1. Introduction
The growth dynamics of Hass avocado consumption around the world have been maintained since 2016. The USA is the main avocado-importing market, with a per-capita avocado consumption between 4 and 7 kg, followed by Canada, EU27 West, and EU27+UK [
1]. The Asian market is emerging but is currently in the last place, and consumption in Asian countries is expected to increase with campaigns promoting its use in Mexican food, new preparation methods, and the dissemination of its health effects. In the harvest season of 2020-21, Latin America was by far the largest exporter of avocado (82%), with México, Perú, Chile, and Colombia being the countries with the highest export volumes globally. This tendency is due to the desire of consumers to eat healthfully while experiencing new and exotic flavors.
The nutrient management strategies and agroecological characterization of orchards are essential for understanding the behavior of nutrients in plants and for establishing whether each structure has the optimal levels to form quality fruits and increase productivity. It is also necessary to study the elimination and accumulation patterns of nutrients in different agroecological zones if management programs are to be established in avocado orchards to optimize the yield, quality, and efficiency of nutrients in avocado crops [
2].
Previously published works have found that the yield and fruit size of avocado could improve with appropriate nutrient management [
3,
4]. However, there is a lack of available knowledge to balance increasing production without affecting the internal quality and ripening pattern of Hass avocado in the target markets. Production is crucial for crop profitability, but providing markets with high-quality fruit is essential for ensuring the competitiveness of the value chain.
Despite its commercial popularity, the marketing of ‘Hass’ avocado is constrained by several postharvest disorders. Vast postharvest losses are incurred when fruit are rejected for not meeting consumers’ expectations regarding fruit-quality standards. The main challenges faced in this production chain are ripening heterogeneity, internal disorders (both physiological and pathological), and guaranteed sensory quality (nutty, creamy, buttery, flavor, and texture factors). Preharvest factors such as the climate, soil, and agronomic management strategy, among other factors, have also been associated with these problems.
Hofman was among the pioneer researchers who studied the relationship between the mineral flesh composition and internal avocado disorders, focusing on Ca in reducing internal damage due to the role of this element in the cell wall and membrane function [
5]. Subsequently, works were performed to optimize the fruit quality [
6] and the robustness of the avocado supply chain through mineral nutrition mechanisms [
7]. These works took a univariate approach to the quality problem: each study considered one mineral vs. an internal disorder.
Heterogeneity in ripening has been focused on as a main logistical factor [
8] but has not been associated with an increase in internal problems when avocado fruits require longer durations to ripen. Although fruit can ripen without internal disorders, such fruit does not always have a high sensory quality [
9].
Studies performed in the sensory area have implemented acceptance tests mainly with a focus on postharvest or breeding [
10]. Other studies have proposed the content of fatty acids as a marker of origin [
11]. However, metabolism during fruit growth limits the application of such methods to countries with highly contrasting production conditions, such as certain regions in Chile, Mexico and Colombia. In addition, few works have sought to determine the relationships between fatty-acid profiles and the sensory quality of avocado fruit.
One aspect of great importance is the lack of multivariate studies addressing avocado quality not only from the aspect of heterogeneity but also from the perspective of the internal and sensory quality to guarantee consistency among the different destination markets of the fruit. Producing countries must include such variables in their production plans to carry out adequate agronomic management programs that guarantee the productivity (ton/Ha) of the crop to achieve economic feasibility without negatively affecting the integral quality of the fruit.
Currently, the harvest indices used, including the dry matter (DM) and oil content (OC) indices, do not allow fruits of high or low integral postharvest quality to be distinguished. Despite past efforts to develop nondestructive techniques, existing methods follow the univariate approach and are often restricted by the high variabilities in the measurement indicators. In a univariate approach, it is not possible to identify orchards, areas and countries with differentiated fruit qualities and thus determine how to manage such regions according to market demands. Therefore, the aim of this work was to develop a methodology for evaluating the integral quality of Hass avocados and to determine predictive quality markers to manage avocado fruit productions.
4. Discussion
As a common characteristic in avocado-producing areas in Colombia, a bimodal rainfall distribution pattern is presented [
23,
24,
25,
26,
27], as was registered in the studied avocado-producing area of Cauca. In this region, the high rainy season registered from January to May supplies the necessary water for nutrient mobility during the main flowering period. However, the intermediate flowering matches the low rainy season recorded from June to September. The flowering phase and initial fruit growth are highly demanding in terms of water and nutrients, and stress factors resulting from these two resources can increase the abscission of flowers and set fruits and can affect fruit growth [
28,
29,
30,
31,
32,
33]. Herein, in the experimental orchards in Cauca, the nutrient management program based on BIK supplied nutrients monthly, but the low water availability in the low rainy seasons potentially limited the transport of these nutrients to the plants during critical periods of high demand within the intermediate flowering period.
The soils in Cauca orchards showed a low capacity to exchange nutrients such as calcium, magnesium, sodium, and potassium. Previous reports showed a relationship between the nutritional condition of avocado trees and the availability of elements in the soil [
34], and some characteristics, such as acidic pH values, low levels of organic matter and high to very high levels of Cu, Fe, K, Ca, B and Zn, lead to deficit concentrations of nutrients in the leaves [
35]. BIK is a widely used tool for diagnosing the nutrimental status of Hass avocado trees [
35,
36].
In the methodology adopted herein, we considered an optimum standard value corresponding to each mineral nutrient in trees with yields exceeding 85 kg per tree and obtain the standard deviation for each nutrient in this population of trees. Using this tool to orientate nutrient management in the orchards of the Cauca region, yield increases of 55% and 26% in N and R orchards, respectively, were recorded in the harvest from the main flowering period. Additionally, improvements in fruit weight were recorded. The results shown herein are in accordance with the reports of Salazar-García and Lazcano-Ferrat, who oriented nutrient management based on the BIK methodology and increased fruit calibers with sizes greater than 170 g by 72% of the orchard yield, using specific fertilization with doses calculated for each nutrient throughout the growth cycle of the Hass avocado [
4].
Ripening heterogeneity has been reported as a severe logistical problem for marketers and results in fruits of inconsistent quality being delivery to consumers. This phenomenon is the result of the complex avocado fruit physiology and preharvest and postharvest factors [
8]. Rapid softening during ripening has been associated with C7 sugars, organic acids, and the lauric acid, stearic acid, and oleic acid contents.
Therefore, avocado-producing countries with high variability face challenges due to the primary and secondary metabolites of Hass avocados produced during fruit development being affected by the climate, harvest practices, rootstock, etc. [
8,
37]. Moreover, the preharvest factors and harvest indices are variable in Colombian conditions [
38]. In practice, the harvest begins in low-elevation regions at a DM value close to 23%. Our results agree with those of Fuentealba et al.: at low DM values, more ripening heterogeneity occurs [
39].
This is because the biological age of the fruit does not guarantee the quantity of fatty acids or other metabolites that soften flesh. Therefore, in Cauca orchards, growers must increase their development time to ensure adequate Hass avocado ripening.
The flesh mineral content has an effect on delaying the firmness of mesocarp softness because some elements are present and associated with the cell wall structure. Previously, nutrition has been reported to play an important role in postharvest Hass avocado quality. The effect on internal quality of some minerals has been discussed separately, as briefly described below. High levels of calcium in avocado fruits have been associated with a delay in ripening due to the effects on respiration, the impedance of the ethylene peak, greater firmness after storage and reduction in internal defects (stem end rot, body rot, vascular browning flesh discoloration, etc.) [
40]. An excess of nitrogen fertilization induces the activation of cytokinins that inhibit the production of ethylene and ABA [
41], making fruit more vulnerable to fungal pathogen attack [
42] and more susceptible to postharvest rot and vascular browning.
Similar to cell wall-associated calcium, boron differences might be another factor contributing to the observed ripening heterogeneity because 95% of the flesh B content is present in the cell wall [
8] and acts as a bridge between the cell wall and membrane [
8]. In contrast, B-deficient tissues have greater PPO activity and accumulate more phenolic compounds, the substrates for PPO-mediated browning reactions. Increasing the K supply beyond the minimum required value may lead to K-induced deficiencies of Ca and Mg, which could cause increased diffuse discoloration and body rot severity. Attention has been given to the balance between Mg, Ca and K cations in the fruit, as this balance seems to be more strongly associated with avocado fruit quality than the Mg content alone [
7].
According to Rooyen and Bower, copper is known to activate a group of oxidizing enzymes, such as polyphenol oxidase, monophenol oxidase, laccase and systems of oxidizing ascorbic acid [
38,
43]. Copper acts as a catalyst for the enzymatic systems that lead to enzymatic browning and is thought to be interrelated with zinc in various oxidation‒reduction reactions. Zinc is often coordinated with copper in the various oxidation‒reduction reactions that lead to browning. For the other minerals, there is a lack of knowledge of their roles in affecting the internal quality of Hass avocado fruits.
The approaches of past studies aimed to find a simple relationship (linear or nonlinear) between mineral contents and internal disorders. However, our results show that no one mineral plays the main role in affecting the internal quality of Hass avocado fruits, and the associated variabilities could be well-represented in a multivariate approach. PCA and PLS-DA were very useful because the confidence of the ellipse of the high-quality group (EB) allowed the identification of multiple vectors (variables) that cause heterogeneity, internal quality and sensory profile differences related to the flesh composition.
After the internal disorders, the other quality challenge of Hass avocado origins is obtaining a sensory quality that is satisfactory to consumer expectations. Therefore, a high sensory quality could serve as a competitiveness strategy to improve the success of certain avocado origins in the international market, especially in emerging avocado markets. Studies have found that the harvest season has an effect on the sensory quality of avocado fruits.
Arpaia et al. reported that likeability increased with an advancing harvest date (DM content), and their research was performed with preference sensory tests [
44]. Rodríguez et al. employed a sensory profile test and showed that the discriminant descriptors related to unmature fruit were green, bitter, acid, spicy taste, and sensations, whereas flux texture, oily taste, oily texture, and sweet taste were descriptors found in fruits at high DM contents [
9].
The results of this work confirmed that harvest practices had an important impact on the Hass avocado fruit quality profile. The main issue under field conditions is that farmers do not have nondestructive equipment or lack knowledge regarding what markers to measure to sort fruit and guide the harvest decisions to guarantee the robustness and sensory quality of the fruit at the destination market [
45,
46]. Our results show that the sensory descriptors change among localities and growth cycles and could be explained as discussed above with regards to the flesh mineral and FAME composition.
There is no information that reports the role of the mineral contents on the sensory quality of Hass avocado fruits. However, the role of the fruit mineral composition on fruit softness and mesocarp discoloration in ‘Pinkerton’ avocado fruits was studied by Rooyen and Bower, who published mineral concentrations related to low, medium and high risks of developing internal flesh disorders [
38]. The results of this work contribute not only to reporting optimal mineral ranges for reducing internal damage but also to improving the sensory profile of Hass avocados.
The flesh fatty acid relationship is influenced by the temperature of the localities or regions where the Hass avocado is produced. This phenomenon has been found in many Hass avocado-producing countries around the world. Some studies have reported that Hass avocados produced in regions with low temperatures had greater oil contents and higher proportions of oleic acid than those grown in high-temperature areas. In contrast, fruits grown in high-temperature regions had more palmitic acid [
47,
48]. Ferreyra et al. found that the fatty acid proportion changed with elevation in Chile [
40].
The authors reported that high oleic acid contents were related to the maximum mean temperature. Therefore, different studies have postulated the fatty acid profile as a biomarker of fruit origin. However, high variabilities exist in avocado-producing countries such as México, Colombia, Chile, and Peru, thus making such classifications difficult. The EB locality has an oleic acid content similar to the cool regions or farms from South Africa [
48], New Zealand [
47], and Chile [
40,
49], whereas the low-elevation orchard has a FAME profile similar to producing localities in Peru, Spain [
49] and California, USA [
50]. Fruits grown at the R orchard at both nutrient management levels had more palmitoleic acid than fruits of other international origins (low and high elevation or temperature) and were similar to the avocados produced in Florida, USA [
51]. There is a lack of information relating the fatty acid profile to the sensory quality. In this work, it is clear that the sensory analysis was influenced by the proportion of fatty acids in the samples, especially with regards to unsaturated fats.
The mouth sensory texture perception could be associated with a change in the mesocarp tissue due to enzymatic (polygalacturonase and cellulase) action during fruit ripening and the mineral and fatty acid compositions. The parenchyma tissue contains oil bodies as a finely dispersed emulsion surrounded by a thin cellulose wall [
52], whereas idioblasts are specialized cells containing large oil sacs covered by a thick cellular wall.
During Hass avocado ripening, the degradation of parenchyma cell walls and the release of some oil bodies in emulsion form occur [
53]. Despite the importance of the role of fatty acids in Hass avocado composition and quality, few studies have reported the role of nutrient management in modulating fatty acids. This work contributes to identifying the quality markers related to nutrient management under field conditions. Our results show the importance of having a robust fruit flesh composition, and it is necessary to consider the rootstock selection, nutrition management and orchard location to guarantee a consistent quality to consumers.
It is necessary to increase the knowledge on the development of nondestructive devices, NIR applications, or other technologies focused on analyzing the discriminant biomarkers found in this work to predict the integral quality of Hass avocados and their shelf life before export. These strategies could reduce postharvest losses and satisfy consumer expectations worldwide.
Figure 1.
Schematic representation of the experimental design and postharvest quality analysis. Locality (orchard): R: Recuerdo, N: Nápoles. BIK: Balanced Indices of Kenworthy. P: nutrient management of the farmer. A: Nutrient management based on the BIK. Harvest cycle: 1. Harvest from the intermediate flowering period. 2. Harvest from the main flowering period. FAMEs: fatty acid methyl esters. AAS: Atomic absorption spectroscopy. ICP: Inductively Coupled Plasma.
Figure 1.
Schematic representation of the experimental design and postharvest quality analysis. Locality (orchard): R: Recuerdo, N: Nápoles. BIK: Balanced Indices of Kenworthy. P: nutrient management of the farmer. A: Nutrient management based on the BIK. Harvest cycle: 1. Harvest from the intermediate flowering period. 2. Harvest from the main flowering period. FAMEs: fatty acid methyl esters. AAS: Atomic absorption spectroscopy. ICP: Inductively Coupled Plasma.
Figure 2.
Climate conditions of the Hass avocado experimental zones corresponding to the following variables: (a) maximum temperature, (b) minimum temperature and (c) evapotranspiration. O-EB: Orchard El Banco. O-N: Orchard Nápoles. O-R: Orchard Recuerdo. ET0: evapotranspiration.
Figure 2.
Climate conditions of the Hass avocado experimental zones corresponding to the following variables: (a) maximum temperature, (b) minimum temperature and (c) evapotranspiration. O-EB: Orchard El Banco. O-N: Orchard Nápoles. O-R: Orchard Recuerdo. ET0: evapotranspiration.
Figure 3.
Yield (production average, kg/per tree) of Hass avocados in each orchard using 2 nutrient management practices during 2 production cycles. Different letters represent significant differences (P < 0.05) as determined using ANOVA and Tukey’s post hoc test. T: treatments. N: Nápoles. R: Recuerdo. P: nutrient management of the farmer. A: Nutrient management based on the BIK standards. Harvest cycles: 1. Harvest from the intermediate flowering period. 2. Harvest from the main flowering period.
Figure 3.
Yield (production average, kg/per tree) of Hass avocados in each orchard using 2 nutrient management practices during 2 production cycles. Different letters represent significant differences (P < 0.05) as determined using ANOVA and Tukey’s post hoc test. T: treatments. N: Nápoles. R: Recuerdo. P: nutrient management of the farmer. A: Nutrient management based on the BIK standards. Harvest cycles: 1. Harvest from the intermediate flowering period. 2. Harvest from the main flowering period.
Figure 4.
Fruit harvest size classification results according to the Codex Stand 197, 1995. R: Recuerdo orchard. N: Nápoles orchard. P: Nutrient management of the farmer. A: Nutrient management program based on the BIK standards. 1. Harvest from the intermediate flowering period. 2. Harvest from the main flowering period.
Figure 4.
Fruit harvest size classification results according to the Codex Stand 197, 1995. R: Recuerdo orchard. N: Nápoles orchard. P: Nutrient management of the farmer. A: Nutrient management program based on the BIK standards. 1. Harvest from the intermediate flowering period. 2. Harvest from the main flowering period.
Figure 5.
Ripening heterogeneity results of Hass avocados. Orchards: EB: El Banco, N: Nápoles, and R: Recuerdo. A: Nutrient management based program on the Balanced Indices of Kenworthy (BIK) standards. P: Nutrient management of the farmer. 1. Harvest from the intermediate flowering period. 2. Harvest from the main flowering period. DRTE: Days to ready-to-eat. The crosses represents the mean values, the yellow dots indicate the minimum and maximum values, and the green dots and brown asterisks denote outliers.
Figure 5.
Ripening heterogeneity results of Hass avocados. Orchards: EB: El Banco, N: Nápoles, and R: Recuerdo. A: Nutrient management based program on the Balanced Indices of Kenworthy (BIK) standards. P: Nutrient management of the farmer. 1. Harvest from the intermediate flowering period. 2. Harvest from the main flowering period. DRTE: Days to ready-to-eat. The crosses represents the mean values, the yellow dots indicate the minimum and maximum values, and the green dots and brown asterisks denote outliers.
Figure 6.
Principal component analysis (PCA) results of the mineral and FAME contents grouped by the samples. a) Score plot. b) Loading plots. Blue dots: active variables. Orchards: EB: El Banco, N: Nápoles, and R: Recuerdo. A: Nutrient management based on the Balanced Indices of Kenworthy (BIK). P: Nutrient management of the farmer. 1. Harvest from the intermediate flowering period. 2. Harvest from the main flowering period.
Figure 6.
Principal component analysis (PCA) results of the mineral and FAME contents grouped by the samples. a) Score plot. b) Loading plots. Blue dots: active variables. Orchards: EB: El Banco, N: Nápoles, and R: Recuerdo. A: Nutrient management based on the Balanced Indices of Kenworthy (BIK). P: Nutrient management of the farmer. 1. Harvest from the intermediate flowering period. 2. Harvest from the main flowering period.
Figure 7.
Partial least squares discriminant analysis (PLS-DA) results of the fatty acid and mineral contents grouped by orchard. Score plot (a) and loading plots (b). R2= 88.9 (3 factors). Orchards: EB: El Banco, N: Nápoles, and R: Recuerdo. A: Nutrient management based on the Balanced Indices of Kenworthy (BIK). P: Nutrient management of the farmer. 1. Harvest from the intermediate flowering period. 2. Harvest from the main flowering period.
Figure 7.
Partial least squares discriminant analysis (PLS-DA) results of the fatty acid and mineral contents grouped by orchard. Score plot (a) and loading plots (b). R2= 88.9 (3 factors). Orchards: EB: El Banco, N: Nápoles, and R: Recuerdo. A: Nutrient management based on the Balanced Indices of Kenworthy (BIK). P: Nutrient management of the farmer. 1. Harvest from the intermediate flowering period. 2. Harvest from the main flowering period.
Figure 8.
Sensory profile of fruits from different orchards under different nutrient management (P and A) and growth cycle (1 and 2) conditions. Orchards: EB: El Banco, N: Nápoles, and R: Recuerdo. A: Nutrient management based on the Balanced Indices of Kenworthy (BIK). P: Nutrient management of the farmer. 1. Harvest from the intermediate flowering period. 2. Harvest from the main flowering period.
Figure 8.
Sensory profile of fruits from different orchards under different nutrient management (P and A) and growth cycle (1 and 2) conditions. Orchards: EB: El Banco, N: Nápoles, and R: Recuerdo. A: Nutrient management based on the Balanced Indices of Kenworthy (BIK). P: Nutrient management of the farmer. 1. Harvest from the intermediate flowering period. 2. Harvest from the main flowering period.
Table 1.
Ranges of chemical contents of the soils in the experimental avocado orchards.
Table 1.
Ranges of chemical contents of the soils in the experimental avocado orchards.
Mineral |
R Min - Max |
N Min - Max |
EB Min - Max |
Depth (cm) |
0. 45 |
0.45 |
0.45 |
pH |
5.42 ± 0.10 |
5.50 ± 0.06 |
5.12 ± 0.05 |
EC (ds/m) |
0.33 ± 0.10 |
0.35 ± 0.06 |
1.05 ± 0.11 |
OM (%) |
12.36 ± 0.47 |
14.85 ± 0.88 |
12.53 ± 0.69 |
P* |
4.69 ± 0.72 |
5.45 ± 0.70 |
37.79 ± 5.08 |
S* |
67.03 ± 7.4 |
75.13 ± 7.9 |
30.52 ± 1.83 |
Mg* |
0.97 ± 0.15 |
0.99 ± 0.04 |
1.64 ± 0.27 |
Ca** |
2.87± 0.40 |
3.90 ± 0.5 |
4.04 ± 0.61 |
K** |
0.62 ± 0.09 |
0.44 ± 0.12 |
0.62 ± 0.05 |
Na** |
0.09 ± 0.003 |
0.08 ± 0.008 |
0.10 ± 0.001 |
CEC** |
4.64 ± 1.00 |
5.29 ± 0.6 |
6.98 ± 0.82 |
B* |
0.22 ± 0.04 |
0.26 ± 0.03 |
0.33 ± 0.06 |
Mn* |
2.39 ± 0.30 |
2.19 ± 0.20 |
13.05 ± 0.88 |
Cu* |
2.49 ± 0.90 |
0.69 ± 0.20 |
5.65 ± 0.41 |
Fe* |
101.95 ± 2.72 |
80.20 ± 5.60 |
309.32 ± 22.23 |
Zn* |
1.54 ± 0.20 |
3.76 ± 1.20 |
8.56 ± 1.35 |
Soil texture |
SL |
SL |
SL |