Thesis (MSc. (Agricultural Economics)) -- University of Limpopo, 2014 / Maize is the most important crop in South Africa, being both the major feed grain for livestock and the primary staple food crop for the majority of the South African population. Furthermore, the maize industry contributes substantially to employment, manufacturing, foreign exchange and food security. The importance of maize in contributing to national growth is critical; this makes it meaningful to investigate the nature of maize farmers’ production decisions. This study quantifies the supply response of maize farmers to price and non-price factors in South Africa using econometric techniques. The non-price factors considered in this study are rainfall, technology and market policy. A modified Nerlovian partial adjustment model was applied on historical time series data spanning from 1980-2012 to estimate the supply response of maize in South Africa. To deal with the expected problems associated with time series data the study adopted several diagnostic tests. Results indicate a short-run supply elasticity of 0.49 and a long-run supply elasticity of 0.65, signifying that maize farmers are less sensitive to price changes. The results confirm that non-price factors seem to have more effect on maize supply in South Africa. These findings coincide with those obtained in supply response studies for field crops conducted in other developing African countries. The study also showed that non-price factors such as, rainfall, technology and market policies have a positive impact on maize production. Given the findings, the study recommends policies that focus more on non-price factors as a means of stabilising maize production. The study also recommends that Industry stakeholders and policymakers should find means to integrate the significant relationships between non-price factors and production output into future decisions and marketing policies to safeguard a healthy, growing and sustainable maize industry in South Africa. Key words: Maize supply response, Nerlovian partial adjustment model, price factors, non-price factors.

From Introduction: There is no evidence available that maize was known in the old world in ancient times. Seeds of barley and wheat have been found in ancient near eastern sites, but never has there been any trace of maize at all. Furthermore, maize as a plant is not mentioned in the Bible, and neither Greek nor Chinese literature makes any reference to maize. There is, therefore, nothing that suggests that maize was known in the Old world before about 1492. However, at that time, Christopher Columbus returned with a report about a new grain called "Maiz". At a later date explorers visiting America found that maize was being grown and consumed by the Red Indians in places as far apart as Canada and Chile. The consensus of opinion is, therefore, that maize originated in America and was only subsequently imported into Europe. However, in a very excellent paper, Dr. M.D.W. Jeffreys comes to the very convincing conclusion that "Maize, a non-self-propagating American plant, was introduced to east African littorals before the Portuguese rounded the Cape and was seen by the Chinese navigators at Melinde Circa 1414… Maize was brought to the Indian Ocean littorals by Arabs before 1400. Maize was brought into southern Africa by the Nguni by 1400 and later by the baVenda. Maize was introduced by the Dutch in 1658. There is no evidence that maize was introduced by the Portuguese. Irrespective of the exact date when maize was introduced into South Africa, it was only from the year 1840 that there was any real agricultural development in South Africa. At this date, all those who had participated in the Great Trek had more or less settled down, and substantial areas were planted with wheat, maize and oats.

Maize production in Africa is constrained by abiotic and biotic stresses. Breeders need to have information on the nature of combining ability of parents, their traits and performance in hybrid combination. This requires careful determination of genetic variability of parents, and studying associations between grain yield and adaptive traits to breed superior cultivars which are better able to withstand such stresses. Therefore, this study was aimed at selecting parental testers with best combining ability in hybrid combination with recombinant inbred lines (RILs); and studying the correlation between grain yield and its components in eastern and western South Africa. It was also aimed at determining genetic variation and associations among adaptive traits in hybrids involving RILs. The final objectives of the study were to determine cultivar superiority of testcrosses involving RILs, and to select the best cultivars within and across four different environments. The 42 RILs were crossed to 9 Zimbabwean tropical testers resulting in 1009 hybrids with sufficient seed for planting in trials. From these a sample of 87 hybrids with adequate seed were selected and planted at four sites for combining ability analysis. The hybrids were evaluated at four sites in two regions; western region (Potchefstroom research station) and eastern region (Cedara, Ukulinga and Dundee research stations), during 2011/12 season. The experiments were laid out as augmented alpha lattice design. Trials were managed in accordance with production culture for each region. All quantitative data was subjected to GenStat and SAS statistical softwares. The results from combining ability study indicated that the line general combining ability (GCA) effects played a non-significant role (p > 0.05) in determining grain yield, grain moisture and anthesis date, while they were significant (p ≤ 0.05) for the other traits such as ear prolificacy. The tester main effects were significant for all the traits except ear prolificacy and plant height. Results also revealed that all the traits were controlled by both additive and non-additive genes, where additive gene action had the most contribution to the traits. The non-additive gene action played a minor role suggesting the total GCA effects attributed to both lines and testers predominantly higher over the specific combining ability (SCA) for all traits. In general the additive effects were preponderant over the non-additive gene effects. One cross (L114 x T12) had a significant and positive SCA effect for grain yield. The correlation between grain yield and secondary traits (number of ears per plant, grain moisture content, ear height, plant height, ear position and anthesis date) suggested that indirect selection can be employed to enhance grain yield by breeding for these particular adaptive traits. Path analysis showed that plant height had the highest direct and indirect effect on grain yield indicating its importance among other secondary traits for grain yield enhancement. Phenotypic coefficient of variation (PCV) was higher than genotypic coefficient of variation (GCV) for all the studied traits across all the four environments. All the traits displayed high heritability at Potchefstroom except anthesis date which was highly heritable at Ukulinga. Cedara was the second best site for heritability of all the traits except for the number of ears per plant. The genetic advance for grain yield was the highest at Cedara followed by Potchefstroom, Dundee and Ukulinga. The hybrids exhibited different patterns of variation and distribution for all the traits. This indicated that selection strategies to exploit GCA should be emphasised. Association studies among grain yield and secondary traits such as ear length, number of ears per plant, plant height, anthesis date, silking date and ear leaf area revealed that there were significant phenotypic correlations between grain yield and secondary traits, and among the secondary traits. Ear length had the highest direct effect on grain yield at Ukulinga; number of ears per plant had the highest direct effect on grain yield at Cedara and Potchefstroom; whereas plant height had the highest direct effect on grain yield at Dundee. Grain yield was least affected by indirect factors at all the sites except Ukulinga, where anthesis date had the highest indirect effect on grain yield through silking date followed by plant height through leaf area. The study reveals that there is significant variation among the hybrids for mean performance, indicating that there is opportunity for selection. Overall the findings suggest that direct selection would be appropriate to enhance grain yield. Path analysis revealed that plant height had the highest direct and indirect effects on grain yield, indicating that plant height can be further exploited as the main trait in future breeding programmes for grain yield increment. Hybrid 10MAK10-1/N3 was the best hybrid at Ukulinga in terms of grain yield, relative yield and economic traits. Whereas hybrid T17/L83 was the best hybrid at Cedara in terms of grain yield and relative yield; however, T11/L102 was selected as the most elite hybrid with respect to grain yield, relative yield and economic traits. Hybrid T3/L48 was identified as thebest hybrid at Dundee with respect to grain yield, relative yield and prolificacy. At Potchefstroom the standard check PAN6611 was identified as the best hybrid in terms of grain yield and relative yield followed by developmental hybrid T1/L28; however, developmental hybrid T1/L28 was the best in terms of earliness, prolificacy and ear aspect. Stability coefficients and cultivar superiority index across the sites revealed that four developmental hybrids were identified as best hybrids and they performed better than the standard check. These hybrids will be recommended for further testing in advanced trials. With respect to cultivar superiority, the desired hybrids are required to combine high grain yield with economic and adaptive traits such as high ear prolificacy, low grain moisture, and low ear aspect score (desired) for them to adapt to production environments in South Africa. There was significant variation among the top 25 yielding hybrids. At least 5 hybrids combined high grain yield with the desired complimentary adaptive traits such as quick moisture dry down, prolificacy and ear aspect. The results showed that there is variation in the performance of high yielding genotypes within all the sites, and that agronomically superior cultivars can be identified. The study shows that there is significant variation among the RILs since they interacted differently with the 9 tropical testers. Even among the top 25 selections of RILs in each environment there was still variation for combinations of the desired traits. Significant associations among grain yield and other economic and adaptive traits were observed with implications for breeding strategy. Above all the significant variation gives large score for future breeding of new unique lines. / Thesis (M.Sc.)-University of KwaZulu-Natal, Pietermaritzburg, 2012.

There are concerns that genetic modification of maize with Bacillus thuringiensis may influence its structural and chemical composition which, together with the Cry1Ab proteins, may affect agro-ecosystem processes and feed quality. This study was aimed at investigating the expression of Cry1Ab protein in leaves, stems and roots of Bt maize and the effect of genetic modification (MON810) on activity of earthworms, silage quality and decomposition of residues in the field. In 2009/10 four maize cultivars; DKC61-25B, DKC61-24, PAN6Q-321B and PAN6777 were planted. Expression of Cry1Ab in leaves, stems and roots was analyzed at 6, 8, 10 and 12 weeks after planting (WAP). Earthworms were also sampled from the same treatments at 6, 9 and 18 WAP. Two silage experiments were conducted using maize cultivars, DKC80-12B and DKC80-10 produced in the 2008/09 season and DKC61-25B, DKC61-24, PAN6Q-321B and PAN6777, produced in 2009/10. The silage was sampled at 0, 2, 4, 8, 15 and 42 days in 2008/09 and 0, 8 and 42 days in 2009/10 and analyzed for Ash Free Dry Matter, Crude Fiber, Neutral Detergent Fiber, Acid Detergent Fiber, Acid Detergent Lignin, Crude Protein and Total Digestible Nutrients. Two litter-bag decomposition studies were also carried out (i) in 2008 (surface applied) using maize cultivars DKC80-12B, DKC80-10 and DKC6-125 residues and (ii) in 2009 (soil incorporated) using DKC75-15B, CRN3505, PAN6Q-321B v and PAN6Q-121. Ash-free dry matter and Cry1Ab protein were measured throughout the incubation time. There were no differences between DKC61-25B and PAN6Q-321B in terms of expression of Cry1Ab in leaves, stems and roots over time. The Cry1Ab expression levels were in decreasing order: leaves > stems > roots. No effects of Bt maize on earthworm numbers and biomass were observed. There were no differences in all silages parameters except NDF and ADF, which were higher in the Bt maize silage than that of the non-Bt maize from the 2008/09 season. The Cry1Ab levels were essentially not reduced during ensiling. The maize residues (both Bt and non-Bt maize) degraded to similar levels, either when surface-applied or incorporated into soil but soil-incorporated residues decomposed faster than surface-applied ones. Cry1Ab degraded as the plant matrix decomposed. The findings suggested that maize genetically modified with the Bt MON810 event can be grown in the Central Eastern Cape without affecting earthworm numbers and biomass, silage quality and decomposition of maize residues.

Maize is the staple food for most South Africans. This implies that any damage to the maize crop will affect food security of many South Africans. Although Eastern Cape Province is not a traditionally maize producing area, smallholder farmers in the province produce it mostly for subsistence purposes and some sell the surplus on the local market or use it to secure other good through barter trading. In South Africa, insect-resistant Bt maize/yieldgard has been used commercially for approximately 10 years now. Available impact studies on Bt maize reveal that, this technology is beneficial not only to farmers but consumers of maize products as well. Welfare gains as well as positive effects for human health are realised by both groups. Due to the costs and effectiveness associated with traditional and conventional maize stem borer control methods, Bt technology has the potential to be part of the solution. This thesis has attempted to investigate the economic viability of planting Bt maize seeds under smallholder farming conditions and identify factors as well as perceptions relating to attributes of Bt maize and to analyze the relationships between those perceptions and choices regarding use of Bt technology. Data was collected from 90 households who were selected using purposive sampling through the use of the snowball method. To collect data, a questionnaire was administered through face-to-face interviews. Gross margin analysis revealed that Bt maize is a more profitable option as compared to conventional maize seeds. Furthermore, econometric analyses, through use of the binomial regression model revealed that perceptions could be used to distinguish between users and non-users of Bt maize seed in the Eastern Cape Province. Results of inferential analysis indicate that the statistically significant variables at 5% level are gene erosion, quality and nutrition of products and food labels for Bt maize products perceptions. On the other hand, low expenses, seed market availability and farmers’ knowledge perceptions were significant at 10%. These findings suggest that an adjustment in each one of the significant variables can significantly influence the probability of Bt maize adoption. In view of the research findings, several policy proposals are suggested to support policy formulation. Key words: Bacillus thuringiensis (Bt) maize, yieldgard, smallholder farmers, perceptions, Flagstaff, gross margin analysis, binomial logistic regression model, Eastern Cape Province.

Thesis (MSc. Agriculture (Agronomy)) -- University of Limpopo, 2019 / The traditional practice of farmers in Limpopo Province is to mixed and broadcast crops at planting without definite row arrangement. This practice hinders farm input application and results in low crop yields. Strip intercropping, where crops are planted with definite row arrangement, has the advantage of reducing inter-species competition, optimise plant population and increasing crop yield. This study aimed at improving cowpea-maize cropping systems using strip intercropping. The experiment was conducted at University of Limpopo farm and Ga-Thaba village. Five cowpea varieties (Glenda (check)), IT86K-499-35, IT82E-16, IT86D -1010, TVu-13464 and maize (PAN 6479) were evaluated using randomised complete block design with three replications. Data collected were days to flowering, days to maturity, plant height, canopy width, peduncle length, pod length, number of pods/plant, 100 seed weight, grain yield, fodder weight and land equivalent ratio was also determined. Data were analysed using the Statistix 9.0. The results revealed that in both locations TVu 13464 flowered early (50 days) respectively. At University of Limpopo farm TVu 13464, IT82E-16 and IT86D-1010 matured early (89, 88 and 91 days). At University of Limpopo farm, IT82E-16 had high cowpea grain yield (2230 kg/ha) under monocropping and also produced high grain yield of 1373 kg/ha during 2016/17 season. At Ga-Thaba, IT86D-1010 produced high cowpea grain yield of 1085 kg/ha under monocropping and during 2015/16 (660 kg/ha) while IT86K-499-35 also produced high grain yield of 915 kg/ha during 2016/17. The varieties showed yield stability depending on different locations. At University of Limpopo farm, strip intercropping achieved high maize grain yield of 3961 kg/ha during 2016/17. At Ga-Thaba, strip intercropping produced high maize grain yield 747 and 1024 kg/ha during 2015/16 and 2016/17, respectively. Monocropping produced low maize grain yield during 2015/16 with a mean of 425 kg/ha and mixed intercropping had mean of 499 kg/ha during 2016/17. The calculated LER for two crops over two seasons under strip intercropping ranged from 1.25 and 2.14, whereas under mixed intercropping, it ranged between 0.73 and 1.05 over two seasons at University of Limpopo farm. TVu 13464, IT82E-16 and IT86D-1010 are promising varieties for strip intercropping in low rainfall areas because of their early maturity and high grain yield. The calculated LER for two crops over two seasons xx under strip intercropping ranged from 1.62 and 2.98, whereas under mixed intercropping, it ranged between 0.76 and 1.67 in both seasons at Ga-Thaba. / National Research Foundation (NRF) and Water Research Commission (WRC)

MENVSC (Geography) / Department of Geography and Geo-Information Sciences / Climate variability and change directly affect agricultural production. This is because the agricultural sector is inherently sensitive to climatic conditions and is one of the most vulnerable sectors to risks and impact of global climate change. The aim of this study was to determine maize producer's vulnerability and assess the impact of climate variability and change on maize production in the Makhuduthamaga Local Municipality, of Limpopo Province, South Africa. Climatic and maize yields data utilized in the study are for the period 1985 - 2015). Interviews were also conducted with the producers and various officials from government and non-governmental sectors. The results illustrate significant rainfall and temperature variations both spatially and temporally. The variations observed in the average rainfall and rain days for the period under consideration were not related to the variation in yield of maize for the same period. The regression results revealed low R² values, indicating a weak relationship between maize yields, rain days and rainfall. Furthermore, the results revealed a significant positive relationship between annual rainfall and temperature (r²<0.05 and P<0.05) but not a significant relationship with maize yields. The results of the qualitative data showed that the producers’ perception of the occurrence of climate variability was high, as 65.7% of the respondents indicated that the state of climate is increasingly variable. About 61.5% of the producers implemented or adopted an adaptation strategy to cope with the perceived climate variability and change. Age, gender and access to extension services were determined as important factors that determine the adoption of adaptation strategies. The vulnerability assessment revealed that producers were highly vulnerable to changing climate; this exposes producers to the risks of crop failure, loss of income and food insecurity. The study recommended (a) intervention and adaptation strategies that target mitigation of decreased rainfall impacts (b) increased access to extension service (c) empirical research around the impacts of climate change to increase producers’ level of awareness. / NRF

Thesis (M.Sc. Agriculture (Agronomy)) -- University of Limpopo, 2019 / Limpopo Province is a semi-arid region prone to drought. Crop yields continue to decline due to low soil fertility and poor cropping systems. Cowpea is nutritionally rich in proteins essential for human consumption and livestock feeding. It fixes N2 which becomes available for the succeeding crop in rotation. For this reason, it is used as a companion crop in cereal-legume intercropping systems. Maize is one of the most important grain crops in South Africa, it serves as the major staple food for many households. Phosphorus is one of the macro-nutrient elements required by crops to produce satisfactory yields. The interactions between different rates of P fertilisation and cowpea-maize strip intercropping have not been studied in detail under rain-fed maize-cowpea strip intercropping in Limpopo Province. Many smallholder farmers in Limpopo Province obtain low yields due to the practice of mixed intercropping. Two season (2014/15 and 2015/16) experiments were laid out in a split-split plot design at Syferkuil farm to determine the performance of cowpea and maize varieties in cowpeamaize strip intercropping at varying P application rates. Treatments consisted of factors namely, P levels (0, 15, 30, 45 kg/ha), cropping system (monocropping and intercropping), maize varieties (WE3127 and ZM1423) and cowpea varieties (PAN311, TVu13464, IT86D-1010 and IT82D-889). Data were collected from growth and yield parameters that included (number of days to flowering, plant height, number of days to physiological maturity, root weight, number of pods per plant, unshelled net pod weight, number of cobs per plant, unshelled net cob weight and grain yield) in order to determine their performance. Results obtained revealed that P application levels significantly influenced most of the measured growth and yield parameters of both crops. PAN311 flowered earliest (49 days) across P levels. Increasing P application hastened the maturity of the varieties of PAN 311 and TVu13464 in both seasons. The P levels of 30 and 45 kg/ha reduced the number of days to maturity as compared to 0 and 15 kg/ha. TVu13464 variety produced more pods per plant (30) than other varieties. PAN311 yielded more grains (2491 kg/ha) than other varieties. Maize varieties performed well between P applications of 30 and 45 kg/ha. WE3127 yielded 3462 kg/ha whereas ZM1423 yielded 3306 kg/ha. Intercropping vi system performed better than monocropping system based on the measured growth and yield parameters. Two promising cowpea varieties (PAN311 and TVu13464) performed well and were selected based on their early maturity, drought tolerance and high yielding. Increasing P application levels increased crop yield. Optimum P levels for cowpea-maize strip intercropping were between 30 and 45 kg/ha. The calculated LER values were greater than one which indicates that intercropping was advantageous in land utilisation. The study showed the importance of P application in improving cowpea yield in cowpeamaize strip intercropping. / National Research Foundation (NRF) and University of Missouri, USA

MSCAGR (Soil Science) / Department of Soil Science / Maize (Zea mays L.) is widely grown in the semi-arid regions of South Africa mainly for its grain that is used for direct human consumption, feed for animals and raw materials for the industries. The challenges of soil infertility, water supply, and availability of high yielding cultivars remain a major constraint for its production in this environment. These constraints are a major threat to sustainable crop production and food security. Maize/lablab Zea mays L.\ L. purpureus) intercropping system could thus become an option for food security among small scale maize producers in dry environments. Preliminary studies show the huge potential of maize/lablab intercropping in the semi-arid environments of the North-Eastern South Africa. Therefore, this study aimed to assess the effects of maize/lablab intercropping on soil water content, nitrogen dynamics and crop productivity based field experiments and crop simulation modeling using the model APSIM. The trials were conducted at two sites (Univen and Syferkuil) in Limpopo province, South Africa, for two seasons (2015/2016) and 2016/2017). The treatments consisted of; (i) sole maize (ii) sole lablab (iii) maize and lablab planted at the same time (Maize+lablab-ST) and (iv) maize with lablab planted 28 days after maize (Maize+lablab-28).The treatments were laid out in an RCBD replicated 4 times, with individual plots size measuring 4.5 m × 4 m (18 m2) and the layout of the field as consisting of 4 plots per block giving a total of 16 plots in 4 blocks. The following parameters were determined: soil water content, soil NO3--N and NH4+-N levels, dry matter and grain yield. The APSIM-model (version 7.7) was then used to simulate maize grain yield and dry matter production to assess risks associated with the production of maize/lablab intercropping. The results obtained from this study showed that maize/lablab intercropping had significant effects on measured parameters (grain, biomass yield soil water content, and N-minerals). Maize+lablab-28 produced 46 % higher grain yield than sole cropping (24%) and maize+lablab-ST) (30%). The results also showed variation in soil water content at different depths among the treatments. The soil water content was increased with depth. The intercropped plots and lablab sole had significantly higher soil water content than the sole maize. At all depths, the highest soil water content was obtained under sole lablab followed by maize+lablab-ST and maize+lablab-28. It was notable however that maize/lablab intercropping showed a higher NO3--N and NH4+-N levels at all depths. At both sites, the soil NO3--N showed a sharp drop at V7 sampling time. The results showed the benefits of intercropping in comparison to sole cropping as demonstrated by positive land equivalent ratios of >1 for both cropping systems in both years and sites. Modelling exercises showed that APSIM was able to simulate the results sufficiently. In the simulation experiment, a stronger negative effect of planting lablab with maize simultaneously was found. Hence, delayed planting of lablab should be a standard practice / NRF

Maize is the most grown crop by the farmers in Jozini. Therefore, the main objective of the study was to assess the economic impact of climate change on maize production under different farming systems in Jozini Municipality in KwaZulu Natal (KZN). The study was looking at the smallholder farmers producing maize under dryland and irrigation system. A total of 100 farmers were selected for the study (40 from dry-land and 60 from irrigating farmers). Cluster and random sampling procedures were used to select the sample. Questionnaires were used for the collection of primary data, from the respondents (maize farmers). Data was analysed using descriptive statistics (frequency, percentages), gross margin, regression analysis and the Ricardian model. Data for computing gross margins and net revenue was taken from the on-farm trials. Gross margin was used on regression analysis and the net revenue was used on the Ricardian modelThe results of the regression analysis indicated that land size, farmer’s experience to farming, level of education, use of fertiliser, use of irrigation and the yield obtained were significant and have a positive relationship with farmers gross margin. The results of the Ricardian model indicated that climate change affects both farming systems, but farmers that are producing under dryland are the most affected farmers because they rely more on climate variables especially rainfall for their production. So a change in climate variables affects maize farmers’ productivity and thus affecting farmers’ gross margin and net revenue. The study recommends that the farmers must use irrigation in order to support maize production even in the absence of rainfall. Farmers must also adapt to the short growing season so that they will be able to produce even in the presence of climate change.