Search Results (432)

Dispersive solid-phase extraction (dSPE) is a crucial step for multiresidue analysis used to remove matrix components from extracts. This purification prevents contamination of instrumental equipment and improves method selectivity, sensitivity, and reproducibility. Therefore, a clean-up step is recommended, but an over-purified extract can lead to analyte loss due to adsorption to the sorbent. This study provides a systematic comparison of the advantages and disadvantages of the well-established dSPE sorbents PSA, GCB, and C18 and the novel dSPE sorbents chitin, chitosan, multi-walled carbon nanotube (MWCNT), and Z-Sep^® (zirconium-based sorbent). They were tested regarding their clean-up capacity by visual inspection, UV, and GC-MS measurements. The recovery rates of 98 analytes, including pesticides, active pharmaceutical ingredients, and emerging environmental pollutants with a broad range of physicochemical properties, were determined by GC-MS/MS. Experiments were performed with five different matrices, commonly used in food analysis (spinach, orange, avocado, salmon, and bovine liver). Overall, Z-Sep^® was the best sorbent regarding clean-up capacity, reducing matrix components to the greatest extent with a median of 50% in UV and GC-MS measurements, while MWCNTs had the largest impact on analyte recovery, with 14 analytes showing recoveries below 70%. PSA showed the best performance overall. Full article

In the absence of comparative real estate data in the market segment of the property to be estimated, the appraiser may resort to income capitalization to estimate the market value. Often, however, the choice of which rate to apply is affected by subjective and arbitrary assessments. The estimation result can therefore be inaccurate and rather unclear. However, the Remote Segments Approach (RSA), through appropriate adjustments on the original values, prices, and incomes detected in the remote segments, makes it possible to arrive at an appraisal result consistent with estimative logic and real estate valuation standards. The proposed application illustrates the estimation of the market value of a specialized fruit orchard of avocado, which is to be considered new in relation to other fruit species already present in the reference area. The adjustments required by the RSA are solved with the General Appraisal System (GAS), defining the difference matrix based on relevant characters common to all segments considered. The application is carried out by comparing the segment in which the orchard being estimated falls (subject) with other remote market segments in which prices and incomes constituted by other tree crops are collected. The market value of the subject is derived by making adjustments to the prices and incomes observed in the remote segments of comparison with a comparison function constructed through relevant characters common to the segments considered. The comparison function makes it possible to arrive at the determination of the capitalization rate to be used in estimating the value of the fruit orchard by income approach. While it is based on the comparison of segments, the approach followed allows for a value judgment consistent with the estimation comparison and capable of providing a solution less conditioned by the appraiser’s expertise in the presence of particularly pronounced limiting conditions. Full article

In recent years, avocados have gained worldwide popularity as a nutritive food. This trend is causing a rise in the production of this fruit, which is accompanied by several problems associated with monocultural practices. Despite massive economic gains, limited molecular and structural information has been generated about avocado ripening. In fact, limited studies have attempted to unravel the proteome complexity dynamics of avocado fruit. We therefore conducted a comparative proteomics study on avocado peel and pulp during the postharvest shelf life using tandem mass tag synchronous precursor selection triple-stage mass spectrometry. We identified 3161 and 1128 proteins in the peel and pulp, respectively. Peels exhibited major over-accumulation of proteins associated with water deprivation and oxidative stress, along with abscisic acid biosynthesis. Ethylene, jasmonic acid, phenylpropanoid, and flavonoid biosynthesis pathways were activated. Structurally, we observed the accumulation of lignin and a reduction in cuticular thickness, which coincides with the reduction in the levels of long-chain acyl-coenzyme A synthetase and a marginal increase in 10,16-dihydroxyhexadecanoic acid. Our study sheds light on the association of proteome modulation with the structural features of Hass avocado. Its detailed characterization will provide an alternative for better preservation during the postharvest period. Full article

This study developed, validated, and tested a simple method for tocopherol analysis on five different food matrices (sunflower oil, mackerel fillets, almonds, spinach, and avocado pulp). Tocopherol extraction from foods was carried out by the Folch method and with n-hexane, and the identification and quantification of tocopherol isoforms (α, β, γ, and δ) was performed using normal-phase liquid chromatography with ultraviolet–visible detection (NP-HPLC–UV–Vis). The normal-phase column fully separated the four tocopherol isoforms in less than ten minutes. Linearity was shown to be excellent for the four isoforms in the assayed range (10–375 ppm, R² > 0.99). Furthermore, the limits of detection (LOD) and quantification (LOQ) ranged from 0.32 to 0.63 ppm, and from 1.08 to 2.11 ppm, respectively. The intra-day and inter-day precision were assessed at different concentrations (10, 100, and 250 ppm) for each tocopherol isoform and they were within the range of acceptable values. Recovery rates were above 80% in most cases for all of the assayed food matrices, regardless of the extraction method (Folch solvents or n-hexane). α-Tocopherol was the main isoform found in all tested foods, and sunflower oil was the sample with the highest content, followed by almond, avocado pulp, mackerel fillet, and spinach. This method provides a convenient alternative for obtaining a complete profile of the four tocopherol isoforms in a variety of food matrices and for tracking the potential degradation kinetics of fortified foods during their processing and storage. Full article

Abiotic stress factors can be detected using visible and near-infrared spectral signatures. Previous work demonstrated the potential of this technology in crop monitoring, although a large majority used vegetation indices, which did not consider the complete spectral information. This work explored the capabilities of spectral information for abiotic stress detection using supervised machine learning techniques such as support vector machine (SVM), random forest (RF), and neural network (NN). This study used avocados grown under various water treatments, maize submitted to nitrogen deficiency, and common beans under phosphorous restriction. The spectral characterization of the crops subjected to abiotic stress was studied on the visible to near-infrared (450 to 900 nm) spectrum, identifying discriminative bands and spectral ranges. Then, the advantages of using an integrated approach based on machine learning to detect abiotic stress in crops were demonstrated. Instead of relying on vegetation indices, the proposed approach used several spectral features obtained by analyzing the discriminative signature shape, applying a spectral subset band selection algorithm based on similarity, and using the minimum redundancy maximum relevance (MRMR), F-test and chi-square test ranks for feature selection. The results showed that supervised classifiers applied to the spectral features outperform the accuracies obtained from vegetation indices. The best common bean results were obtained using SVM with accuracies up to 91%; for maize and avocado, NN obtained 90% and 82%, respectively. It is noted that detection accuracy depends on various factors, such as crop type, genotype, and level of stress. Full article

The present paper tests the use of an agricultural futures minimum tracking error portfolio to replicate the price of the Mexican Hass avocado (a non-commodity). The motivation is that this portfolio could be used to balance the basis risk that the avocado price hedge issuer could face. By performing a backtest of a theoretical avocado producer from January 2000 to September 2023, the results show that the avocado producer could hedge the avocado price by 94%, with the hedge offered by a theoretical financial or government institution. Also, this issuer could balance the risk of such a hedge by buying a coffee–sugar futures portfolio. The cointegrated or long-term relationship shows that using such a futures portfolio is useful for Mexican Hass avocado price hedging. This paper stands as one of the first in testing futures portfolios to offer a synthetic hedge of non-commodities through a commodities’ futures portfolio. Full article

Plants generate a range of physiological and molecular responses to sustain their growth and development when suffering heat stress. Avocado is a type of tropical fruit tree with high economic value. Most avocado cultivars delete, wither, or even die when exposed to heat stress for a long time, which seriously restricts the introduction and cultivation of avocados. In this study, samples of a heat-intolerant variety (‘Hass’) were treated under heat stress, and the transcriptomics and metabolomics were analyzed, with the expectation of providing information on the variety improvement and domestication of avocados. The differentially expressed genes identified using transcriptome analysis mainly involved metabolic pathways such as plant hormone signal transduction, plant–pathogen interaction, and protein processing in the endoplasmic reticulum. Combined transcriptome and metabolome analysis indicated that the down-regulation of Hass.g03.10206 and Hass.g03.10205 in heat shock-like proteins may result in the reduced Trehalose and Sinapoyl aldehyde content. Metabolomics analysis results indicated that the decrease in Trehalose and Sinapoyl aldehyde content may be an important factor for heat intolerance. These results provide important clues for understanding the physiological mechanisms of adaptation to heat stress in avocados. Full article

The utilization of agroindustrial residues, such as avocado peel, as a source of bioactive compounds with antioxidant properties has garnered significant attention. In this study, we investigated the antioxidant potential using the DPPH (2,2-diphenyl-1-picrylhydrazyl) and ORAC (oxygen radical absorbance capacity) methods, along with the antimicrobial activity of phenolic compounds extracted from Hass avocado peel. These soluble polyphenols were quantified and identified using high-performance liquid chromatography (HPLC). The research focused on their effects against three fungal pathogens, Verticillium theobromae, Colletotrichum musae, and Aspergillus niger, which significantly impact banana crops, an essential agricultural commodity in Ecuador. The results have revealed that the application of 80% ethanol as an organic solvent led to increased soluble polyphenol content compared to 96% ethanol. Extraction time significantly influenced the phenolic content, with the highest values obtained at 90 min. Interestingly, despite substantial mycelial growth observed across all extract concentrations, the antifungal effect varied among the pathogens. Specifically, V. theobromae exhibited the highest sensitivity, while C. musae and A. niger were less affected. These results underscore the importance of considering both antioxidant and antimicrobial properties when evaluating natural extracts for potential applications in plant disease management. Full article

The avocado cv. Hass requires a suitable rootstock for optimal development under water stress. This study evaluated the performance of two avocado rootstocks (ANRR88 and ANGI52) grafted onto cv. Hass under four water stress conditions, 50% and 25% deficit, and 50% and 25% excess during the nursery stage. Plant height, leaf area (LA), dry matter (DM), and Carbon (OC) content in the roots, stems, and leaves were measured. Root traits were evaluated using digital imaging, and three vegetation indices (NDVI, CI_RE, and MTCI) were used to quantify stress. The results showed that genotype significantly influenced the response to water stress. ANRR88 exhibited adaptation to moderate to high water deficits. ANGI52 adapted better to both water deficit and excess, and showed greater root exploration. LA and DM reductions of up to 60% were observed in ANRR88, suggesting a higher sensitivity to extreme changes in water availability. More than 90% of the total OC accumulation was observed in the stem and roots. The NDVI and the MTCI quantified the presence and levels of stress applied, and the 720 nm band provided high precision and speed for detecting stress. These insights are crucial for selecting rootstocks that ensure optimal performance under varying water availability, enhancing productivity and sustainability. Full article

The health-promoting properties of vitamin K stimulate the growing interest in this compound, which translates into the development of new analytical methodologies for its determination. New, more efficient methods of its isolation are sought, paying increasingly more attention to the methods within currently available extraction techniques that, owing to the optimization of the process, not only increase the extraction efficiency but are also economical and environmentally friendly. This article proposes a procedure for the extraction and analysis of one of the vitamin K vitamers, i.e., vitamin K1, using PLE and LC-MS/MS. It has been shown that the PLE technique can be optimized with a mathematical model—accelerating and reducing the costs of the extraction process—which, together with process automation, bodes well for industrial applications. The optimized process was used to extract vitamin K1 from various vegetables, showing very different contents of the test compound ranging from 1.22 to 114.30 µg/g dry weight for avocado and spinach, respectively. In addition, by showing the effect of water within the material subjected to extraction on the variable yield of vitamin K1, attention was drawn to the need to standardize the analytical methods used in assessing the quality of food products. Full article

Crop residue decomposition is fundamental for ecosystems, influencing carbon cycling, organic matter accumulation, and promoting plant development through nutrient release. Therefore, this study aimed to ascertain the rate of decomposition of four commonly cultivated crops (alfalfa, maize, avocado, and eucalyptus) along the northern coast of Lima (Huaral) and in the Ancash Mountain range (Jangas) areas. Decomposition rates were assessed using mass loss from decomposition bags measuring 15 × 10 cm, filled with 10–15 g of material tailored to each species, and buried at a depth of approximately 5 cm. Sampling occurred every three months over a year, totaling four sampling events with three replicates each, resulting in ninety-six experimental units. The findings demonstrate that the decomposition rates and the release of nutrients were markedly greater in Huaral for maize and avocado. In contrast, these rates were notably elevated in Jangas for alfalfa and eucalyptus. The leaf litter of avocado and eucalyptus (tree) had periods of accumulation and release of heavy metals such as Cd. The initial C/N ratio was one of the main factors related to the nutrient decomposition rate; in contrast, there were no significant relationships with soil properties at the study sites. Full article

Carbohydrate levels are important regulators of the growth and yield of tree crops. Current methods for measuring foliar carbohydrate concentrations are time consuming and laborious, but rapid imaging technologies have emerged with the potential to improve the effectiveness of tree nutrient management. Carbohydrate concentrations were predicted using hyperspectral imaging (400–1000 nm) of leaves of the evergreen tree crops, avocado, and macadamia. Models were developed using partial least squares regression (PLSR) and artificial neural network (ANN) algorithms to predict carbohydrate concentrations. PLSR models had R² values of 0.51, 0.82, 0.86, and 0.85, and ANN models had R² values of 0.83, 0.83, 0.78, and 0.86, in predicting starch, sucrose, glucose, and fructose concentrations, respectively, in avocado leaves. PLSR models had R² values of 0.60, 0.64, 0.91, and 0.95, and ANN models had R² values of 0.67, 0.82, 0.98, and 0.98, in predicting the same concentrations, respectively, in macadamia leaves. ANN only outperformed PLSR when predicting starch concentrations in avocado leaves and sucrose concentrations in macadamia leaves. Performance differences were possibly associated with nonlinear relationships between carbohydrate concentrations and reflectance values. This study demonstrates that PLSR and ANN models perform well in predicting carbohydrate concentrations in evergreen tree-crop leaves. Full article

Avocado seed contains 64% of the phenolic compounds of the whole fruit. This makes avocado seed a potential candidate for the development of treatments for different illnesses, including obesity (the major risk factor for metabolic disorders). The aim of this study was to investigate the effects of avocado seed powder on high-fat diet-induced obesity in rats. Sprague Dawley rats (16 rats) were fed a high-fat diet for 10 weeks. After 10 weeks, the rats were assigned into two groups of eight animals each and were fed either a high-fat diet (HFD; control group) or a high-fat diet containing avocado seed powder (HFD-A; treatment group) for 6 weeks. Animals were weighed weekly, and weekly weight gain was determined. Animals in the treatment (avocado seed) group showed significantly lower body weight gain (7.8 ± 9.63 g) than animals in the control group (33.9 ± 10.84 g) at the end of this study. The treatment group presented with lower triglycerides than the control, with LDL and HDL comparable to the control group. Avocado seed powder showed potential to reduce obesity in rats fed a high-fat diet. Avocado seed can therefore be investigated further as a potential anti-obesity nutraceutical. Full article

Avocado (Persea americana Mill.) cultivation has spread to many countries from the tropics to the Mediterranean region, where avocado crops commonly face water shortages and diseases, such as white root rot (WRR) caused by Rosellinia necatrix. The use of drought- and WRR-tolerant rootstocks represents a potential solution to these constraints. In this research, water relations and the morpho-physiological response of avocado ‘Hass’ grafted on two selections of R. necatrix-tolerant rootstocks (BG48 and BG181) were evaluated under well-watered (WW) and at two soil-water-availability conditions (WS, ~50% and ~25% field capacity). Under WW, scion water use was markedly affected by the rootstock, with BG48 displaying a water-spender behavior, showing higher water consumption (~20%), plant transpiration rates (~30%; E_plant) and leaf photosynthetic rates (~30%; A_N) than BG181, which exhibited a water-saving strategy based upon a trade-off between leaf-biomass allocation and tight stomatal control of transpiration. This strategy did not reduce biomass, with BG181 plants being more water use efficient. Under WS, BG48 and BG181 exhibited a drought-avoidance behavior based on distinct underlying mechanisms, but increases in leaf mass area (~18–12%; LMA), and decreases in E_plant (~50–65%), plant hydraulic conductance (~44–86%; K_h) and leaf water potential (~48–73%; Ψ_w) were observed in both rootstocks, which aligned with water stress severity. After rewatering, photosynthetic rates fully recovered, suggesting some ability of these rootstocks to withstand water stress, enabling the ‘Hass’ variety to adapt to region-specific constraints. Full article

This research improves the strength of plastic using avocado seed starch and PLA. The effect of blending avocado seed starch and PLA was optimized using the RSM approach by using two variables: water absorption and biodegradability. Mixing them using RSM gave the best result: 1.8 g of starch and 3 g of PLA. Degradable plastic has a tensile strength of 10.1 MPa, elongation at a break of 85.8%, and a Young’s modulus of 190 MPa. Infrared spectroscopy showed that the plastic had a -OH bond at 3273.20 cm⁻¹, 3502.73 cm⁻¹, and 3647.39 cm⁻¹, a CH₂ bond at 2953.52 cm⁻¹, 2945.30 cm⁻¹, and 2902.87 cm⁻¹, a C=C bond at 1631.78 cm⁻¹, and a C-O bond at 1741.72 cm⁻¹. The plastic decomposed in the soil. It was organic and hydrophilic. Thermal tests demonstrated that the plastic can withstand heat well, losing weight at 356.86 °C to 413.64 °C, forming crystals and plastic melts at 159.10 °C—the same as PLA. In the melt flow test, the sample melted before measurement, and was therefore not measurable—process conditions affected it. A water absorption of 5.763% and biodegradation rate of 37.988% were found when the samples were decomposed for 12 days. The starch and PLA fused in the morphology analysis to form a smooth surface. The RSM value was close to 1. The RSM gave the best process parameters. Full article