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By E. J. Y., G. J. McLachlan, E. Amini, Koha

Inferring individual component flotation rates from recovery-time data of ore complexes is important in optimising and designing minerals processing plants. However, existing two-component first-order flotation models are computationally intensive to solve using conventional non-linear least squares regression. In this paper, a Convolutional Neural Network (CNN) is used to approximate the inverse function which predicts the two-component first-order model parameters using recovery-time data. This paper compares the accuracy and computation speed of the proposed CNN against traditional non-linear least squares regression on 1 million generated data based on a known two-component firstorder kinetic model. It is shown that using a CNN is possible to approximate the inverse function for the non-invertible two-component model with recovery-time as an input matrix for convolution operations. The CNN method is 450 times faster to compute than the Trust-Region (TR) non-linear least squares regression algorithm. However, the CNN model is less accurate compared to the TR algorithm overall. Keywords: Flotation kinetics, convolutional neural network, inverse problem, modelling and simulations

Jan 1, 2020

By X. Zhang, E. Li, Y. Xiao, Z. Yu, H. Han, J. Xie, J. Tian, W. Sun, K. Hong

In a pulp environment, the surface properties of magnesite and dolomite tend to be similar, due to the re-adsorption of dissolved calcium species, which makes the flotation separation difficult. In this paper, the chelating reagent EDTA is introduced to eliminate the adverse influence of the calcium species and to restore the selectivity of magnesite-dolomite separation using sodium hexametaphosphate (SHMP) as a depressant. Flotation experiments confirm that the recovery of magnesite improves significantly in the presence of EDTA. Zeta potential experiments confirm that the negatively charged EDTA4+ and HEDTA3+ species can form soluble and stable chelates with positively charged Ca2+ and Ca(OH)+ species preventing their adsorption on the magnesite surface. Adsorption measurements prove the addition of EDTA can decrease the adsorption of depressant SHMP on the magnesite surface. X-ray photoelectron spectroscopy (XPS) measurements further confirm the transformation from the surface of magnesite to dolomite in the presence of calcium ions, and the possible adsorption mechanism of EDTA and SHMP on the magnesite and dolomite surface. Key words: Magnesite; Dolomite; Surface dissolution; Flotation separation

Jan 1, 2020

By B. Maybee, J. Venter, J. Wesseloo

The selection of open-pit slope angles involves high-value decisions with small changes in slope angle, often representing significant changes in net present value. The existing methods used to define design acceptance criteria have evolved from factor of safety to probability of failure (P[F]) to risk consequence to risk frontiers, which represents current state of the art. Current design acceptance measures are based on references to published tables representing the experience and judgement of their authors, who did not specify the purpose of the measures contained therein. As the purpose of the published design acceptance criteria is not specified (i.e., definite stability, marginal stability, optimization, etc.), such tables cannot be used to achieve optimum slope angles that maximize profitability. This paper develops a design acceptance criterion that maximizes profitability by defining a formulation for optimum risk that balances expected risk and reward. The model developed is titled the Mining Risk Model (MRM), and is applied to open-pit slope angle selection through an equation for optimum probability of downside (P[D]O) that balances the upside or opportunity, the P[F], and the downside impact. This formulation for optimum risk is unique, as many authors have presented objective functions for their risk models that can be optimized, but none of the sources reviewed contained a formulation for optimum risk. The MRM is sufficiently flexible to allow the design performance measure that drives P[F], and hence P[D]O, to be selected based on the intended goal. Furthermore, the essential information that must be known to quantify optimum risk is defined. This allows users to determine what information to collect for optimum risk decisions. A further benefit of the MRM is that slope angle decisions and pit shells can be ranked to select the best option, and a threshold is provided that separates acceptable from unacceptable decisions. Finally, the workflow and information required to determine optimum risk are presented.

Sep 9, 2024

By T. Song, X. Wang, X. O. Xia, X. J. Luo, B. Chen

Interparticle breakage is the main crushing mode of an inertia cone crusher according to its working principle and feeding condition. In this paper the breakage behaviour of an inertia cone crusher is investigated, based on energy controlled compression combined with the vibration theory, rather than geometry controlled compression (form conditioned) which plays a major role in conventional eccentric cone crushers. The effect of feeding and operating conditions on breakage behaviour was described quantitatively from the perspective of energy consumption and product size distribution. The influence of feeding conditions, discharge size settings and vibration exciter speeds on the crushing process and product quality has been studied according to the results of laboratory crushing experiments. The results of the experiments show that the particle size of broken products becomes finer with the decrease of a discharge gap within the gap range selected by the experiment. The product size increases significantly when the gap approaches the upper limit of 6 mm. The variation of eccentric speed has a more prominent effect on reducing the product size compared with the change of discharge gap. The change in product size is not apparent when the eccentric speed rises to a certain level. The throughput of an inertia cone crusher is sensitive to the change of discharge gap, which increases linearly with the discharge gap and decreases with the eccentric speed. The change of feeding conditions has little influence on the crusher throughput. Keywords: Inertia cone crusher, interparticle breakage, energy consumption, product size distribution

Jan 1, 2020

By M. Smit, N. C. J. Dempers, S. Lunkov, C. Saguru, J. Nel

A common method for the recovery of copper is by heap leaching, solvent extraction, and electrowinning. During solvent extraction, the solution is continuously recycled, and it is necessary to remove impurities that build up in the raffinate. For the process investigated in this study, the main impurities include Fe, Co, As, and Zn. Recovery of these impurities can provide economic benefits while adhering to legal and environmental constraints. Such impurities are often removed by precipitation utilizing a neutralizing agent, such as limestone or lime, but it is also possible to remove the impurities by sulfide precipitation. Sodium hydrosulfide (NaHS) is used to selectively precipitate copper, arsenic, and zinc from a solvent-extraction raffinate stream. The resulting sulfide precipitate is bagged and sent to a roaster for further treatment. The design of the sulfide precipitation was investigated to optimize the processing conditions (including temperature, pressure, and residence time), the materials of construction, and the toxicity and explosive nature of the hydrogen sulfide gas produced

Jan 1, 2023

By A. S. Geldenhuys, L. S. Leal Filho, D. A. Deglon, T. C. Souza Pinto

The Brucutu iron ore mine (Minas Gerais, Brazil), is Vale`s largest iron producing operation achieving around 21 million tons by flotation of iron ore pellet feed per annum. The run of mine is mainly composed of hematite (70%) and quartz (30%). After preparation (comminution and sizing), the slurry is submitted to reverse cationic flotation of quartz under basic conditions (pH=10.5). Corn starch (500g/t) is used to depress Fe-bearing minerals and alkyl (C10) ether amine is the collector for quartz. The flotation circuit is arranged in a “coarse” section utilizing dated 28m3 square Wemco cells, and a “fine” section utilizing modern 160m3 tank cells. The “coarse” flotation circuit treats material from the deslime cyclone underflow while the “fine” circuit treats material from the deslime cyclone overflow and the pulp product from the “coarse” circuit scavenger 2 bank. Evaluation of process performance is of high importance as even small gains can lead to large improvements for this high throughput plant. Cell-by-cell samples of the froth products, selected feed and pulp-products were analyzed for flow-rate, overall chemical composition, and particle size distribution. Bank-by-bank samples of the feed, froth and pulp products were analyzed on an assay-by-size basis. In addition, the flotation cells were hydrodynamically characterized and gas dispersion parameters assessed. The detailed experimental program resulted in a thorough characterization of the process and enough information to produce a calibrated floatability component model. Longer mainline residence time results in significant Fe2O3 losses while yielding little benefit in terms of SiO2 grade. Scavenger 2 has twice the residence time of scavenger 1 while having to treat only 10% of the SiO2; resulting in high Fe2O3 recoveries to the froth and poor separation. In addition, it is shown that the Fe2O3 exhibits true flotation behavior resulting in increased Fe2O3 losses. The detailed data collection campaign coupled with in depth data analysis and modelling gives unprecedented information and highlights avenues for optimization that was previously unknown. Keywords: Froth Flotation, Process modelling, Process evaluation, Metallurgical survey

Jan 1, 2020

By C. O’Donova, E. Adam, L. A. Torres-Cruz

High-profile failures of tailings dams illustrate the significant safety challenge they pose. The decant pond of such facilities plays an important role in their mechanical stability. This study investigates the feasibility of using public multispectral data collected by the Sentinel-2 satellite mission to monitor the area of the decant pond. The Sentinel-2 mission has a revisit time of 5 days and the data used herein has a spatial resolution of 10 m/pixel. We considered two water-detection metrics: the normalized difference water index (NDWI) and the near-infrared (NIR) reflectance. Implementation of the method at a South African platinum tailings dam illustrates the capabilities and limitations. Public, sub-metre resolution true-colour imagery served as validation data. There is good agreement between pond area measurements based on Sentinel-2 and the validation imagery. These results suggest the feasibility of using Sentinel-2 data to supplement the monitoring of the decant pond.

Apr 2, 2022

By S. Stuurman

Inorganic acids such as sulphuric acid have found use together with certain reducing agents in leaching of copper-cobalt oxide ores. These reagents are not ideal due to the adverse effect the inorganic acids generally have on the environment and the high costs of the reducing agents. In this study a copper-cobalt oxide ore from the Central African Copperbelt was leached in two different environments; sulphuric acid in conjunction with hydrogen peroxide as a reducing agent and tartaric acid. The effects of acid concentration, reducing agent concentration, and temperature were independently determined for both leaching environments. The sulphuric acid concentration was varied between 0.4 M and 1.2 M and the concentration of hydrogen peroxide between 4.0 M and 6.5 M, while the tartaric acid concentration was varied between 0.15 M and 0.35 M. The temperature was varied between 20°C and 50°C. The results showed that the extraction of both copper and cobalt increased with sulphuric acid concentration, reaching a peak at approximately 0.8 M and then decreasing at higher acid concentrations. A similar increase and decrease in metal extraction was observed when the reducing agent was increased. In leaching with tartaric acid, the extraction of cobalt was much higher than that of copper, although extraction of both metals increased with acid concentration. Additions of small amounts of hydrogen peroxide were found to increase cobalt extraction in tartaric acid but had a minimal effect on copper. An increase in the solution temperature had a significant effect in the organic acid environment, with the effect on cobalt extraction being much more pronounced than on copper.

Jan 1, 2014

By A. J. S. Spearing, M. Sharifzadeh, K. V. Jessu

Empirical pillar design methods are commonly used in the mining industry. The parameters within which these methods are valid are frequently unknown to the user or ignored. In addition, empirical design may not consider essential parameters such as blasting effects, orebody dip and the presence of geological structures, which all adversely affect the stability of the pillars. This can result in potentially serious pillar design strength over-estimates. Although the commonly based tributary area method is generally conservative, as the spans are seldom that large relative to the depth, failing to consider other relevant parameters can result in errors. Problems associated with an under-designed pillar can range from a local pillar collapse to a catastrophic chain reaction collapse (or run). Over-designed pillars are generally safe but reduce the extraction of the orebody, thus adversely affecting the profitability of the mining operation. We used laboratory tests and numerical modelling to understand the effects of pillar orientation, blasting and the presence of discontinuities on pillar strength. Reduction factors were developed with these models to be implemented in conjunction with the existing empirical pillar design methods. For any pillar or mine design, once it is implemented, the actual performance of the system must be checked regularly by observation and monitoring and adjusted if needed. The pillar design approach outlined in this paper can better optimize the pillar mining method by considering other generally ignored but important parameters, thus improving safety, productivity, and economic aspects.

Oct 1, 2022

By D. Menne

A comminution model and a quick laboratory milling test procedure are presented. These allow the determination of milling parameters for the - optimization of ball size and pulp density in operating mills estimation of the performance of new feed stocks in an existing mill - estimation of the expected milling performance for a new project. Information on the estimation of the size of mills to deliver specified amounts of comminution energy, and amount of expected ball, rod, and liner wear to allow cost estimates for new projects, is also included.

Jan 1, 1983

By J. D. Swanepoel, S. Horn, C. J. Badenhorst

Diesel particulate matter (DPM) is the particulate component of diesel exhaust, which includes diesel soot and aerosols. When released into the atmosphere, DPM can take the form of individual particles or chain aggregates, with most in the invisible sub-micrometer range of 100 nanometres. The main particulate fraction of diesel exhaust consists of fine particles and because of their small size, inhaled particles may easily penetrate deep into the lungs. The rough surfaces of these particles make it easy for them to bind with other toxins in the environment, thus increasing the hazards of particle inhalation. DPM is a significant health hazard in underground mining operations, where the use of dieselpowered equipment in confined spaces can lead to high levels of exposure among people working in these environments. Classified as a carcinogen by the International Agency for Research on Cancer (IARC), DPM has been linked to severe health effects, including respiratory and cardiovascular diseases, as well as an increased risk of lung cancer. Effective management of DPM is essential not only for protecting people’s health but also for ensuring regulatory compliance, maintaining operational efficiency, and safeguarding the long-term viability of mining companies.

Mar 5, 2025

By HORNICKA OSTRAVA

The Czechoslovak Scientific-Technical Institute has arranged the international conference 'Hornicka Ostrava' for four or five days at the end of October, 1969, as part of the preparation for the international 'Miners' Congress' on deep coalextraction in 1970. The keynote of the conference is 'New Techniques in coal mining,' and will be covered by five groups dealing mainly with: 1. New trends in the opening of mines, optimal parameters, projections, equipment, utilization of computers for economic analyses, etc. 2. Increase in efficiency of coal extraction in deep mines, technology, concentration, pressure control, optimization of material and coal transport. 3. Modernization of devices for increased safety and working conditions, new trends in explosives, new techniques for reducing environmental diseases. 4. Innovations in deep level coal extraction, mechanization, rationalization, automation, etc. 5. Other topics about modern techniques in mining. Address your enquiries to: Ing. Karel Kalas (Secretary of the Conference), Dum Techniky Cs YTS, Ostrava 1, Jesenkiho 7-9, Czechoslovakia.

By D White, L. Lorenzen

Sampling and metallurgical testwork during various phases of engineering studies is of paramount importance for a robust processing plant design. When developing a process flowsheet, risks in achieving desirable financial outcomes are minimised by ensuring that appropriate sampling and adequate metallurgical testwork support the engineering and cost estimation at each phase of project development. The quality and type of samples used for metallurgical testwork are just as important as the metallurgical testwork itself. The key characteristic required of any sample is that it represents some defined portion of a mineral deposit. Representivity should consider the spatial orientation, lithology, alteration, degree of oxidation, mineralogy, and competency of the ore such as hardness and abrasiveness. Statistically representative sampling procedures and an appropriate metallurgical testwork program should be designed to bring metallurgical understanding up to feasibility study standard and to give a basis for process plant design. The authors have observed that the quality of sampling and quantity of metallurgical testwork carried out during the various phases of engineering studies are often insufficient to truly support a robust plant design. Some designs are based on benchmarks of apparently similar ore bodies or rely on buoyant metal prices supporting cash flows until rectifications can be implemented. The paper will discuss important aspects of sampling and testwork required for engineering studies in designing process plants. Keywords: Sampling, metallurgical testwork, studies, design

Jan 1, 2020

By F. Wang, P. Rosario, A. Vazirizadeh

Advances in data science, machine learning, and artificial intelligence are transforming mining and mineral processing, and making them more algorithm intensive. The paradigm is shifting from one of detection and control to one of prediction and optimisation. To build up reliable prediction and optimisation models these steps should be passed: collect, aggregate, cleanse, and process large amounts of complex, structured, and unstructured data as a first stage. Next, the right tools must be used to extract meaningful features from the operational data for the build-up of a prediction model. A grinding circuit is one of the challenging areas in terms of determining its overall efficiency and the prediction of product quality. In a processing plant, some of the KPIs are typically unmeasurable or infrequently measured for real-time application, e.g. ore grindability and grind size. However, these variables are required to calculate the grinding circuit efficiency and to model the operation performance. In this paper, advanced analytic tools have been used to extract one selected KPI (cyclone overall P80 or final grind size) and its relationship with measured variables for an industrial dataset. The results illustrate that the performance of the grinding circuit can be predicted for real-time monitoring by means of measured data. Keywords: Grinding circuit, data-driven, machine learning, process modelling, hybrid modelling

Jan 1, 2020

By C. A. Green, M. A. T. Cocquerel, R. T. Gates

"Engineering studies by Selection Trust, Limited, initially in connection with the development of a copper and nickel deposit for Bamangwato Concessions, Limited, and subsequently for several other clients, have required a large number of metallurgical design calculations. The flash smelting process, developed by Outokumpu Oy in Finland, has been selected as the most suitable method for these projects and the computer programs described in this paper have been developed to facilitate the computation.The data required by the programs arc the chemical and mineralogical analyses of the concentrate, gangue and flux materials and the specification of possible fuels. The required grade of furnace matte is set as the main design parameter and the programs calculate detailed heat and material balances for the smelting process."

Jan 1, 2014

By G. R. Lane

My opportunity to serve as President of the prestigious Southern African Institute of Mining and Metallurgy (SAIMM) was made possible by an Anglo American scholarship 39 years ago—a pivotal moment that set me on a career path spanning various roles and start-up ventures in the mining industry. Over the past decade, I have been privileged to broaden my experience by consulting across diverse industries globally. This exposure revealed something profound: what I had previously considered mining-specific challenges are, in fact, universal across many sectors. At its core, a mining operation is a complex system of interconnected activities—from exploration through mining operations like drill and blast, load and haul, to beneficiation, and outbound logistics. My cross-industry work has clearly shown that diverse sectors, such as chocolate manufacturing, tissue paper production, toilet paper converting facilities, labgrown diamonds, or high-tech equipment lifecycle management, all rely on value streams of interconnected activities to transform products. The objective is to maximise throughput while effectively managing performance variability. The primary difference lies solely in the specific technical expertise required for each industry, such as chemical, mining, processing, or metallurgical engineering. Across all these industries, I have observed a consistent pattern, that is, performance is primarily driven by individual efforts, where people react and work diligently as situations unfold in real-time. General managers and their teams often operate tactically, focusing on explaining yesterday’s poor performance rather than proactively setting up operations for success. This often resembles an ‘‘under-7s soccer match’’, with everyone chasing the ball. The common response to issues is to add more ad hoc meetings. This effort-driven organisational behaviour persists regardless of whether operations are greenfield digital manufacturing facilities, advanced digital mines with advanced process control, or operations run on paper and Excel spreadsheets for data acquisition. Paradoxically, more real-time data can lead to increased data noise, greater indecision, and sometimes, lower performance. Despite value streams often operating significantly below capacity, organisations continue to invest heavily in additional equipment or in ‘‘glossy brochure promises’’ of Industry 4.0 digital technology and real-time data solutions, which frequently fail to deliver value. This leads to a critical question: Have we underinvested in our most valuable resource— people? Even Tesla faced this challenge with their underperforming fully automated Model X facility. We must shift our focus to designing the ecosystem, or operating model, of our organisations. This extends beyond the traditional triad of people, process, and technology, and moves beyond simplistic views of change management. Artificial Intelligence (AI) has the potential to add significant value, but it also introduces another layer of complexity into designing the organisation of the future. My full presidential address below at the SAIMM AGM discussed the symptoms of an effort-driven organisation and covered the fundamental building blocks and requirements of an operating model, including recommendations on implementing a people-centric approach.

Oct 2, 2025

By Zdenek Kunicky

Kovohute Pribram is a plant recycling lead wastes, lead acid batteries in particular. Relevant new recycling technologies are being gradually developed. Outdated technology of smelting lead plates has been replaced by a new technology based on processing of entire batteries in a blast furnace according to the process developed by know-how of German Varta company. The classical Harris refining has been substituted by the oxygen refining. New technologies aimed at utilization of related wastes arising from refining lead bullion in Kovohute Pribram are being developed in house. At present, a new technology of utilization of spent battery acid for extracting zinc from various wastes has been developed. Zinc oxide dross from alkaline refining of lead bullion, during which residual zinc from the preceding vacuum de-zincing is removed as well as waste zinc galvanic sludges (a product of neutralizing precipitation of metals from industrial wastewaters with lime) were treated. In this study, the new developed technology yielding basic zinc carbonate - a valuable raw material for zinc electrowinning, is described together with the first experience of applying the developed method to processing zinc wastes on a pilot scale. Most of the equipment used in the past to regenerate alkali solutions originating from Harris refinery was utilized in the practical realization of this new technology.

Jan 1, 2008

By K. J. Kruger

Aluminium alloys have gained popularity in many industries due to their high strength and low weight. One shortcoming of aluminium alloys is their poor resistance to abrasion and erosion wear compared to materials such as stainless steels. In this project, aluminium alloy 2014 (AA2014) was coated with a 1.5 mm thick laser-deposited layer composed of silicon, copper, and aluminium with the aim of increasing the wear resistance. The amount of silicon, copper, and aluminium added to each sample was determined by a mixtures model. It was discovered that the Al-Cu system is very sensitive to silicon additions and that wear resistance depends on the primary phase to solidify as well as on the final phase distribution. Two primary phases were identified; alpha aluminium and theta intermetallic. It was observed that the clad layer increases both the hardness and wear resistance of AA2014, and that the material solidifying as primary alpha aluminium displayed a lower hardness but higher wear resistance than the samples containing primary theta phase. All clad layers performed better in terms of wear resistance than the unclad samples. The knowledge gained and principles used in this project could be applied to many other aluminium alloys.

Jan 1, 2014

"Chairman: Professor J. C. Griffiths Rapporteur: Mr J. P. G. PRETORIUSPapers:Mine-mill production scheduling by dynamic programming by R. J. Roman Optimization of a large mining venture by J. C. Paynter, B. K. Loveday and C. G. Robinson Economic surface mining of multiple seams by T. V. Falkie and W. E. PorterIn introducing his paper, Mr Roman said that whereas in manufacturing plants the yearly production levels were usually chosen to produce the largest annual cash flow, in a mining operation, the raw materials (ore) were exhaustible so that the production had to be scheduled to maximize the total net present worth of the operation. This optimum production schedule could be determined by using dynamic programming. The required information was readily available to management at most mines. The 'possible operating range' of production rates lay between the rate with the highest profit per ton. and that with the highest profit per year. The optimum production rate started typically at the top of this range and decreased slowly as the deposit was depleted.Dynamic programming was used to determine several production schedules for a hypothetical mine-mill complex. The effects of changes in the ore grade estimates, size of deposit and acceptable rate of interest on the production schedule were taken into account. Apart from the fact that the net present worth of the overall profits was larger than that obtained by conventional methods, it appeared from the cases studied that the amount of metal recovered was also greater.Dr it P. King commented that this was a very interesting application of dynamic programming. He pointed out, however, that the market price of the metal was likely to vary significantly and randomly during the life of the mine, and he suggested that the problem should, therefore, be reformulated as a stochastic dynamic programming problem.If the price of the metal rose to abnormally high levels, a much higher than normal production rate could be expected. The results of analyses given in Table 5 showed that the production rate was a function of market price. In his view the stochastic problem could be solved just as easily as the deterministic problem.In reply to a question by Dr King as to whether the function relating recovery to production rate (Table I) was based on real data, the author replied that it was based on the results of an analysis conducted at the Union Carbide Corporation's Pine Creek tungsten mine in California.Dr D. M. Hawkins stated that costs were incurred when the production rate was altered, for example, in appointing or laying off staff, and that in practice it may be necessary to take these costs into account in finding the optimum production rate. Mr Roman replied that, while normal administrative costs were accounted for, the additional costs incurred in appointing and laying off staff were not taken into account."

Jan 1, 2014

By M. Saghaeian, R. Hejazi, V. Sheikhzadeha, A. H. Baladastian, A. Dehghani Ahmadabadi

This paper describes research done to remove apatite (phosphorus) from hematite ultrafine (70% finer than 25 micron) concentrate, recovered by electromagnetic separators at the FST Tailing Recovery Plant located in Chadormalu Iron Ore Complex through reverse froth flotation. As a result, iron and phosphorus content in magnetic concentrate (flotation feed) were 53.52% and 0.58%, respectively. Therefore, to increase the Fe content and decrease the P content of the sample, reverse flotation tests were applied. Chemical reagents used in this research consisted of sodium silicate as a depressant, sodium hydroxide and sodium carbonate as pH regulators, Alke & Dirol as fatty acid collectors and MIBC as frother. Process parameters including dosages of collectors, depressant and frother, preparation times of depressant and collectors, steps and time of frothing and pH range were selected. After doing flotation tests, in optimum condition, dosages of collectors were 1200 g/t, depressant 1200 g/t, pH in the range of 9.5 to 10, preparation time of collectors in the first step was eight minutes and at the other steps, four minutes; the number of frothing steps 4 and frothing time in each stage was three minutes. In this case, it was observed that the amount of phosphorus in the final concentrate was reduced to 0.05%, the Fe content increased from 53.52% to 61.66% and the Fe recovery achieved was 82.21%. Keywords: Iron ore, hematite ultrafine concentrate, iron and phosphorus content

Jan 1, 2020