Inputs Seed Maize Cassava Sweet potato Pigeon pea Cowpea Soybean Bean Fertilizer 23:21:0 + 4 s 46:0:0 Chemicals Roundup Harness Dimethoate Outputs Maize Cassava Sweet potato Pigeon pea Leaf Vegetables Planting materials Cassava Sweet potato Firewood Cowpea Soybean Bean

Year 1

Year 2

Year 3

Min. $

Max. $

Increase %

Min. $

Max. $

Increase %

Min. $

Max. $

Increase %

Kg Bundle Bundle Kg Kg Kg Kg

1.48 0.82 0.82 0.86

2.04 2.04 2.04 2.61

38 205 150 150

1.37

1.59

16

1.80

1.85

3

0.44 0.49 0.68

3.01 2.68 3.42

775 511 400

50 kg 50 kg

29.63 29.63

39.09 37.96

32 28

34.93 34.25

39.59 39.73

13 16

37.44 36.24

42.68 40.00

14 10

L L 100 ml

8.16 9.31

14.69 10.61

80 14

9.59

10.82

13

7.80 8.54

10.98 11.71

41 37

4.11

5.75

40

kg kg kg kg 400 g Bundle Bundle kg kg kg Kg

0.16 0.04 0.07 0.49 0.12 0.82 0.82 0.04

0.18

0.34

83

0.12

0.17

75

0.33 0.22

0.66 0.33

100 50

0.07 0.33 0.27 0.49

0.10 0.55 0.49 1.04

40 67 80 111

0.33 0.16 0.16 1.22 0.20 2.04 2.04 0.12

100 300 111 150 67 150 150 200

financial returns of all three cropping systems may be similar in the short-term, depending on the yields realized by smallholder farmers, NTM and CAR may have a greater positive impact than CTR in the longterm by improving resilience to climate variability, soil quality, and sustainability.

marketable products and do not consider the potential environmental impacts of each cropping system. As part of a larger study at these research sites, NTM increased water infiltration and NTM and CAR increased soil moisture content and reduced soil sediment runoff compared to CTR in Nkhotakota (TerAvest et al., 2015). The results of this and other studies suggest that no-till and CA can increase resilience to drought and in-season dry periods compared to conventional tillage practices (Gicheru et al., 2006; TerAvest et al., 2015; Thierfelder et al., 2012a, 2012b; Thierfelder and Wall, 2010). Furthermore, numerous studies in southern and eastern Africa have reported that adopting CA principles can increase ecosystem services, such as sequestering soil carbon, maintaining soil structure, and reducing soil erosion (Kihara et al., 2011; Thierfelder et al., 2012a, 2012b; Thierfelder and Wall, 2009). Providing more ecosystem services may further increase smallholder farmers' ability to meet their basic needs, such as adequate food, clean water, and shelter (Summers et al., 2012). Therefore, while the

4.2. Market access and wellbeing Sensitivity analysis was used to test the robustness of each cropping system to varying labor and input costs and output prices. Maize had the most stable input costs and output prices, making NTM the most robust cropping system. Conversely, the input costs and output prices of the alternative crops grown in CAR and CTR were highly variable, affecting their potential to increase smallholder farmer wellbeing. Labor has been reported to be a significant constraint on smallholder farms in southern and eastern Africa (Giller et al., 2009; Zingore 33

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limit their ability to divert land to alternative crops in rotation, (Dowswell et al., 1996; Ellis et al., 2003; Thierfelder et al., 2014). Furthermore, fertilizer and improved seed-subsidy programs have focused primarily on maize production, which can lead to maize monocropping (Sanchez, 2010; Thierfelder et al., 2014). Monocropping of maize is also encouraged by its dominant role in the subsistence diet, especially for farmers with small landholdings. Strengthening markets for alternative crops could both increase the purchasing power of smallholder farmers who choose to grow these crops (to purchase maize) as well as reduce uncertainty, which would increase the feasibility of diverse crop rotations.

et al., 2009). Some studies have suggested that CA can reduce labor in Malawi by eliminating the time-consuming practice of cultivating ridges (Ito et al., 2006; Ngwira et al., 2011, 2012). In this study, however, the labor saved from eliminating tillage was often offset by increased labor demands in planting and fertilizer application in NTM and CAR. Smallholder farmers applied fertilizer and seed manually with a dibble stick. In untilled soil, the soil surface was harder than the recently cultivated ridges and it was more difficult to place and cover-up seed and fertilizer, increasing labor use. If household labor shortages would have resulted in hiring off-farm workers during peak seasons, profits for smallholder farmers would have been reduced in both districts, but more so in Nkhotakota. The reduction in net revenue would be similar across cropping systems, with NTM remaining very profitable. Climatic differences between the research sites most likely played a significant role in increasing labor in Nkhotakota. More annual rainfall and daily average temperatures that were 5.6 °C hotter in Nkhotakota than Dowa most likely increased the need for hand weeding while reducing labor productivity. Despite increased labor costs, all three cropping systems would still have been profitable in both districts as long as the labor constraints did not result in a failure to properly manage crops. Improving rural infrastructure can improve market access for smallholder farmers, reduce transportation and transaction costs, and decrease the price of inputs (Alene et al., 2007; Jayne et al., 2010; Yamano and Kijima, 2010). In this study, the influence of input prices differed depending on the crop being produced. Market prices for maize inputs (seed and inorganic fertilizers) were stable across locations so that the profitability of NTM was very robust in these two scenarios. In contrast, the market for seed and planting materials for alternative crops was highly variable leading to greater fluctuations in the financial returns of crop rotations. Large price fluctuations can cause uncertainty, which could make crop rotations appear too risky for smallholder farmers (Pannell et al., 2006). Policies that improve input markets for alternative crop seed and planting materials are needed to bring down input costs and reduce risk for smallholder farmers. Additionally, strategies that reduce input costs could also result in greater input use and increased crop production. Farmers with poor access to output markets or desperate to sell produce quickly would have had very low net revenues in this study; and adoption of rotations with the trialed alternative crops would likely be low. Improving rural infrastructure can expand the size of output markets for smallholder farmers and access to market information and cooperative selling can improve farmers bargaining power in the market and reduce transactions costs (Alene et al., 2007; Jayne et al., 2010; Mather et al., 2013). Increasing farmgate prices of alternative crops would have the greatest impact on profitability and farmer wellbeing in this study. Increasing prices from the minimum to maximum price resulted in a 3 to 8.4-fold increase in net revenue in every cropping system. However, the revenue increases were greater in CAR in both districts and in CTR in Nkhotakota compared to NTM. For storable crops, the maximum output prices were observed 3–6 months after harvest. Enhancing the capacity of smallholder farmers to store grains could allow them to capitalize on favorable market conditions (Jones et al., 2011).

5. Conclusions The financial returns of three cropping systems–continuous no-till maize, CA rotation, and conventional tillage rotation–on smallholder farms in two agroecological zones in Malawi were evaluated using notional financial analysis and sensitivity analysis. Using notional financial analysis, in which we assumed labor and other prices were explicit, no-till maize produced the greatest gross and net revenues of all three cropping systems. However, this system was also costlier in both labor and inputs than the diversified CA and conventional tillage systems with alternative crops, which included cassava, cowpea, soybean, or bean production. The CA rotation system did not produce significant labor savings compared to conventional tillage rotation, mainly due to more labor-intensive planting and fertilizer applications in the absence of tillage. Despite lower revenue in CA and conventional rotations, these systems were still profitable for smallholder farmers. This was driven by lower costs, greater maize production following alternative rotation crops, and additional revenue from co-products, such as planting materials, firewood, and leafy vegetables. Conventional tillage rotation offered farmers returns equal to no-till maize but would likely not provide smallholder farmers with the greater ecosystem services of the continuous no-till maize or CA rotation systems. Low yields for alternative crops reduced the competitiveness of the CA system. However, improving yields of alternative crops would make the CA rotation system as or more profitable than the continuous no-till maize system and could increase dietary diversity for smallholder households in the short-term. Sensitivity analysis was used to examine the effects of input, output, and labor costs on farmer wellbeing. Across all scenarios tested, continuous no-till maize was more robust than diverse crop rotations. Input costs and output prices for alternative crops were highly variable, making diverse crop rotations appear risky and reducing their appeal to smallholder farmers. To reduce risk and increase adoption, agricultural retail networks need to be expanded to include seed and planting materials for these crops. Altering farmgate prices of alternative crops had a greater impact on the net revenue received by smallholder farmers than changes to labor or input costs. In the long-term, policies that reduce uncertainty and risk of alternative crops or increase their farmgate prices would likely increase adoption of crop rotations and conservation farming practices. These policies can improve the feasibility of CA in the short term, enhance the ecosystem services provided by CA in the long term, and overall lead to greater wellbeing for smallholder farmers.

4.3. Constraints to adoption

Acknowledgements

Many factors will affect smallholder farmer decisions regarding the adoption of new farming practices or technologies including short-term costs and output prices, medium and long-term profitability, adjustment costs, impacts on other aspects of the farm, riskiness and uncertainty, compatibility with the farmer's current practices, the complexity of new farming practices or technologies, and government policies (Pannell et al., 2006). The first priority of smallholder farmers is to meet basic household needs by producing sufficient food, particularly maize, for consumption (Pannell et al., 2014). This necessity can

We would like to thank Trent Bunderson, Executive Director of Total LandCare, and Total LandCare staff for their assistance in identifying participating farmers and their invaluable logistical support. We also thank the smallholder farm families for their cooperation in using their farms. This work was conducted with financial support from the CIMMYT CGIAR Research Program MAIZE (www.maize.org) and the USAID-funded Feed the Future program Africa RISING. 34

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