Peanut Kernels Research Articles

Automation of the Oil Extraction Process Performed by Means of A Screw Press

Abstract The continuous development of the oil-manufacturing industries causes the necessity of improving extraction technologies. In this case, the specific interest is focused on the control systems of screw presses. Among a great variety of such machines, the small household presses are in significant demand among consumers. Various seeds and kernels require different technological conditions to be provided in order to maximize the qualitative and quantitative characteristics of the extracted oil. Therefore, the main objective of this research is developing and testing the control system allowing for automation of the oil extraction process. Particularly, the temperature parameters of the pressing chamber, extracted oil, and electric motor are to be monitored and limited. In addition, the consumer should be able to predefine the mass of the oil to be extracted. Considering the small household screw press LiangTai LTP200, the general algorithm (block diagram) of the control system operation is proposed and the corresponding experimental prototype is developed. The latter is based on the Arduino Mega microcontroller and is equipped with three temperature sensors, two coolers (fans), one heater, and one mass sensor. The proposed control system allows for continuous monitoring and limiting of the pressing chamber, oil, and electric motor temperatures, as well as the mass of the extracted oil. The experimental data show that the pressing chamber preheating process lasts for about 3 min (170…190 s) and its maximal temperature does not exceed 44°C. The temperature of the extracted oil does not rise over 61°C. The motor temperature changes within the range of 69...71°C. The oil extraction productivity is as follows: 1.2 kg/h (sunflower seeds), 1.06 kg/h (walnut kernels), 0.9 kg/h (almond kernels), and 0.78 kg/h (peanut kernels). The obtained results can used in further investigations focused on analyzing the influence of these parameters on the quantitative and qualitative characteristics of the extracted oil.

Deciphering Cadmium Accumulation in Peanut Kernels through Growth Stages and Source Organs: A Multi-Stable Isotope Labeling Study.

The mechanisms of cadmium (Cd) uptake and redistribution throughout the peanut lifecycle remain unclear. This study employed multi-isotope labeling techniques in hydroponic and soil-foliar systems, revealing that Cd uptake during podding (Cdp) constituted 73.7% of kernel Cd content, whereas contributions from the flowering (Cdf) and seedling (Cds) stages were 22.2 and 4.1%, respectively. Stem-stored Cd (Cdstem) contributes 53.2% to kernel Cd accumulation, while leaf-stored Cd (Cdleaf) contributes 46.8%. Prestored Cdf in shoots demonstrated the most efficient transport to pods, approximately twice that of Cds and Cdp. Cds and Cdf were predominantly stored in leaves (51.0%), while Cdp mainly in stems (46.3%), 2.8 times its presence in leaves (16.5%), indicating distinct root-stem-kernel translocation. In the transfer of shoot Cd from stems to pods, 29.3% of Cdleaf and 25.0% of Cdstem were exported. This study provides novel insights into Cd dynamics in peanuts, establishing a foundation for future Cd regulation strategies.

Synergistic effect of acetic acid and chitosan against Aspergillus flavus

The mycotoxin-producing fungi contamination of foodstuffs and agricultural commodities is a serious problem. In this study, the efficacy of acetic acid (AcA), chitosan (CS), and CS with extra AcA (CS/extra AcA) against Aspergillus flavus (A. flavus) in vitro and in vivo were investigated. Results showed that CS/extra AcA strongly inhibited the mycelial growth and aflatoxins production of A. flavus at lower concentrations than CS (MIC >16.0 mg/mL) or AcA (MIC: 0.31 %). Significant inhibition was achieved in the presence of 4.0/0.12 and 8.0/0.08 CS (mg/mL)/extra AcA (%). CS/extra AcA exhibited remarkable antifungal activities based on the results of spore germination inhibition, abnormalities of spore morphology, disruption of cell membrane, mitochondrial dysfunction, and induction of apoptosis of hyphae. Moreover, pathogenicity test in peanut kernels showed that 8.0/0.16 CS (mg/mL)/extra AcA (%) could effectively inhibit the fungal infection and aflatoxin B1 production. The efficacy of CS/extra AcA is possibly due to the synergy of the antifungal property of CS, and undissociated AcA. The findings referred that CS/extra AcA is safe, efficient, and economical, and it could be used as a promising way to control A. flavus contamination in agro-foods preservation.

Effect of dielectric barrier discharge high voltage atmospheric cold plasma on Aspergillus flavus inactivation and aflatoxin B1 degradation on inoculated raw peanuts

High voltage atmospheric cold plasma (HVACP) is an emerging non-thermal technology with short treatment time, low energy consumption, and no chemical residues on foods. Peanut samples inoculated with Aspergillus flavus spores and spiked with Aflatoxin B1 (AFB1) toxin were treated with HVACP at 90 kV for 2, 5, and 10 min, and post-treatment storage times (0, 4, and 24 h) using air with different relative humidities (RH, 5, 40, and 80 %), respectively. A treatment of 5 min resulted in a 2.20 log spores reduction of A. flavus spores on peanuts. A. flavus was almost completely inactivated (99.9 %) by HVACP treatment for 10 min with 80 % RH in the air and 24 h post-treatment storage. A 71.3 % AFB1 reduction was achieved with a treatment of 2 min and 80 % RH without post-treatment. The reduction of AFB1 toxin also significantly increased with increasing treatment time, higher RH and post-treatment storage (p < 0.05). HVACP is a promising technology to effectively inactivate A. flavus and reduce AFB1 on raw peanut kernels without adversely affected peanut quality. Industrial relevanceTo improve the food safety and quality, it is crucial to develop an effective microbial decontamination approach while having minimal impact on the organoleptic characteristics and nutritional value of treated foods. Peanuts are an excellent source of plant-based protein, but they are highly susceptible to contamination with Aspergillus spp. mold, which may lead food safety issues. Cold plasma as an emerging non-thermal technology with short treatment time, low energy consumption, and no chemical residue on the food proves to be a promising tool to effectively inactivate A. flavus and reduce AFB1 on raw peanut kernels without adversely affected peanut quality.

Salmonella Detection in Food Using a HEK-hTLR5 Reporter Cell-Based Sensor.

The development of a rapid, sensitive, specific method for detecting foodborne pathogens is paramount for supplying safe food to enhance public health safety. Despite the significant improvement in pathogen detection methods, key issues are still associated with rapid methods, such as distinguishing living cells from dead, the pathogenic potential or health risk of the analyte at the time of consumption, the detection limit, and the sample-to-result. Mammalian cell-based assays analyze pathogens' interaction with host cells and are responsive only to live pathogens or active toxins. In this study, a human embryonic kidney (HEK293) cell line expressing Toll-Like Receptor 5 (TLR-5) and chromogenic reporter system (HEK dual hTLR5) was used for the detection of viable Salmonella in a 96-well tissue culture plate. This cell line responds to low concentrations of TLR5 agonist flagellin. Stimulation of TLR5 ligand activates nuclear factor-kB (NF-κB)-linked alkaline phosphatase (AP-1) signaling cascade inducing the production of secreted embryonic alkaline phosphatase (SEAP). With the addition of a ρ-nitrophenyl phosphate as a substrate, a colored end product representing a positive signal is quantified. The assay's specificity was validated with the top 20 Salmonella enterica serovars and 19 non-Salmonella spp. The performance of the assay was also validated with spiked food samples. The total detection time (sample-to-result), including shortened pre-enrichment (4 h) and selective enrichment (4 h) steps with artificially inoculated outbreak-implicated food samples (chicken, peanut kernel, peanut butter, black pepper, mayonnaise, and peach), was 15 h when inoculated at 1-100 CFU/25 g sample. These results show the potential of HEK-DualTM hTLR5 cell-based functional biosensors for the rapid screening of Salmonella.

Enhanced detection of Aspergillus flavus in peanut kernels using a multi-scale attention transformer (MSAT): Advancements in food safety and contamination analysis

In this study, a multi-scale attention transformer (MSAT) was coupled with hyperspectral imaging for classifying peanut kernels contaminated with diverse Aspergillus flavus fungi. The results underscored that the MSAT significantly outperformed classic deep learning models, due to its sophisticated multi-scale attention mechanism which enhanced its classification capabilities. The multi-scale attention mechanism was utilized by employing several multi-head attention layers to focus on both fine-scale and broad-scale features. It also integrated a series of scale processing layers to capture features at different resolutions and incorporated a self-attention mechanism to integrate information across different levels. The MSAT model achieved outstanding performance in different classification tasks, particularly in distinguishing healthy peanut kernels from those contaminated with aflatoxigenic fungi, with test accuracy achieving 98.42±0.22%. However, it faced challenges in differentiating peanut kernels contaminated with aflatoxigenic fungi from those with non-aflatoxigenic contamination. Visualization of attention weights explicitly revealed that the MSAT model's multi-scale attention mechanism progressively refined its focus from broad spatial-spectral features to more specialized signatures. Overall, the MSAT model's advanced processing capabilities marked a notable advancement in the field of food quality safety, offering a robust and reliable tool for the rapid and accurate detection of Aspergillus flavus contaminations in food.

Impact of the Water Content in Peanut Kernels on the Generation of Benzeneacetaldehyde in Roasted Peanut Oils

Impact of the Water Content in Peanut Kernels on the Generation of Benzeneacetaldehyde in Roasted Peanut Oils

Utilizing plant-based biogenic volatile organic compounds (bVOCs) to detect aflatoxin in peanut plants, pods, and kernels

Mycotoxins and particularly aflatoxin are a concern for peanut growers, processors, and consumers. Aflatoxins are responsible for approximately 25 % of liver cancer cases worldwide, while also costing millions of dollars in lost revenue on an annual basis. Current detection techniques based on high pressure liquid chromatography (HPLC) are time, labor and cost intensive. Peanut product can be held multiple days before testing is complete, costing processors additional revenue loss. Over the past few years, The Georgia Tech Research Institute (GTRI) has been investigating the use of plant-based biogenic volatile organic compounds (bVOCs) for monitoring the status of peanut plants. Initially, GTRI utilized these bVOCs to monitor for heat/drought stress in peanut plants. They quickly saw very promising indications of the ability of bVOCs to monitor other parameters in these plants. More recently, the team has started to investigate the of use of bVOCs to monitor aflatoxin development in plants, pods, and kernels pre- and post-harvest. A field trial for detection of aflatoxin using bVOCs was conducted in August–September of 2020 where three test groups were prepared: plants treated with Aspergillus fungus; plants treated with Afla-Guard (biocontrol agent); plants not treated – acting as a control group. Plant-based bVOCs were collected from the plants before treatment, and once a week post treatment using Stir Bar Sorptive Extraction (SBSE) devices or Twisters®. Each Twister® was then analyzed via gas chromatography–mass spectrometry (GC/MS). Pods from tested plants were harvested and sent to GTRI where bVOCs were collected and analyzed using GC/MS. Several statistical analysis and machine learning techniques were applied to all the collected GC/MS data. It was found using only bVOCs, that Random Forest classification performed well for the analysis of the pod and kernel samples with an F1 score of 0.80. On the other hand, Linear Discriminate Analysis (LDA) was only able to correctly classify 50 % of plant-based samples solely on bVOCs alone, which may be due to training models developed using original labels assuming no cross contamination at the field level. These results indicate the potential for bVOC screening for aflatoxin as an important way to lower impacts to growers, shellers, and consumers.

Scope, Distribution, and Cause of the Peanut Kernel Shrivel (PKS) Syndrome: An Emerging Threat to Australia’s Peanut Industry

The cause of peanut kernel shrivel (PKS) syndrome, affecting peanut crops in Australia’s growing regions, is currently unknown. It is estimated that PKS is costing the peanut industry more than AUD 5 M p.a. and is a potential threat to the industry. Previous investigations have ruled out all abiotic factors and most biotic factors as the cause of PKS. This research aimed at investigating the scope, distribution, and cause of the PKS syndrome. The survey showed PKS symptoms to be present in peanut crops in all the growing regions surveyed. Based on our study of culturable microorganisms, there appears to be no clear-cut involvement of plant pathogenic bacteria and fungi; however, Fusarium spp. were revealed as the most prevalent fungi in affected plants. Moreover, the soil metagenomics study revealed Fusarium spp. as the most abundant fungal communities in the soil microbial profile, and they could contribute to the PKS syndrome. The consistent presence observed of the identified Fusarium oxysporum in PKS-affected samples could indicate a role for this pathogen in the syndrome, especially in conjunction with abiotic stressors. The pathogenicity testing of F. oxysporum resulted in very mild PKS symptoms. A separate report suggesting the involvement of phytoplasma in the PKS syndrome raises the possibility of an interplay of biotic factors in the development of this disease. Further investigation is warranted to determine the true cause or causes of this disease.

Integrated physiological, transcriptomic and metabolomic analyses reveal the mechanism of peanut kernel weight reduction under waterlogging stress.

Waterlogging stress (WS) hinders kernel development and directly reduces peanut yield; however, the mechanism of kernel filling in response to WS remains unknown. The waterlogging-sensitive variety Huayu 39 was subjected to WS for 3 days at 7 days after the gynophores touched the ground (DAG). We found that WS affected kernel filling at 14, 21, and 28 DAG. WS decreased the average filling rate and kernel dry weight, while transcriptome sequencing and widely targeted metabolomic analysis revealed that WS inhibited the gene expression in starch and sucrose metabolism, which reduced sucrose input and transformation ability. Additionally, genes related to ethylene and melatonin synthesis and the accumulation of tryptophan and methionine were upregulated in response to WS. WS upregulated the expression of the gene encoding tryptophan decarboxylase (AhTDC), and overexpression of AhTDC in Arabidopsis significantly reduced the seed length, width, and weight. Therefore, WS reduced the kernel-filling rate, leading to a reduction in the 100-kernel weight. This survey informs the development of measures that alleviate the negative impact of WS on peanut yield and quality and provides a basis for exploring high-yield and high-quality cultivation, molecular-assisted breeding, and waterlogging prevention in peanut farming.

Biochar boosted high oleic peanut production with enhanced root development and biological N fixation by diazotrophs in a sand-loamy Primisol

Peanut yield and quality face significant threats due to climate change and soil degradation. The potential of biochar technology to address this challenge remains unanswered, though biochar is acknowledged for its capacity to enhance the soil microbial community and plant nitrogen (N) supply. A field study was conducted in 2021 on oil peanuts grown in a sand-loamy Primisol that received organic amendments at 20 Mg ha−1. The treatments consisted of biochar amendments derived from poultry manure (PB), rice husk (RB), and maize residue (MB), as well as manure compost (OM) amendment, compared to no organic amendment (CK). In 2022, during the second year after amendment, samples of bulk topsoil, rooted soil, and plants were collected at the peanut harvest. The analysis included the assessment of soil quality, peanut growth traits, microbial community, nifH gene abundance, and biological N fixation (BNF) rate. Compared to the CK, the OM treatment led to an 8 % increase in peanut kernel yield, but had no effect on kernel quality in terms of oil production. Conversely, both PB and MB treatments increased kernel yield by 10 %, whereas RB treatment showed no change in yield. Moreover, all biochar amendments significantly improved oilseed quality by 10–25 %, notably increasing the proportion of oleic acid by up to 70 %. Similarly, while OM amendment slightly decreased root development, all biochar treatments significantly enhanced root development by over 80 %. Furthermore, nodule number, fresh weight per plant, and the nifH gene abundance in rooted soil remained unchanged under OM and PB treatments but was significantly enhanced under RB and MB treatments compared to CK. Notably, all biochar amendments, excluding OM, increased the BNF rate and N-acetyl-glucosaminidase activity. These changes were attributed to alterations in soil aggregation, moisture retention, and phosphorus availability, which were influenced by the diverse physical and chemical properties of biochars. Overall, maize residue biochar contributed synergistically to enhancing soil fertility, peanut yield, and quality while also promoting increased root development, a shift in the diazotrophic community and BNF.

Ecological and health risk assessments of heavy metals and their accumulation in a peanut-soil system

Heavy metals pollution is a notable threat to environment and human health. This study evaluated the potential ecological and health risks of heavy metals (Cu, Cr, Cd, Pb, Zn, Ni, and As) and their accumulation in a peanut-soil system based on 34 soil and peanut kernel paired samples across China. Soil As and Cd posed the greatest pollution risk with 47.1% and 17.6% of soil samples exceeding the risk screen levels, respectively, with 26.5% and 20.6% of the soil sites at relatively strong potential ecological risk level, respectively, and with the geo-accumulation levels at several soil sites in the uncontaminated to moderately contaminated categories. About 35.29% and 2.94% of soil sites were moderately and severely polluted based on Nemerow comprehensive pollution index, respectively, and a total of 32.4% of samples were at moderate ecological hazard level based on comprehensive potential ecological risk index values. The Cd, Cr, Ni, and Cu contents exceeded the standard in 11.76, 8.82, 11.76 and 5.88% of the peanut kernel samples, respectively. Soil metals posed more health risks to children than adults in the order As > Ni > Cr > Cu > Pb > Zn > Cd for non-carcinogenic health risks and Ni > Cr ≫ Cd > As > Pb for carcinogenic health risks. The soil As non-cancer risk index for children was greater than the permitted limits at 14 sites, and soil Ni and Cr posed the greatest carcinogenic risk to adults and children at many soil sites. The metals in peanut did not pose a non-carcinogenic risk according to standard. Peanut kernels had strong enrichment ability for Cd with an average bio-concentration factor (BCF) of 1.62. Soil metals contents and significant soil properties accounted for 35–74% of the variation in the BCF values of metals based on empirical prediction models.

Dual-aspect attention spatial-spectral transformer and hyperspectral imaging: A novel approach to detecting Aspergillus flavus contamination in peanut kernels

In this study, an innovative dual-aspect attention spatial-spectral transformer (DAASST) was introduced to advance postharvest quality control by the detection of Aspergillus flavus contamination and the accurate identification of contamination times in peanut kernels. The critical importance of maintaining postharvest quality and safety in nuts was recognized, with hyperspectral imaging technology being leveraged due to its great potential in non-destructive testing and quality assessment of nuts. At the heart of DAASST's innovation, an enhanced transformer architecture that incorporated an attention fusion mechanism was employed for the effective integration of the extracted features. This sophisticated integration not only improved the model’s performance but also was significantly surpassed by the capabilities of traditional machine learning methods in the context of postharvest biology and technology. Exceptional accuracy was demonstrated in testing, with 99.40% achieved in detecting Aspergillus flavus contamination and a remarkable 100% in distinguishing between different contamination times. Significant contributions to the field of postharvest biology and technology were made by merging cutting-edge feature extraction techniques, attention mechanisms, and transformer architecture to refine hyperspectral image analysis for postharvest quality control. The proven effectiveness of the DAASST in accurately detecting Aspergillus flavus and determining contamination times in peanut kernels highlighted its potential as a valuable tool for ensuring the safety and quality of postharvest nuts.

Does market quality benefit from internationalization? Evidence from Chinese commodity futures markets

Internationalization is the primary way to facilitate the high-quality development of Chinese commodity futures markets. Based on liquidity provision theory, we investigate the impacts of opening to foreign traders on the market quality of China’s 10 commodity futures using the synthetic control method. Specifically, we measure market quality based on activity, liquidity, and price efficiency using tick-by-tick data. We find that opening to foreign traders reduced (improved) the market quality of iron ore (purified terephthalic acid and rapeseed oil) futures significantly and had limited impacts on palm oil, soybean No. 1, soybean No. 2, soybean oil, soybean meal, rapeseed meal, and peanut kernel futures. The competition channel plays a dominant role in the influence mechanism, whereas the adverse selection channel does not play a significant role. We conclude that coke, ferrosilicon, stainless steel, and glass futures have the highest priority to be opened. Our findings have practical significance for implementing the internationalization of commodity futures in emerging countries.

The underlying reasons for the efficient extraction of peanut oil by aqueous ethanol combined with roasting conditioning pretreatment

To overcome the disadvantages of severe emulsification and difficulty in obtaining free oil during aqueous extraction of peanut oil, the effect of roasting assisted aqueous ethanol extraction on free oil recovery was investigated. When peanut kernels were roasted at 180 °C for 10 min, free oil recovery increased from 57% to 96%, and the acid and peroxide values of the peanut oil met the requirements of good quality. The degree of hydration swelling of proteins in the extract increased, and soluble solids were easier to aggregate, resulting in reduced emulsification and significantly higher free oil recovery. The roasting conditions selected were found to significantly promote protein hydrophilicity, aggregation and fusion of oil bodies, as well as cell rupture, which facilitated the release of free oil but with a lower degree of protein denaturation. This study may promote the practical application of aqueous extraction technology for peanut oil.

Unveiling the molecular regulatory mechanisms underlying sucrose accumulation and oil reduction in peanut kernels through genetic mapping and transcriptome analysis

Sucrose content is a key factor for the flavor of edible peanut, which determines the sweet taste of fresh peanut and also attribute to pleasant flavor of roasted peanut. To explore the genetic mechanism of the sucrose content in peanut, an F2 population was created by crossing the sweet cultivar Zhonghuatian 1 (ZHT1) with Nanyangbaipi (NYBP). A genomic region spanning 28.26 kb on chromosome A06 was identified for the sucrose content through genetic mapping, elucidating 47.5% phenotypic variance explained. As the sucrose content had a significantly negative correlation with the oil content, this region was also found to be related to the oil content explaining 37.2% of phenotype variation. In this region, Arahy.42CAD1 was characterized as the most likely candidate gene through a comprehensive analysis. The nuclear localization of Arahy.42CAD1 suggests its potential involvement in the regulation of gene expression for sucrose and oil contents in peanut. Transcriptome analysis of the developing seeds in both parents revealed that genes involved in glycolysis and triacylglycerol biosynthesis pathways were not significantly down-regulated in ZHT1, indicating that the sucrose accumulation was not attributed to the suppression of triacylglycerol biosynthesis. Based on the WGCNA analysis, Arahy.42CAD1 was co-expressed with the genes involved in vesicle transport and oil body assembly, suggesting that the sucrose accumulation may be caused by disruptions in TAG transportation or storage mechanisms. These findings offer new insights into the molecular mechanisms governing sucrose accumulation in peanut, and also provide a potential gene target for enhancing peanut flavor.

Effective removal of aflatoxin B1 using modified attapulgite loaded with bacillomycin D from stored peanut kernels

Peanut kernels could be easily contaminated by Aspergillus flavus and its mycotoxins. This not only reduced their nutritional and economic value, but also posed a serious threat to human health. In this study, acid-modified attapulgite loaded with bacillomycin D (H-ATP-BD) was used for aflatoxin B1 (AFB1) removal in peanut kernels contaminated with A. flavus spores. During storage, H-ATP-BD treatment inhibited mildew of peanut kernels. At 12% moisture content, the H-ATP-BD treatment reduced mildew from 52.3% to 18.2%. Furthermore, the H-ATP-BD could reduce the oxidative decomposition of fatty acids in oilseed products such as peanut kernels, and lower the fatty acid value, peroxide value, and malondialdehyde content during storage, thereby slowing down the decline of peanut kernels quality. H-ATP-BD have been shown to be effective in prolonging the storage life of peanut kernels by both inhibiting mold growth and removing pre-existing mycotoxins. The addition of H-ATP-BD significantly reduced AFB1 content ranging from 61.1% to 85.2%. It was superior to BD as well as acid-modified attapulgite (H-ATP) used alone. Thus, these results suggested that the utilization of H-ATP-BD provided a novel strategy to control mold contamination and detoxification in food products to ensure food safety.

Nondestructive and Rapid Screening of Aflatoxin-Contaminated Single Peanut Kernels Using Field-Portable Spectroscopy Instruments (FT-IR and Raman).

A nondestructive and rapid classification approach was developed for identifying aflatoxin-contaminated single peanut kernels using field-portable vibrational spectroscopy instruments (FT-IR and Raman). Single peanut kernels were either spiked with an aflatoxin solution (30 ppb-400 ppb) or hexane (control), and their spectra were collected via Raman and FT-IR. An uHPLC-MS/MS approach was used to verify the spiking accuracy via determining actual aflatoxin content on the surface of randomly selected peanut samples. Supervised classification using soft independent modeling of class analogies (SIMCA) showed better discrimination between aflatoxin-contaminated (30 ppb-400 ppb) and control peanuts with FT-IR compared with Raman, predicting the external validation samples with 100% accuracy. The accuracy, sensitivity, and specificity of SIMCA models generated with the portable FT-IR device outperformed the methods in other destructive studies reported in the literature, using a variety of vibrational spectroscopy benchtop systems. The discriminating power analysis showed that the bands corresponded to the C=C stretching vibrations of the ring structures of aflatoxins were most significant in explaining the variance in the model, which were also reported for Aspergillus-infected brown rice samples. Field-deployable vibrational spectroscopy devices can enable in situ identification of aflatoxin-contaminated peanuts to assure regulatory compliance as well as cost savings in the production of peanut products.

High-accuracy classification and origin traceability of peanut kernels based on near-infrared (NIR) spectroscopy using Adaboost - Maximum uncertainty linear discriminant analysis

Peanut kernels, known for their high nutritional value and palatability, are classified as nut food. In this study, peanut kernel samples from six distinct cities in Shandong Province, China, were examined to categorize and trace their origins. Near-infrared (NIR) spectra of samples were captured using a portable NIR-M-R2 spectrometer. After the application of Savitzky-Golay (SG) filtering, the classification was attempted using principal component analysis (PCA) plus linear discrimination analysis (LDA). Additionally, maximum uncertainty linear discriminant analysis (MLDA) was applied for comparison. A specific number of eigenvectors could respectively maximize the classification accuracies, 81.48% for PCA + LDA and 76.54% for MLDA. In order to further improve the classification accuracies, Adaboost-MLDA was proposed to develop a stronger classifier. This method, after 18 iterations, achieved remarkable effects, achieving a high accuracy of 95.06%. In a similar vein, the enhancement with preprocessing techniques multiplicative scatter correction (MSC) + SG and standard normal variate (SNV) + SG raised accuracies to 98.77% and 97.53%, respectively. The results of classifying first-order and second-order derivative spectra using Adaboost-MLDA were also described, achieving accuracies near 100%. The experiment demonstrates that integrating Adaboost with NIR spectroscopy offers a highly accurate method for peanut kernel classification, promising for practical applications in food quality control.

The Role of Heating Treatments on Bioactive Compounds, Fatty Acid Compositions, Phenolic Compounds and Mineral Contents of Peanut Kernels.

In this study, the role of boiling and roasting on chemical properties, fatty acid compositions, polyphenols and mineral contents of peanut kernels provided from Mersin (Silifke) province in Turkey was investigated. The oil yields of peanut kernels treated were specified between 48.92% (boiled) and 52.93% (oven roasting). While total phenolic quantities of raw, boiled and roasted-peanut kernels were assessed between 71.98% (boiled) and 178.81 mgGAE/100 g (raw(control)), total flavonoid quantities of treatedpeanut kernels were found to be between 120.36 (boiled) and 530.36 mgQE/100 g (control). The antioxidant activities of peanut kernels ranged from 2.66 (microwave roasting) to 3.90 mmolTE/kg (control). The phenolic constituents of peanut kernels are sensitivities to heat treatment. The maximum reduction in the phenolic compounds of peanut kernels was determined in the peanut kernels roasted in the microwave and oven roasting systems, and followed by the boiled process in decreasing order. Also, while oleic acid quantities of raw, boiled and roasted-peanut kernel oils are determined between 54.06% (boiled) and 57.22% (microwave roasting), the linoleic acid quantities of the oils of peanut kernels treated were specified between 25.18% (microwave roasting) and 27.33% (boiled). The composition of the oil of the peanut kernels roasted in microwave has highly increased (except palmitic and linoleic acids) according to the control. The macro elements found at the highest amounts in raw, boiled and roasted-peanut kernels were P, K, Ca, Mg, S and Na. The most available as micro element has been Fe and Zn. Heat treatments such as roasting and boiling not only change the visible rawness of peanuts, but they can also subsequently cause chemical changes in peanut kernels.