ARTICLES

 

Farmers' Production Practices, Incidence and Management of Pests and Diseases, Extension Services, and Factors Limiting Cotton Production and Quality in South Africa

 

 

Malinga L.N.^I; Laing M.D.^II

^IAgricultural Research Council, Private Bag X82075, Rustenburg, 0300, South Africa. South African Sugarcane Research Institute, P/Bag X02, Mount Edgecombe, 4300
^IIUniversity of KwaZulu-Natal, P/Bag X01, Scottsville, Pietermaritzburg, 3209, South Africa

Correspondence

 

 

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ABSTRACT

Cotton is one of the essential cash crops; however, several factors, such as low yields and pest and disease infestations, affect the production. In South Africa, cotton production has increased among small-scale farmers since the late 1990s. Although the crop is not new to South African farmers, no recent information reflects the current status of cotton production practices. A study evaluated farmers' production practices, the incidence and management of pests and diseases, extension services, and factors limiting cotton production and quality in South Africa. One hundred and forty farmers, mainly smallholder farmers, were interviewed during the 2017/18 growing season. Most farmers planted genetically modified (GM) cotton on less than 5 ha of cotton, with 96% planting under dryland. Most farmers neither practised conservation agriculture (95%) nor conducted soil analyses (87%). A mean cottonseed yield of 700 kg ha^-1 was reported on dryland cotton, and 5 000 kg ha^-1 was obtained from irrigated cotton. Most of the farmers (99%) harvested their cotton by handpicking. Farmers' pest knowledge was higher than their knowledge of different diseases. Most participants were unaware of nematodes (88%) or disease-resistant cultivars (74%), while 91% were aware of insect-resistant cultivars. Extension officers only mentored and supported many respondents (82%). Most farmers (93%) relied on pesticides to control cotton pests, and the rest (7%) used biological control. Climatic conditions (98%), labour costs (88%), and insect infestations (42%) were identified as the main constraints in cotton production. Although this study had a limited number of surveyed farmers, it gives some insight into their knowledge and challenges.

Keywords: Cotton, Insect Pests, Diseases, Integrated Pest Management, Farmers' Knowledge.

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1. INTRODUCTION

Cotton (Gossypium hirsutum L.) is an important cash crop globally (Boyer et al., 2017; Tigga et al., 2017) and particularly in the Southern African Development Community countries (Gwarazimba, 2009). Cotton is grown in 75 countries worldwide (World Trade Organisation, 2019), accounting for about 80% of natural fibre production (Townsend, 2020). However, South Africa's production is far less than the domestic demand for cotton (Department of Agriculture, Forests and Fisheries, 2011). Cotton is susceptible to a wide range of pests that significantly impact the yield and quality of the fibre (Manjunath, 2004; Karavina et al., 2012). The damage caused by these pests is most severe on cotton grown in developing countries. Efficient integrated pest management has long been proposed as essential for efficient cotton production (Fitt et al., 2009). However, the concept requires interventions based on a thorough knowledge of the crop, the pests, and the environment (Prudent et al., 2007; Tibugari et al., 2012). Although pests and diseases in cotton are not new to South African cotton farmers, no recent information reflects farmers' current knowledge of pests and diseases.

Furthermore, the cotton yields among dryland farmers in South Africa continue to be low and individual farmers employ different production practices to improve the yields. Attempts to improve cotton production require a detailed understanding of the farmers' knowledge and needs (Norton & Mumford, 1993; Sinzogan et al., 2004). Hence, a survey was conducted to provide more information on cotton farmers' knowledge and perceptions about cotton production in three cotton-producing regions of South Africa. This survey also aimed to give relevant information on the farmers' agronomic activities, the status of the pests and diseases, and their management. The overall objective of this study was to explore farmers' knowledge of cotton pests and cotton production practices in South Africa. This information could assist in identifying research gaps and developing future programmes to enhance cotton production.

 

2. MATERIALS AND METHODS

2.1. Study Area

The survey study was conducted in three cotton-producing provinces of South Africa. Five regions were surveyed as the representative area. The regions were Nokaneng-Mpumalanga (25°5'S; 28°38'E), Tonga-Mpumalanga (25°40'S; 31°52'E), Makhathini-KwaZulu-Natal (27°42'S; 32°10'E), Groblersdal-Limpopo (25°09'S; 29°23'E) and Marble Hall-Limpopo (24°58'S; 29°18'E).

2.2. Survey Sampling

A questionnaire was sent to 200 randomly selected farmers to gather information on cotton pests and production practices. The number of farmers interviewed in each area depended on the participation and availability of farmers. The survey was conducted on the region's recognised cotton farmers. The survey involved both electronic and manual surveys of mainly smallholder cotton producers. Of the 200 farmers, 140 (70%) completed and returned the questionnaires.

2.3. Data collection

Information for this study was gathered from a farmers' survey conducted between April and August 2017. The questionnaire was designed to obtain information on farmers' production practices, the incidence and management of pests and diseases, extension services, and factors limiting cotton production and quality (Table 1). With the assistance of Cotton South Africa, the questionnaires were pre-tested with some farmers in the surveyed areas before the study was conducted to ensure that farmers had no problem understanding them. Where required, translation was done into the language of the farmers, and then their answers were translated back into English. Questionnaires were distributed to the selected farmers. The questionnaire required approximately 10 minutes to complete. There was no financial incentive for responding or any known risk for the participating farmers. All information supplied by the participants was regarded as confidential, and no individual farmer's responses were shared with any other party or person.

2.4. Data analysis

Survey data from the questionnaires were summarised and conveyed using descriptive statistics (means and percentages) based on the total number of affirmative responses compared to the total number of responses received. For each question, the percentage of farmers who gave similar responses was calculated for each site. The percentages were calculated by dividing the number of responses to that question by the total number of responses and multiplying by 100. Data collected were combined for analysis and presented in percentages in the form of tables.

 

3. RESULTS AND DISCUSSION

3.1. Climatic Condition and Soil Type of Selected Study Areas

The survey was conducted on cotton farmers from some of the major cotton-producing regions in South Africa. The respondents were mainly from KwaZulu-Natal (70%) followed by Mpumalanga (28%). Farms used for the study have mainly loam (22%) and sandy (56%) soil (Table 2). The overall mean rainfall reported by the respondents during the survey was 450 mm. KwaZulu-Natal reported 498 mm, while Limpopo and Mpumalanga reported 500 mm and 350 mm, respectively. Rain is crucial after planting or during emergence, and rainfall of 15 to 20 mm after planting promotes a good stand of cotton (Dippenaar, 2015). The mean summer temperature was 26.7°C, which is a suitable temperature for cotton production. As cotton is a tropical crop, it prefers summer temperatures of 25°C or higher (Coleman, 2019) and is favoured by soil temperatures above 18°C during germination (Boman & Lemon, 2005). Krzyzanowski & Delouche (2011) reported that the optimal temperature for cotton germination is 28°C to 30°C and that the germination rate decreases as temperatures go above 33°C or below 20°C. Cotton should also not be planted before the top 30 mm of the soil has maintained a temperature of 16 to 18°C or higher for approximately ten days (Dippenaar, 2015). However, Dippenaar (2015) also noted that in Limpopo, Mpumalanga, and KwaZulu-Natal, the soil temperature is not a limiting factor for the planting date for cotton.

3.2. Farm Size and Irrigation Source

On average, cotton was grown on six ha per household, but this varied significantly across provinces, ranging from one ha in Mpumalanga and KwaZulu-Natal to 200 ha in Limpopo (Table 3). The farm with 200 ha of cultivated cotton belonged to a commercial farmer. Most (62%) of the farms included in the survey had less than five hectares of land under cotton cultivation. Cotton South Africa (2017) reported that in South Africa during the 2016/17 season, 33 628 hectares were planted (19 273 ha irrigated and 14 355 ha dryland). 134 farmers (96%) planted dryland cotton, while only 12% had irrigated cotton fields. Most smallholder farmers in South Africa cultivate cotton under dryland conditions. The difference between the two farming systems is that the cottonseed yields are much higher in irrigated fields than in dryland fields.

3.3. Production Practices

The primary production practices of the farmers are provided in Table 4. Cultivar PM 3225 B2RF from Monsanto was the variety planted by most participants (89%). This cultivar has the BGII and RR Flex genes, giving it resistance to bollworms and the herbicide glyphosate. It also has hairy leaves, giving it tolerance to jassids but making it unsuitable for mechanical picking.

All the farmers planted GM cotton because no seed is commercially available for non-GM cotton cultivars in South Africa (James, 2014; United States Department of Agriculture, 2017). GM cotton was introduced in South Africa in 1997 as the first GM crop grown by both commercial and smallholder farmers (Thomson, 2016). Today, South Africa is one of the largest producers of GM crops globally. It is by far the largest in Africa (Masinjila, 2018), with most smallholder farmers adopting GM cultivars. Most farmers indicated that the advantages of planting GM cotton were reduced production costs, reduced insecticide use, and higher yields. Gouse, Kirsten and Jenkins (2003) noted yield increases for large-scale irrigated farmers (18.5%), large-scale dryland farmers (13.3%), and small-scale dryland farmers (45.8%) that adopted GM cotton.

Most of the respondents (95%) did not practise conservation agriculture because they cited unfamiliarity with the concept. Thierfelder et al. (2016) stated that conservation agriculture is the solution to water-conserving and sustainable cropping systems, which may be affected by unpredictable climatic conditions and frequent droughts in southern Africa. However, available estimates of its adoption currently suggest that smallholder farmers have not adopted it widely (Brown, Nuberg & Llewellyn, 2017). Most farmers (87%) did not conduct soil analysis before planting their fields. This problem was linked to their financial constraints and a lack of knowledge. Soil analysis is crucial to optimal fertilisation, increasing yields, and lowering the costs of cotton farming (Harper, 2011).

Of the respondents surveyed, 99% harvested their cotton by handpicking. Handpicking is more expensive than machine picking in South Africa. In contrast, Chaudhry (2008) reported that handpicking cotton in mainland China was cheaper than machine picking in Brazil. Although manual cotton harvesting is labour-intensive (Sandhar, 1999), major cotton-producing countries such as Egypt have not considered moving to machine picking because the handpicking of cotton guarantees high quality and puts less stress on the fibres. Farmers (1%) that harvested cotton mechanically used a picker or a stripper. The picker harvests cotton without causing damage to unopened bolls (Deshmukh & Mohanty, 2016; Certi-Pik, 2017) and is generally used only for a yield higher than 5 000 kg ha^-1 (Coleman, 2019). A stripper device pulls off the entire boll, damaging the stalk, and it is usually used when the yield is lower than 5 000 kg ha^-1 (Coleman, 2019). A mean cottonseed yield of 700 kg ha^-1, with individual fields ranging between 120 kg ha^-1 and 1 800 kg ha^-1, was reported by dryland farmers, while a mean yield of 5 000 kg ha^-1 was obtained from irrigated cotton. In 2017, the mean cotton yields in South Africa were 4 595 kg ha^-1 and 910 kg ha^-1 for irrigated and dryland production, respectively (Cotton South Africa, 2017). Global cotton yields are near the 10-year average of 770 kg ha^-1 (Cotton South Africa, 2018), a cotton production yield that is usually non-profitable. South Africa's break-even point for high-quality dryland cotton is 1 500 kg ha^-1 and 3 780 kg ha^-1 for average-quality irrigated cotton (Coleman, 2019). Many farmers (86%) bought seeds for planting, while 14% used seeds from the previous season.

3.4. Incidence and Management of Pests and Diseases

The incidence and management of pests and diseases are presented in Table 5. The study found that farmers' knowledge of pests was slightly better than their knowledge of various diseases that attacked their crops. Li et al. (2010) reported a similar trend in China, where the early detection and treatment of cotton diseases are uncommon. They recommended guidance from experts and a diagnostic system to help cotton farmers. Those who were aware of diseases on cotton knew about Verticillium wilt (10%), Fusarium wilt (8%), boll rots (23%), virus diseases (5%), seedling diseases (9%), and bacterial blight (12%). Those farmers aware of Verticillium wilt further reported how difficult it was to control this disease and its contribution to yield loss. These observations correspond with studies that have identified Verticillium wilt as one of the key reasons for low cotton yields among smallholder farmers (Mapope, 2001; Chapepa et al., 2015; Yuan et al., 2017). Controlling Verticillium wilt is challenging because it can infect a broad host range (Trapero et al., 2015), and there are few registered control measures. The Agricultural Research Council-Industrial Crops has developed two cotton cultivars resistant to Verticillium wilt; however, their adoption has been limited (unpublished). Cotton bollworms were recognised by 89% of the respondents. Larvae of these species are regarded as major pests of cotton in South Africa (Fourie, Van den Berg & Du Plessis, 2017). Other insect pests mentioned included aphids (84%), cotton stainers (96%), spider mites (91%), leafhoppers (known as jassids locally) (84%), and whiteflies (32%). Most participants (88%) indicated that they were unaware of nematodes on cotton in their fields. Fifty-eight farmers (58%) were aware of insect pests other than the ones listed above.

The farmers' knowledge of pests in cotton production from the sampled area may be related to the high number of these insects in their cotton fields. Also, there is a high potential that these insects cause crop damage and low yield for dryland farmers. Most of the participants indicated that there was a high prevalence of spiders (91%), ants or termites (87%), ladybirds (80%), and parasitic wasps (76%). While 91% of participants knew of insect-resistant cotton varieties, only 26% knew of disease-resistant varieties. Although most respondents reported that they rely on GM varieties to control pests and diseases, their yields will be compromised if some insects resist commonly used pesticides (Kranthi et al., 2019). The participants identified bollworms (42%) and leafhoppers (31%) as the main pests that the GM varieties provide resistance against, while the Verticillium wilt (26%) was regarded as the main disease that GM varieties provide resistance against. Where possible, host resistance is the most effective, natural, and affordable strategy to control Verticillium wilt (Klosterman et al., 2009; Tsror, 2011). Most farmers used pesticide sprays to control cotton pests (57%). Due to limited research on the biological control of cotton pests in South Africa, only 7% of the survey farmers used biological control methods. Chemical control of insect pests must be integrated with other control measures to be fully effective (Hillocks, 1995; Gautam et al., 2023). Only 9% used fungicide sprays to control cotton diseases, while 44% relied on resistant cultivars, despite only 26% of the farmers being aware of disease-resistant cotton varieties.

Chemical control (31%) was mainly used as a management strategy for the control of both pests and diseases, followed by resistant cultivars (27%) and biological control (2%), such as reliance on natural enemies. Where crop development is adversely affected by diseases, weed infestation, or poor crop management, the effectiveness of chemical control cannot be realised (Hillocks, 1995). Only 1% of the respondents said they received advice from other farmers. This confirms the observation by Midega et al. (2012) that mechanisms are required to train and encourage the farmer-to-farmer transfer of appropriate pest management information.

3.5. Extension Service and Factors Limiting Yield

Data in Table 6 illustrate the level of farmer support, factors limiting cotton yields, and areas requiring more research. Most respondents (82%) received mentoring and support from the extension officers and seed companies (14%), but only 1% indicated that they had received support from the Agricultural Research Council. Only 23% of the participants had been visited by a cotton researcher. Of those seen by a researcher, 63% were visited at least once in the previous season, while only 20% of the farmers experienced more than one visit. The farmers' limited knowledge of pests and diseases may be attributed to little information sharing among farmers and the limited mentoring and support from researchers and extension. Most farmers (91%) purchased their cottonseed from the seed suppliers. Only a few farmers (8%) used seeds bought in the previous year. Most respondents (98%) identified climatic conditions as the primary constraint, followed by the intensive demand for labour (88%) for efficient cotton production on their farms. Farmers in developing countries are more vulnerable to climate change than farmers in developed countries because their agriculture is mainly rain-fed (Intergovernmental Panel on Climate Change, 2007).

Further increases in global temperature and changes in rainfall patterns will significantly reduce cotton yield in Africa (Diarra et al., 2017). Problems with insect infestation affected 42% of the farmers, and only 8% reported a combination of different factors. None of the participants identified diseases as a limiting factor to the cotton yield; however, Chapepa et al. (2013) had previously noted that diseases remain a major limiting factor in cotton production. Concerning diseases, the participating farmers' perception may be related to the lack of support from the trained personnel who should provide information on the role of diseases on the yield. The farmers reported difficulties in controlling weeds, especially morning glory (Ipomoea purpurea) (33%) and nutsedges (Cyperus esculentus and C. rotundus) (21%).

However, more than a third (35%) of the respondents reported that they did not experience any weed problems, possibly because they successfully used glyphosate on Roundup Ready cotton varieties to manage weeds. Morning glory is one of the most problematic weeds due to its extended emergence period (Jha et al., 2006; Jha & Norsworthy, 2009) and abundant growth capabilities (Sellers et al., 2003; Norsworthy et al., 2008). Kerr (2016) described nutsedges as the world's most damaging weeds, with two primary species of nutsedge being found in South Africa. Commercial farmers practice effective chemical control methods for these weeds (Reinhardt, 2016; Burke et al., 2008). However, smallholder farmers cannot afford to use effective herbicides. The farmers believed that the problem of low cotton yields could be resolved through research on pest control (45%), weed control (19%), soil analysis (5%), and breeding for new cotton varieties (17%). The handpicking of cotton is more of a labour issue, with some farmers concerned about the high costs involved. Some farmers (14%) recommended mechanical harvesting as an alternative. Conservation agriculture would allow farmers to reduce labour constraints and increase yields compared to conventional methods (Grabowski & Haggblade, 2016; Thierfelder et al., 2016). Although many farmers cited rainfall and heat as factors most limiting cotton yields, none of the farmers supported research on climate change. This could be because the surveyed farmers are unfamiliar with climate change.

 

4. CONCLUSION

This study evaluated farmers' production practices and the incidence and management of pests and diseases. The study further sought to report the farmers' views of extension services and factors limiting cotton production and quality in South Africa. Despite the limited sampling area of the survey, the outcomes of this study offer some insight into farmers' knowledge of the pests and practices of cotton. The study may be helpful in the development of integrated pest management practices and identify inefficiencies in production practices in the industry to increase yield, reduce pesticide use, and increase gross margins. These results could assist in the development of effective agricultural extension programmes for farmers engaged in cotton production.

 

5. RECOMMENDATIONS

Based on the outcomes, the survey recommends 1) the development of novel cotton cultivars to combat diseases, weeds, and the detrimental effects of climate change; 2) technology transfer to enhance farmers' awareness of nematodes and diseases; 3) the development of alternative control methods to reduce the use of agrochemicals; 4) technology transfer to cotton farmers on the application of conservation agriculture; 5) technology transfer to farmers on the value of soil analysis; and 6) frequent visits by researchers to advise and mentor the farmers, and to learn from the farmers. A further survey, including all the cotton-producing areas in South Africa, needs to be undertaken to verify the outcomes of the current study.

 

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Correspondence:
L.N. Malinga
Email: lawrence.malinga@sugar.org.za