South Africa is the largest producer of sugar in Africa and one of the ten largest sugarcane producers in the world. Sugarcane in South Africa is grown under a wide range of agro-climatic conditions. Climate has been identified as the single most important factor influencing sugarcane production in South Africa. Traditionally, sugarcane mill committees have issued forecasts of anticipated production for a region. However, owing to several limitations of such committee forecasts, more advanced technologies have had to be considered. The aim of this study has been to develop, evaluate and implement a pertinent and technologically advanced operational sugarcane yield forecasting system for South Africa. Specific objectives have included literature and technology reviews, surveys of stakeholder requirements, the development and evaluation of a forecasting system and the assessment of information transfer and user adoption. A crop yield model-based system has been developed to simulate representative crops for derived Homogeneous Climate Zones (HCZ). The system has integrated climate data and crop management, soil, irrigation and seasonal rainfall outlook information. Simulations of yields were aggregated from HCZs to mill supply area and industry scales and were compared with actual production. The value of climate information (including climate station networks) and seasonal rainfall outlook information were quantified independently. It was concluded that the system was capable of forecasting yields with acceptable accuracy over a wide range of agro-climatic conditions in South Africa. At an industry scale, the system captured up to 58% of the climatically driven variability in mean annual sugarcane yields. Forecast accuracies differed widely between different mill supply areas, and several factors were identified that may explain some inconsistencies. Seasonal rainfall outlook information generally enhanced forecasts of sugarcane production. Rainfall outlooks issued during the summer months seemed more valuable than those issued in early spring. Operationally, model-based forecasts can be expected to be valuable prior to the commencement of the milling season in April. Current limitations of forecasts include system calibration, the expression of production relative to that of the previous season and the omission of incorporating near real-time production and climate information. Several refinements to the forecast system are proposed and a strong collaborative approach between modellers, climatologists, mill committees and other decision makers is encouraged. / Thesis (Ph.D.)-University of KwaZulu-Natal, Pietermaritzburg, 2005.

South Africa is the leading producer of sugarcane in Africa and one of the largest sugarcane producers in the world. Sugarcane is grown under a wide range of climatic, agronomic, and socio-economic conditions in the country. Stress factors such as water and nutrient deficiencies, and insect pests and diseases are among the most important factors affecting sugarcane production in the country. Monitoring of stress in sugarcane is therefore essential for assessing the consequences on yield and for taking action of their mitigation. The prediction of sugarcane yield, on the other hand is also a significant practice for making informed decisions for effective and sound crop planning and management efforts regarding e.g., milling schedules, marketing, pricing, and cash flows. In South Africa, the detection of stress factors such as nitrogen (N) deficiency and sugarcane thrips (Fulmekiola serrata Kobus) damage and infestation are made using traditional direct methods whereby leaf samples are collected from sugarcane fields and the appropriate laboratory analysis is then performed. These methods are regarded as being time-consuming, labour-intensive, costly, and can be biased as often they are not uniformly applied across sugarcane growing areas in the country. In this regard, the development of systematically organised geo-and time-referenced accurate methods that can detect sugarcane stress factors and predict yields are required. Remote sensing offers near-real-time, potentially inexpensive, quick and repetitive data that could be used for sugarcane monitoring. Processing techniques of such data have recently witnessed more development leading to more effective extraction of information. In this study the aim was to explore the potential use of remote sensing to quantify stress in and predict yield of sugarcane in South Africa. In the first part of this study, the potential use of hyperspectral remote sensing (i.e. with information on many, very fine, contiguous spectral bands) in estimating sugarcane leaf N concentration was examined. The results showed that sugarcane leaf N can be predicted at high accuracy using spectral data collected using a handheld spectroradiometer (ASD) under controlled laboratory and natural field conditions. These positive results prompted the need to test the use of canopy level hyperspectral data in predicting sugarcane leaf N concentration. Using narrow NDVI-based vegetation indices calculated from Hyperion data, sugarcane leaf N concentration could reliably be estimated. In the second part of this study, the focus was on whether leaf level hyperspectral data could detect sugarcane thrips damage and predict the incidence of the insect. The results indicated that specific wavelengths located in the visible region of the electromagnetic spectrum have the highest possibility of detecting sugarcane thrips damage. Thrips counts could also adequately be predicted for younger sugarcane crops (4–5 months). In the final part of this study, the ability of vegetation indices derived from multispectral data (Landsat TM and ETM+) in predicting sugarcane yield was investigated. The results demonstrated that sugarcane yield can be modelled with relatively small error, using a non-linear random forest regression algorithm. Overall, the study has demonstrated the potential of remote sensing techniques to quantify stress in and predict yield of sugarcane. However, it was found that models for detecting a stress factor or predicting yield in sugarcane vary depending on age group, variety, season of sampling, conditions at which spectral data are collected (controlled laboratory or natural field conditions), level at which remotely-sensed data are captured (leaf or canopy levels), and irrigation conditions. The study was conducted in only one study area (the Umfolozi mill supply area) and very few varieties (N12, N19, and NCo 376) were tested. For practical and operational use of remote sensing in sugarcane monitoring, the development of an optimum universal model for detecting factors of stress and predicting yield of sugarcane, therefore, still remains a challenging task. It is recommended that models developed in this study should be tested – or further elaborated – in other South African sugarcane producing areas with growing conditions similar to those under which the predictive models have been developed. Monitoring of sugarcane thrips should also be evaluated using remotely-sensed data at canopy level; and the ability of multispectral sensors other than Landsat TM and ETM+ should be tested for sugarcane yield prediction. / Thesis (Ph.D.)-University of KwaZulu-Natal, Pietermaritzburg, 2010.

There is a need in the South African sugar industry to investigate improved techniques for forecasting seasonal sugarcane yields. An accurate and timely forecast of seasonal cane yield is of great value to the industry, and could potentially allow for substantial economic savings to be made. Advances by climatologists have resulted in increasingly accurate and timely seasonal climate forecasts. These advances, coupled with the ongoing advances made in the field of crop yield simulation modelling, present the sugar industry with the possibility of obtaining improved cane yield forecasts. In particular, the lead time of these forecasts would be improved relative to traditional techniques. Other factors, such as the flexibility offered by simulation modelling in the representation of a variety of seasonal scenarios, would also contribute to the possibility of obtaining improved cane yield forecasts. The potential of applying crop yield simulation models and seasonal rainfall forecasts in cane yield forecasting was assessed in this research project. The project was conducted in the form of a case study in the Eston Mill Supply Area. Two daily time step cane yield simulation models, namely the ACRU-Thompson and CANEGRO-DSSAT models, were initially evaluated to test their ability to accurately simulate historical yields given an observed rainfall record. The model found to be the more appropriate for yield forecasting at Eston, the ACRU-Thompson model, was then used to generate yield forecasts for a number of seasons, through the application of seasonal rainfall forecasts in the model. These rainfall forecasts had previously been translated into daily rainfall values for input into the model. The sugarcane yield forecasts were then evaluated against observed yields, as well as against forecasts generated by more traditional methods, these methods being represented by a simple rainfall model and Mill Group Board estimates. Although the seasonal rainfall forecasts used in yield forecasting were found not to be particularly accurate, the proposed method provided more reliable cane yield forecasts, on average, than those using the traditional forecasting methods. A simple cost-benefit analysis indicated that the proposed method could potentially give rise to the greatest net economic benefits compared to the other methods. Recommendations are made for the practical implementation of such a method. Future areas of research are also identified. / Thesis (M.Sc.)-University of Natal, Pietermaritzburg, 2000.

The aim of this study was to evaluate potential applications of remote sensing technology in sugarcane agriculture, using the Umfolozi Mill Supply Area as a case study. Several objectives included the evaluation of remotely sensed satellite information for the following applications: mapping of sugarcane areas, identifying sugarcane characteristics including phenology, cultivar and yield, monitoring the sugarcane inventory throughout the milling season and yield prediction. Four Landsat 7 ETM+ (Enhanced Thematic Mapper Plus) images were obtained for the 2001-2002 season. Mapping of sugarcane areas was conducted by .means of unsupervised hierarchical classifications, on three relatively cloud free, Tasseled Cap transformed images. The Brightness, Greenness and Wetness bands for each Tasseled Cap transformed image were combined into a single image for this classification. The investigation into relationships between satellite spectral reflectances and phenology, cultivar and yield involved the cosine of the solar zenith angle (COST) method for atmospheric correction of all four Landsat 7 ETM+ images. Detailed agronomic records and field boundary information, for a selection of sugarcane fields, were used to extract the at-satellite reflectances on a pixel basis . These values were stored in a relational database for analysis. Monitoring of the sugarcane inventory throughout the milling season was conducted by means of unsupervised classifications on the Brightness, Greenness and Wetness bands for each of the four time-step Tasseled Cap transformed images. Accurate field boundary information for all sugarcane fields was used to mask out non-sugarcane areas. The remaining sugarcane areas in each time-step image were then classified by means of unsupervised classification techniques to ascertain the relative proportions of the different land covers, namely: harvested immature and mature sugarcane by visual interpretation of the classification results. The yield forecasting approach utilized a time-step approach in which Vegetation Indices (VIs) were accumulated over different periods or time frames and compared with annual production. VIs were derived from both the National Oceanic and Atmospheric Administration (NOAA) and Landsat 7 ETM+ sensors. Different periods or times were used for each sensor. The results for the mapping of sugarcane areas showed that the mapping accuracies for the large scale grower fields was higher than for the small-scale growers. In both instances, the level of accuracy was below that of the recommended sugar industry mapping standard, namely 1% of the true area. Despite the low mapping accuracies, much benefit could be realized from the map product in terms of identifying new areas of sugarcane expansion. These would require detailed accurate mapping. The results for monitoring of the sugarcane inventory throughout showed that remote sensing, in conjunction with detailed field information, was able to accurately measure the areas harvested in each time-step image. These results may have highly beneficial applications in sugarcane supply management and monitoring. The results for time-step approach to yield forecasting yielded poor results in general. The Landsat derived VIs showed limited potential; however, the data were only available for one season, making it difficult to quantify the impact of climatic conditions on these results. All results for the time-step approach using NOAA data yielded negative results. The results for the investigation into relationships between satellite spectral reflectances and phenology, cultivar and yield showed that that different phenological stages of sugarcane growth were identifiable from Landsat 7 ETM+ at-satellite reflectances. The sugarcane yields and cultivar types were not correlated with the at-satellite reflectances. These results combined with the sugarcane area monitoring may provide valuable information in the management and monitoring of sugarcane supply. / Thesis (M.Sc.)-University of KwaZulu-Natal, Pietermaritzburg, 2004.

The effects of irrigation-induced salinity and/or sodicity on sugarcane yield, and two growth parameters, namely stalk height and number of nodes per stalk , were investigated on a sugarcane estate in the Zimbabwean lowveld. The effects of soil salinity and/or sodicity on the size, activity and metabolic efficiency of the soil microbial community was also studied. Furrow-irrigated fields which had a gradient in soil salinity and/or sodicity which increased from the upper to lower ends of the fields were selected for this study. This gradient was recognized by decreasing sugarcane growth down from the upper to the lower ends and the appearance of salt on the soil surface at the lower ends of fields. Sugarcane growth was classified as either dead, poor, satisfactory or good; and soil samples (0-0 .15 m, 0.15-0 .3 m, 0.3-0 .6 m and 0.6-0.9 m) were taken from each of these areas. Soils from under adjacent areas of undisturbed veld were also sampled. Sugarcane growth and yields in micro-plots of the various areas of the fields were measured. Foliar samples of sugarcane were taken at 22 weeks of age and analysed for nutrient content. Soil salinity and sodicity were quantified by measuring pH(water), electrical conductivity (ECe) and cation content of saturation paste extracts and the exchangeable cation content. From this information, the sodium adsorption ratio (SARe)and exchangeable sodium percentage (ESP) were also calculated. The calcareous, vertic soils in the study area under undisturbed veld were found to have high pH values (8 to 9.5), very high exchangeable Ca and Mg concentrations and there was evidence of accumulation of soluble salts in the surface 0.15 m. Under sugarcane production, irrigation induced salinity and sodicity had developed. Under poor and dead sugarcane, high values for ECe, SARe, and ESP were generally encountered in the surface 0-0 .3 m of the profile. In addition, the pH values under sugarcane were often between 9 and 10 particularly in profiles where sugarcane grew poorly or had died. As expected, pH was positively related to ESP and SARe, but negatively related to ECe. Measurements of aggregate stability by wet sieving, the Emerson dispersion test and the Loveday dispersion score all showed that soils from the study sited tended to disperse and that dispersion was most apparent where high ESP and SARe values occurred in association with elevated pH values and relatively low ECe values. These measurements confirmed observations at the sites of low infiltration rates and restricted drainage particularly on the lower ends of fields where sugarcane had died. In addition to the above measurements it was also observed that there was a rise in the watertable under furrow irrigation and that the watertable was nearest to the surface at the lower ends of the fields. In some cases the watertable was observed to be only 0.2 to 0.3 m from the surface. Thus, death of roots due to anaerobic conditions could be occurring to a greater extent at the lower ends of the fields. Another consequence of the high watertable was that these vertic soils were observed to remain in a permanently swollen state. This limits air and water movement in the soil profile as such soils need to be allowed to dry out and crack regularly so that macroporosity can be restored. Sugarcane yield, stalk height and number of nodes per stalk were not significantly related to ECe. Sugarcane yields were, however, significantly correlated with ESP and pH while stalk height and number of nodes were negatively correlated with ESP, SARe and pH. These results suggested that sodicity was a more limiting factor for sugarcane growth than salinity. Foliar analysis of leaf tissue did not reveal substantial differences in macro- or micro-nutrient content between good and poorly-growing sugarcane. It was concluded that the gradient of decreasing sugarcane growth down the furrow-irrigated fields, with crop death at the lower ends, was the result of a combination of factors. That is, the watertable had risen due to over-irrigation and it was nearer the surface at the lower ends of the fields. Due to capillary rise of salts, this resulted in sodic and sometimes saline-sodic conditions in the surface soil. These conditions could limit plant growth through ion toxicities, plant water stress and inhibition of root growth and function and physiological processes. These would be induced by the high pH and high salt, Na and HC03- concentrations in soil solution. Poor physical conditions associated with sodicity and the continually swollen state of the soils presumably limited infiltration and aeration in the surface soil, and probably restricted root growth. In addition, it is likely that the high watertable limited effective crop rooting depth to about 0.2 m at the lower ends of the fields. The net result was that sugarcane died at the lower ends. A negative effect of soil salinity and/or sodicity was also observed on the soil microbial population. Significant negative correlations were obtained with ECe SARe and ESP with microbial biomass C and microbial activity (as measured by FDA hydrolytic activity or arginine ammonification rate). The activity of enzymes involved in C (P-glucosidase), P (phosphatase) and S (arylsulfatase) mineralization and potential nitrogen mineralization (as determined by aerobic incubation) were also negatively correlated with these factors, with the exception of arylsulfatase activity and ESP. All the above mentioned microbial population measures were also positively correlated with soil organic C content, besides potential nitrogen mineralization. The metabolic quotient, which provides an indication of stress and efficiency of the microbial community, increased considerably with increasing salinity and sodicity and decreased with soil organic C. Thus, increasing salinity and/or sodicity resulted in a smaller, more stressed, less efficient microbial community, while the turnover rate and cycling of C, N, P and S also decreased. It was concluded that salt affected soil not only causes a decline in sugarcane yield through raising the concentration of soluble salts in soil solution, but also has a detrimental effect on microbial activity and on mineralization of soil organic C, N, Sand P. / Thesis (M.Sc.)-University of Natal, Pietermaritzburg, 2001.

Crop rotation is not commonly practised in the sugarcane industry in South Africa. It has, however, proven to be beneficial to other crops in South Africa. The objective of this study was to determine the impact of soybean-sugarcane crop rotation on selected physiological and phenological indicators of sugarcane performance and its subsequent effect on cane and estimated recoverable crystal (ERC) yields. A field trial was conducted at Mount Edgecombe, where soybean cultivar A5409RG and sugarcane cultivar NCo376 were planted under drip irrigation with different management practices. After the soybean crop, the following sugarcane crop was planted and fertilized with different levels of nitrogen (N) fertilizer (50% and 100% of the recommended N rate). The effects on sugarcane growth were recorded by taking into consideration date of emergence, plant height, tiller population, leaf N, plant performance index and chlorophyll content. Sugarcane yield and quality at harvest were also evaluated. Tiller population in all crop rotation treatments at Mount Edgecombe weresignificantly (P<0.05) higher than the monocrop treatment. There was a trend of increased leaf N in all of the cane-after-soya (crop rotation) crops compared to the cane-after-cane (monocrop) treatment, although this was not significant. A similar pattern was obtained with respect to the chlorophyll content and plant performance index. Sugarcane yields at Mount Edgecombe did not differ significantly between monocrop and crop rotation treatments. Crop rotation with soybean is beneficial for cane production, but its long term impact on soil quality and farm economy requires further investigation. / M.Sc.Agric. University of KwaZulu-Natal, Pietermaritzburg 2013.

An experiment was conducted at Pongola (27°24´S, 31°25´E; 308m altitude) in South Africa to study the effects of season on growth and potential biomass and sucrose yields on nine commercial sugarcane cultivars. The treatments that were the focus in this study consisted of the cultivars NCo376, N25 and N26 ratooned in March, April, May, August and December. The crops were well fertilized and kept free of weeds and diseases. Irrigation applications were scheduled with a computer programme to keep the crops free of stress at all times. Shoot populations were counted regularly to study shoot density dynamics. Leaf appearance rates, sizes, numbers and senescence were measured to study the development of green leaf area. Green foliage, dead trash and stalk mass were measured at 4, 8, 10, 11 and 12 months in each of the starting times and also at 13 months in the March, April and May ratoon crops. The fibre, sucrose and non-sucrose content of stalks were determined on these harvesting occasions. Yields were calculated in terms of individual shoots and area (m‾²). The fraction of PAR intercepted by the developing canopies was measured until full canopy and daily intercepted solar radiation was interpolated for the entire crop. An automated meteorological station adjacent to the experiment site provided daily weather data. Shoot densities were described by thermal time, however, average peak shoot densities were lowest in the May ratoon (31.8 m‾²) and highest in the December ratoon (48.7 m‾²). Shoot senescence was most rapid in August and December ratoons. At the final harvest shoot densities were highest in the March, April and May ratoon (14.8 to 14.2 m‾²) crops. NCo376 (16.4 m‾²) and N25 (13.6 m‾²) had higher final shoot densities than N26 (10.5 m‾²). Leaf appearance rate was also well described by thermal time, however the first twelve leaves took longer to appear in crops started in December i.e. the first phyllochron was longer (109.5°C d) than in crops started at other times (80.4 to 94.5°C d). Leaves produced during the early stages of December and August ratoon crops were larger (e.g leaf number 13 of N26 was 443 to 378 cm²) than in other crops. April and May ratoon crops produced much smaller leaves (e.g leaf number 9 of N26 was 170 to 105 cm²). Leaf senescence was slower in April and May ratoon crops (0.36 to 0.46 leaves per 100°C d) than in March (0.51 to 0.59 leaves per 100°C d) or August and December ratoon crops (0.60 to 0.68 leaves per 100°C d). December ratoon crops produced very high green leaf area indexes (LAI) (>7.0) at the age of four months; all other crops had lower LAI (3.3 to 6.0) and most peaked later (8 to 11 months of age). The LAI of N25 peaked at the age of 8 months while NCo376 and N26 peaked when 10 to 11 months old. Seasonal fraction of solar radiation intercepted was high in the March ratoon crops (0.84) and declined to 0.63 in the May ratoon crops and was highest in the December ratoon crop (0.88). N26 intercepted lower fractions of PAR than NCo376 and N25, particularly in the May and August ratoon crops. Biomass accumulation, although initially slow, tended to be linear in the March, April and May ratoon crops in relation to intercepted radiation. In August and particularly in the December ratoons biomass accumulation was initially rapid, and RUEs were high (2.65 g MJ‾¹ at 114 days in the December ratoon crops). However, biomass accumulation slowed when these December ratoon crops experienced winter. Low growth rates after winter, as well as low shoot densities resulted in December ratoon crops having produced significantly lower above-ground biomass yields (4 886 g m‾² at the age of 12 months) than March, April and May ratoon crops (6 760 to 5 715 gm‾² at the age of 12 months). The December ratoon crops responded poorly to the better growing conditions in spring and second summer and accumulated little biomass after winter. N26 shoots grew rapidly during the first 6-8 months of the December ratoon crop and it yielded better than NCo376 and N25 at harvesting (biomass yields were 5.8 and 13.3% higher at the age of 12 months, respectively). April ratoons produced significantly higher biomass yields (6 760 g m‾²) than March, August and December ratoons. May ratoon crops produced the highest cane fresh mass yields (18 151 g m‾²) and April, May and August ratoons produced significantly higher sucrose yields than March and December ratoons. The highest sucrose yield was produced by the April ratoon crop of N26 (2 385 g m‾²). On average, across the five ratoon dates, NCo376, N25 and N26 produced similar sucrose yields (1 902 to 1 959 g m‾²). Foliage production was severely limited during winter while sucrose accumulation was less affected by the low temperatures, resulting in accumulation of sucrose in the top sections of the culm. Low temperatures slowed the development of canopies in March, April and May ratoon crops, but these crops were able to recover their growth rates and produced high biomass and sucrose yields at the age of 12 months. The December ratoons experienced low winter temperatures (<12°C) when they had already accumulated relatively high yields and became moribund during winter. They were unable to accumulate any significant amounts of biomass during final four months before the final harvest at the age of 12 months. NCo376, N25 and N26 all yielded poorly in the December ratoon crop. However, there are cultivars that appear to be less sensitive to the low winters and are able to yield relatively well when they are ratooned in December. Sucrose yields of March, April and May ratoons were increased substantially (10.6 to 22.7%) by harvesting at the age of 13 months rather than at the age of 12 months. The poor growth of December ratoon crops after winter is possibly due to the recently revealed feedback signaling by high sugar levels induced by low temperatures on photosynthesis. The incorporation of the effects of low temperature and the feedback signaling with the objective of better simulating yields of December ratoons is a proposed study at the South African Sugarcane Research Institute. Annual mean sucrose yields of NCo376, N25 and N26 crops were estimated to be 17% higher in March than in December ratoons. The suggested short term remedy therefore of the poor December yields is to shift milling seasons to include March and exclude December harvested crops in the northern irrigated regions. March crops grow vigorously during the months close to harvesting and therefore have lower levels of sucrose content which can be corrected with chemical ripeners. / Thesis (Ph.D.)-University of KwaZulu-Natal, Pietermaritzburg, 2009.

As is the case in many other regions in the world, sugarcane production in southern Africa is affected by a wide range of climatic conditions, which can vary considerably from location to location and from year to year. As a result, the season length and growth cycles of sugarcane in southern Africa differ greatly. Such conditions include the hot and dry regions of northern KwaZulu-Natal, Swaziland and Mpumalanga, where sugarcane is mostly irrigated, to the humid sub-tropical coastal belt extending from the far north coast of KwaZulu-Natal to areas in the Eastern Cape, as well as the cool frost prone midlands regions of KwaZulu-Natal. Owing to the wide range of climatic conditions in which sugarcane is grown in southern Africa, there are many different external factors that affect sugarcane production, including a range of pests and diseases, frost occurrences and variations in soil water. The objective of this research was to (1) identify a number of important variables that affect cane production in southern Africa, (2) employ suitable models to reflect these variables, and (3) simulate and map the extent and severity of these variables at a high spatial resolution over southern Africa. Such variables include the Eldana saccharina and Chilo sacchariphagus stalk borers, sugarcane rust fungus, heat units with selected base temperatures, frost, soil water content, soil compaction, irrigation water demand, conducive and non-conducive growing conditions, flowering proficiencies for sugarcane, sugarcane yields and yield increments per unit of irrigation. The distribution patterns of the above-mentioned variables relied greatly upon the various models employed to represent them, as well as the accuracy of the temperature and rainfall databases to which the various models were applied. Although not definitive, the models used to reflect the variables which had been identified were considered to be generally satisfactory. The resolution at which the variables which had been identified in this study were mapped, was also found to be adequate. / Thesis (M.Sc.)-University of KwaZulu-Natal, Pietermaritzburg, 2008.