Boundary Line Analysis: A Study to Establish Cationic Macronutrient Availability Classes in Cocoa Trees in Brazil

Boundary Line Analysis: A Study to Establish Cationic Macronutrient Availability Classes in Cocoa Trees in Brazil | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Boundary Line Analysis: A Study to Establish Cationic Macronutrient Availability Classes in Cocoa Trees in Brazil Amanda Santos Oliveira, Jerusa Schneider, Júlio César Lima Neves, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6916464/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 04 Dec, 2025 Read the published version in Discover Soil → Version 1 posted 11 You are reading this latest preprint version Abstract To ensure high cacao yields, assessing soil fertility is crucial for appropriate amendment and fertilizer use. This study uses the boundary line method to determine new cationic macronutrient availability classes for cacao at two soil depths (0–10 cm and 0–20 cm), aiming for accurate fertilization recommendations for modern cacao cultivars. We analyzed a database from 15 experimental areas in southern Bahia, Brazil, collecting soil samples from two depths (0–10 cm and 0–20 cm) to measure K + , Ca 2+ , Mg 2+ , and their ratios (Ca/Mg, Ca/K, Mg/K, (Ca + Mg)/K). The boundary line analysis helped identify potential response curves for cacao productivity, establishing seven nutrient availability classes from very low to excess. For the 0–20 cm soil layer, the adequate ranges for Ca 2+ (100–200 mg dm -3 ) and Mg 2+ (40–80 mg dm -3 ) matched literature, while the K + range (48–94 mg dm -3 ) was lower, potentially reducing potassium fertilizer use. In the 0–10 cm soil layer, the ranges were: K + (57–101 mg dm -3 ), Ca 2+ (110–220 mg dm -3 ), and Mg 2+ (45–90 mg dm -3 ), indicating higher nutrient accumulation. This study also provided the first specific adequate availability classes for Ca/K (10–20) and Mg/K (2–4) ratios. The research established reference values for "tendency to excess" and "excess" classes, providing a nuanced understanding of nutrient dynamics in cacao cultivation and offering precise fertilization recommendations to enhance productivity. These findings support the fertilization process, complementing or replacing information from the 0–20 cm layer. Cocoa cultivation soil sampling soil fertility sufficiency ranges fertilizer recommendations Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 1. INTRODUCTION Cacao ( Theobroma cacao L.) has historically shaped the organizational processes of various cultures and continues to significantly influence important socioeconomic changes in many countries worldwide [ 1 ]. This is particularly evident in the context of family farming, which encompasses between five to six million small cacao farms worldwide [ 2 ]. Although there are regional variations in cacao production, the highest yields are observed in areas with favorable climatic conditions and farming systems that incorporate genetic improvement and new cultivation technologies [ 3 , 4 ]. In this context, successfully managing cacao trees is challenging, and plant nutrition remains one of the most crucial components [ 5 , 6 ]. As an arboreal species, the cacao tree has a deep root system; however, its roots are primarily concentrated in the more superficial layers of the soil. Consequently, the most commonly analyzed layer for soil fertility assessment and recommendations regarding liming and fertilization is the 0‒20 cm depth [ 4 ]. At depths greater than 20 cm, the biomass of the root system in adult cacao trees is significantly reduced, with the quantity of fine roots in the 0‒10 cm layer potentially being more than twice that found in the 10‒20 cm layer [ 7 ]. Furthermore, correlations between nutrient concentrations in leaves and soil are stronger in the 0‒10 cm layer [ 8 ], indicating that this layer is particularly relevant for evaluating nutrient availability for the crop, especially for nutrients with lower mobility in the soil. To ensure proper nutrition and sustained productivity over successive crop cycles, soils designated for cultivation must provide adequate amounts of water and nutrients [ 9 ]. Thus, soil chemical analysis is crucial tool for assessing soil fertility. It plays a key role in determining fertilizer doses, aiming to correct nutritional deficiencies and ensure the adequate supply of nutrients. This approach enhances productivity and improves resource use efficiency [ 10 , 11 , 4 ]. Souza Júnior et al. [ 12 ] examined the classification and interpretation of chemical attributes of soils for cocoa cultivation. They found that much of the existing research on this topic is outdated, and its findings need to be reassessed. This is primarily due to the fact that the genetic materials currently in use have a significantly higher production potential than those employed in previous crops. Cationic macronutrients such as potassium (K + ), calcium (Ca 2+ ), and magnesium (Mg 2+ ) are vital for the nutrition of cacao trees. Potassium improves resistance to abiotic stresses and diseases and participates in physiological functions such as enzyme activation and photosynthesis [ 13 ]. Calcium maintains cellular integrity, regulates stomatal opening, and plays a crucial role in nutrient absorption, all of which directly impact plant development and productivity [ 14 ]. Magnesium, an essential component of chlorophyll, is fundamental not only for photosynthesis but also for ATP synthesis and enzyme activation [ 15 ]. Maintaining a balance between Ca²⁺ and Mg²⁺ in the soil is fundamental for efficient nutrient uptake, as the ratios of Ca/Mg, Ca/K, Mg/K, and (Ca + Mg)/K influence nutrient availability and overall plant health [ 16 , 5 ]. An imbalance in these ratios can compromise nutrient absorption, affecting physiological processes such as water regulation, enzyme activity, and structural integrity [ 15 , 17 , 18 ]. In tropical soils, high rainfall and leaching can result in significant K + losses, requiring careful management to prevent deficiencies [ 19 , 20 ]. Therefore, the analysis and management of cationic macronutrients and their ratios are essential for optimizing cacao tree productivity and health. Given these considerations, new studies are required to update or establish nutrient availability classifications that support more precise fertilization recommendations aligned with the needs of modern cacao cultivars [ 4 , 21 ]. In this context, the use of mathematical models to relate soil nutrient content and crop productivity emerges as an innovative approach to address this gap. The Boundary Line (BL) approach, proposed by Webb [ 22 ], offers a framework for analyzing the relationship between independent and dependent variables through scatter plots [ 23 ]. The BL represents the upper boundary portion of the dataset, highlighting the strongest connection within specific value ranges [ 18 ]. By defining optimal performance within the population, the BL approach allows for the isolation of the effects of a specific production factor on crop productivity, even when other factors vary [ 24 ]. However, data points below this limit indicate that the dependent variable (productivity) may be influenced by unexamined factors [ 25 ]. In agricultural research, the BL framework enables the analysis of extensive data from commercial and experimental crops cultivated under diverse conditions, with the goal of identifying high-yield populations and their associated nutrient profiles [ 6 , 18 ]. Therefore, this study aimed to establish new categories for the availability of exchangeable cationic macronutrients in cacao trees across two soil layers (0–10 cm and 0–20 cm) using the BL approach. This framework seeks to refine nutrient availability classifications and improve fertilization recommendations, ensuring optimal cacao tree productivity and economic returns. 2. METHODS 2.1. Setting up and description of experimental conditions A database from the Renova Cacau project, established in 2015 and concluded in 2022, was used. This database contains information on cacao bean productivity and soil nutrient contents. The project consists of a full factorial design, with three renewal methods of old cacao plantations and five genetic materials, each replicated twice per experimental area (EA). The study was conducted over three consecutive years (2020–2022), encompassing 15 experimental areas installed in 15 commercial cacao farms, each corresponding to a single EA, located in 11 municipalities in the southern region of Bahia, Brazil. The study area spans latitudes 13°11'35'' S to 15°26'00" S and longitudes 39°06'36" W to 39°35'18" W. The soils in this region exhibit substantial variability, as shown in Fig. 1 , which maps the different soil types across the study area and the location of the experimental farms. Figure 1 . The three methods of renovation are: R1 – grafting onto basal shoots of old cacao trees, followed by their gradual removal; R2 – planting new grafted seedlings and gradually removing the old cacao trees; and R3 – removing old cacao trees and planting banana plants for temporary shading, followed by planting new grafted seedlings. The five genetic materials were: CCN 51, CP 49, FA 13, PS 1319, SJ 02. Each EA covered 3,000 m² and was distributed across the region to encompass a wide diversity of soils cultivated with cacao trees. The plot consists of 10 cacao trees per genotype and renewal method, with five of these trees making up the productive plot (cacao trees whose yields were assessed), totaling 300 cacao trees per EA. Before setting up the experiments, soil samples were collected (20 simple samples per composite sample at depths of 0–20 cm and 20–40 cm) and analyzed for their chemical properties. These analyses were used to recommend liming and gypsum application for cacao cultivation, following the criteria proposed by Souza Júnior et al. [ 4 ], for cocoa trees, whereby: liming was carried out in the EA that had base saturation (V) of less than 65% in the 0–20 cm soil layer, with the aim of increasing V to 75%, considering a reaction depth of 5 cm. Gypsum application was carried out in the AE that had aluminum saturation (m) greater than 20% in the 20–40 cm soil layer, with the aim of reducing m to 20, considering the 30 cm thick reaction layer. Limestone and gypsum were manually applied to cover the entire soil surface without being incorporated into it. This surface application of limestone motivated the consideration of a shallower reaction depth of 5 cm for liming. By the final year of this study (2022), no additional applications of limestone and/or gypsum had been made. For the renewal methods involving seedling planting (R2 and R3), grafting with the five genetic materials was performed on seedlings approximately 75 days after sowing. The cacao seedlings were planted approximately eight months after sowing in cylindrical pits measuring 60 cm in depth and 20 cm in diameter. Each pit was supplemented with 120 g of single superphosphate, 5 g of potassium chloride, 40 g of dolomitic limestone, 15 g of FTE BR-12 (containing 9% Zn, 1.8% B, 0.8% Cu, 2.1% Mn, and 0.1% Mo), and 2 dm 3 of chicken manure [ 4 ]. In the first two years, the plants received establishment fertilization, with the annual dose divided into four applications [ 4 ]. For R2 and R3, 500 and 800 grams per plant per year of NPK 16-16-16 fertilizer were used in the first and second years, respectively. This latter amount was also applied annually in R1 (renewal method via grafting on basal shoots). From the third year of the experiment onwards, fertilizer doses were tailored for each experimental area (EA) based on the most recent soil analysis of the 0–10 cm layer, following the recommendations of Souza Júnior et al. [ 4 ]. The annual doses of nitrogen (N), phosphorus (P), and potassium (K) (Table 1 ) were divided into four applications, using urea, monoammonium phosphate or triple superphosphate, and potassium chloride as sources. Table 1 Annual fertilization with N, P, and K from the third to the seventh year of the experiment, based on soil P and K contents. Year N P content in the soil K content in the soil --------- mg dm − 3 ----------- -------------- mg dm − 3 -------------- 60 180 N, kg ha − 1 P 2 O 5 , kg ha − 1 K 2 O, kg ha − 1 3º e 4º 175 260 190 125 40 0 330 240 170 20 0 5º a 7º 220 290 220 155 70 0 370 280 200 40 0 Table 1 . Micronutrient fertilization was applied once a year with the following doses: 1.0 kg ha − 1 of B (for EA with B in the soil less than 0.7 mg dm − 3 ); 2.0 kg ha − 1 of Cu (for EA with Cu in the soil less than 2.0 mg dm − 3 ) and 2.5 or 5.0 kg ha − 1 of Zn (for EA with Zn in the soil between 3.5 and 5.0 mg dm − 3 or less than 3.5 mg dm − 3 of Zn, respectively). The sources used were boric acid and copper and zinc sulphates. These fertilizers were dissolved in water, and the solution was applied and mixed into chicken litter. A volume of 250 cm³ of this chicken litter was then applied to each plant in order to provide the aforementioned micronutrient doses. During the experiment, we took several measures to manage the environment. We used a brush cutter to remove invasive plants, pruned diseased plant material affected by witches' broom disease, and applied registered agricultural pesticides to control pests and diseases as needed. 2.2. Database Data from three years, 2020 to 2022, were used, during which the EA had been established for five to seven years, making the productivity results representative. The study evaluated 13 to 17 EA per year, located across 11 municipalities in southern Bahia, Brazil. For soil analyses, six sample plots were considered in each experimental area (three renewal methods and two repetitions), with each sample plot comprising an area covering 50 cacao trees (five clones and 10 cacao trees per clone). Soil samples were collected from the 0–10 cm and 10–20 cm layers (20 simple samples per composite sample) over the three years evaluated. The analytical methodologies employed are described by Teixeira et al. [ 26 ], with K + extracted using Mehlich-1 and Ca 2+ and Mg 2+ extracted using 1.0 mol/L KCl. Additionally, the equimolar ratios of Ca/Mg, Ca/K, Mg/K, and (Ca + Mg)/K were calculated. The nutrient contents and their respective ratios for the 0–20 cm soil layer were estimated by averaging the values from the 0–10 cm and 10–20 cm layers. For estimating productivity, the average yield of the useful plot (five cacao trees per clone) was considered, with healthy fruits being harvested and counted monthly. The annual yields, measured in kilograms of dry beans per plant, were calculated by multiplying the total number of fruits harvested each year by the average weight of dry beans per fruit for each clone. The fruit index was determined as the average weight of dry beans per fruit, with 40 fruits per clone evaluated per experimental area per year, after the fresh beans were dried. Data on productivity over three years (considering different ages and climatic conditions), three renewal methods, and five clones were used. To ensure consistency in productivity measurement, we chose to use relative yield (RY). RY is calculated as follows: (RY = average productivity of the useful plot / highest productivity for each clone, renewal method, and year) * 100, expressed as a percentage. Subsequently, the average RY of the five clones forming the soil sample plot was calculated. Finally, for each year, the average relative yield (ARY) was determined using the formula: ARY = (average RY of the useful plots of the five clones / highest average RY for each year) * 100, expressed as a percentage. The dataset consisted of 270 observations, considering the three years of evaluation, three renewal methods, and two repetitions per EA. 2.3. Data processing and statistical analysis The cacao bean yield and the nutrient contents in the soil of the respective sample plots were plotted using Microsoft Excel® to generate scatter plots for each nutrient in the two soil layers studied (0–10 cm and 0–20 cm). After plotting the scatter plots, we were able to visualize the boundary population within the point cloud that best represented the relationship between ARY (dependent variable) and soil nutrient content (independent variable) across the intervals corresponding to the upper limits or upper boundary region [ 23 ]. To select the (x,y) pairs corresponding to the upper limit of the relationship between ARY and soil nutrient content or ratios established in the scatter plots, these pairs were obtained manually. Subsequently, using the SigmaPlot 10.1 software, regression models were fitted to relate ARY with the nutrient content or ratios in the soil samples taken from the upper boundary. These two variables did not allow for the selection of a single regression model that fit the data satisfactorily. Therefore, we decided to use two models for the same dataset, with the endpoint of the first model (ŷ 1 ) serving as the intersection point with the start of the second model (ŷ 2 ). The two selected regression models were those that demonstrated the best biological relevance and fit the data well, showing the highest adjusted R 2 and having coefficients significant at the 10% content according to the t -test. To define the availability classes for nutrient contents or their relationships in each soil layer, we adapted the criteria presented in Table 2 , adapted from Fernandes [ 27 ]. Table 2 Limits for establishing nutrient sufficiency ranges in soil based on the average relative yield (ARY) of cacao trees Sufficiency range ARY (%) Very low < 40 Low ≥ 40 a < 70 Medium ≥ 70 a < 90 High or adequate ≥ 90 a ≤ 100 Very high ≥ 90 a < 100, to the right of the maximum Tendency to excess ≥ 70 to < 90, to the right of the maximum Excess < 70, to the right of the maximum Table 2 . In exponential models, it was not possible to mathematically determine the nutrient content in the soil required to achieve the maximum estimated ARY, as these models are asymptotic. In this study, the nutrient content (or the ratio between them) required to achieve maximum ARY was estimated by averaging the values calculated at two points to obtain 90% ARY: one to the left of the maximum point (lower limit of the adequate range) and one to the right of the maximum point (lower limit of the excess trend range) (Table 2 ). 3. RESULTS For the three macronutrients and their equimolar relationships, broad plateaus were observed, separating the regions of deficiency and excess. This made it impossible to use a single regression model to explain the relationship between nutrient content in the soil (or their ratios) and average relative yield (ARY). Therefore, in all scenarios, two regression models were employed. The endpoint of the first model (ŷ 1 ) served as the starting point for the second model (ŷ 2 ). In general, regardless of the nutrient or their interactions and soil layer, the selected models demonstrated significant coefficients and strong predictive ability, with most determination coefficients (R 2 ) exceeding 0.90. The variation of ARY as a function of exchangeable potassium (K + ) content in the soil showed similarity for both layers (Figs. 2 A and 2 B). Initially, a linear response was observed (ŷ 1 ), followed by a quadratic regression (ŷ 2 ). During the linear phase, each 1.0 mg dm⁻³ increase in K⁺ resulted in ARY increases of 1.37 percentage points in the 0–10 cm layer and 1.99 percentage points in the 0–20 cm layer (Figs. 2 A and 2 B). Figure 2 . The potential productivity response curves of cacao trees to Ca 2+ contents in the 0–10 cm and 0–20 cm soil layers are shown in Figs. 2 A and 2 B, respectively. In both layers, an initial linear response (ŷ 1 ) was observed, indicating that for each 1.0 mmol c dm − 3 of Ca 2+ in the 0–10 cm and 0–20 cm soil layers, there are respective increases of 2.46 and 3.47 percentage points in ARY (Figs. 2 A and 2 B). On the other hand, for the second model (ŷ 2 ), the best fit was achieved with the exponential model for the 0–10 cm layer (Fig. 3 A) and the quadratic model for the 0–20 cm layer (Fig. 3 B). Figure 3 . The potential productivity response curves of cacao trees in relation to Mg 2+ contents in the 0–10 cm and 0–20 cm soil layers (Figs. 4 A and 4 B) showed similar patterns to those of Ca 2+ (Fig. 2 ). However, the sequence of the selected models differed, with the first being exponential (ŷ 1 ) and the second linear (ŷ 2 ). Based on ŷ 1 , it can be estimated that an increase from 3.5 to 7.0 mmol c dm − 3 of Mg 2+ in the 0–10 cm layer would result in the ARY rising from 25.8–91.3%, representing a 65.5 percentage point increase (Fig. 4 A). A variation in Mg²⁺ concentration from 2.0 to 6.0 mmol c dm − 3 of Mg 2+ in the 0–20 cm soil layer would result in an estimated increase in ARY from 21.2–90.5%, representing a 69.3 percentage point rise (Fig. 4 B). Figure 4 . The variation in ARY as a function of the soil Ca/Mg ratio followed a similar trend in both layers (Fig. 5 ), resembling the patterns observed for Ca²⁺ and Mg²⁺ (Figs. 3 and 4 , respectively). However, the plateau associated with the Ca/Mg ratio was broader than those of the individual nutrients, suggesting greater flexibility in cacao nutrient balance. The linear regression slope coefficients (ŷ1) indicate that each 0.1 unit increase in the Ca/Mg ratio led to ARY increases of 19.8 percentage points in the 0–10 cm layer and 10.5 percentage points in the 0–20 cm layer (Figs. 5 A and 5 B). Figure 5 . The variation of ARY in relation to the Ca/K ratio initially showed similar trends in both layers, with the first model (ŷ1) exhibiting an exponential response (Figs. 6 A and 6 B). However, the plateau observed in the 0–10 cm layer (Fig. 6 A) was broader than that in the 0–20 cm layer (Fig. 6 B). In both layers, the second model (ŷ2) also followed an exponential pattern (Figs. 6 A and 6 B). Figure 6 . The potential response curves of cacao tree productivity to the Mg/K ratio in the 0–10 cm and 0–20 cm soil layers (Figs. 7 A and 7 B) showed similar patterns in the selected models, both initially exhibiting a linear behavior (ŷ 1 ). The slope coefficients of ŷ 1 indicate that for every 0.1 unit increase in the Mg/K ratio in the 0–10 cm and 0–20 cm soil layers, there were corresponding increases of 42.3 and 51.0 percentage points in ARY, respectively (Figs. 6 A and 6 B). Regarding the second model (ŷ 2 ), the best fit was achieved with the quadratic model for both layers. However, in the excess region for the Mg/K ratio, the 0–20 cm layer (Fig. 7 B) showed a more pronounced decrease in ARY compared to the 0–10 cm layer (Fig. 7 A). Figure 7 . Considering the linear models (ŷ 1 ), it can be estimated that for each unit increase in the (Ca + Mg)/K ratio in the 0–10 cm and 0–20 cm soil layers, there are increases of 20.9 and 22.0 percentage points in ARY, respectively (Figs. 7 A and 7 B). For both layers, the second selected model (ŷ 2 ) was the exponential one (Figs. 8 A and 8 B). Figure 8 . Defined availability classes for nutrient contents and their equimolar ratios ranged from "very low" to "excessive" in both layers (Table 3 ), according to the criteria in Table 2 . However, the "very low" availability class was not established for K⁺, Ca²⁺, Ca/Mg, Ca/K, and Mg/K in the 0–10 cm layer, nor for Ca²⁺, Ca/Mg, and Mg/K in the 0–20 cm layer, as these fell outside the sampling range (Table 3 ). Nonetheless, availability classes for "tendency to excess" and "excess" were identified across all nutrients and ratios—novel findings for cacao cultivation. Table 3 Availability classes of exchangeable cationic macronutrients for cacao trees in two soil layers in experimental areas in southern Bahia, Brazil. Attribute Unit Very low Low Medium High or adequate Very high Tendency to excess Excess ARY 1/ % < 40 ≥ 40 a < 70 ≥ 70 a < 90 ≥ 90 a ≤ 100 < 100 a ≥ 90 < 90 a ≥ 70 < 70 Layer 0–10 cm K + mg dm − 3 - 248 Ca 2+ mmol c dm − 3 - 106 Mg 2+ mmol c dm − 3 37 Ca/Mg - 6,4 Ca/K - 47 Mg/K - 21,9 (Ca + Mg)/K 70 Layer 0–20 cm K + mg dm − 3 218 Ca 2+ mmol c dm − 3 - 100 Mg 2+ mmol c dm − 3 30 Ca/Mg - 6,6 Ca/K 39,2 Mg/K - 21,1 (Ca + Mg)/K 65 1/ ARY: average relative yield Table 3 . For all three nutrients, as expected, their contents in all availability classes were higher in the 0–10 cm layer compared to the 0–20 cm layer, reflecting nutrient accumulation in the upper soil layers due to cycling processes. For the 0–20 cm soil layer, the K⁺ content within the adequate availability class ranged from 48 to 94 mg dm⁻³ (Table 3 ). In contrast, the suitable range for the 0–10 cm layer was slightly higher, spanning from 57 to 101 mg dm⁻³, representing an 11% increase compared to the deeper layer. Considering Ca²⁺ concentration, the adequate availability range in the 0–20 cm soil layer was determined to be between 23 and 47 mmolc dm⁻³ (Table 3 ). Meanwhile, in the 0–10 cm layer, the appropriate range extended from 32 to 62 mmolc dm⁻³, averaging 34% higher than the deeper layer. For Mg²⁺, the adequate availability range in the 0–20 cm soil layer was defined as 7 to 16 mmolc dm⁻³ (Table 3 ). In the 0–10 cm layer, however, the suitable range was found to be slightly broader, between 8 and 20 mmolc dm⁻³. Regarding nutrient ratios, the optimal Ca/Mg ratio was similar across both layers, ranging from 1.6 to 3.9 in the 0–10 cm layer and 1.5 to 3.8 in the 0–20 cm layer (Table 3 ). These values align with previous recommendations for cacao but confirm a narrower optimal range, likely due to the crop’s high magnesium demand. The optimal Ca/K ratio was consistent between the layers, varying from 8.8 to 22.3 in the 0–10 cm layer and 8.0 to 21.9 in the 0–20 cm layer (Table 3 ). However, the adequate Mg/K ratio exhibited slight differences between the two layers. The lower limit was similar for both layers, at 2.2 in the 0–10 cm and 2.0 in the 0–20 cm layer (Table 3 ). Finally, the optimal (Ca + Mg)/K ratio obtained in this study ranged from 11 to 31 in the 0–10 cm layer and 10 to 24 in the 0–20 cm layer (Table 3 ). These values closely align with previous findings for cacao seedlings but provide an extended range that accommodates field conditions. 4. DISCUSSION The established nutrient availability ranges in this study align with values found in previous literature [ 28 , 4 ]. However, our findings refine these ranges by introducing the "tendency to excess" and "excess" classes, which had not previously been reported for cacao. This distinction provides a more comprehensive understanding of nutrient dynamics in cacao cultivation, highlighting the importance of monitoring nutrient levels beyond traditional adequate ranges (Table 3 ). The 0–10 cm soil layer plays a significant role in cacao nutrition due to nutrient cycling, organic matter deposition, and a higher concentration of fine roots compared to deeper layers [ 7 ]. Studies show that nutrient availability in this layer correlates strongly with leaf nutrient content [ 8 ], making it important for assessing nutrient uptake, especially for less mobile nutrients like Ca²⁺ and Mg²⁺. However, the 0–20 cm layer remains the standard for soil fertility evaluation and fertilization recommendations [ 4 ]. While deeper soil layers contribute to overall nutrient uptake, the analysis of the 0–10 cm layer provides critical insights that can complement traditional assessments in the 0–20 cm layer. Previous studies highlight the need for calibration beyond superficial layers (e.g., 20–40 cm) in perennial crops [ 3 , 29 ], but our findings suggest that refining fertilization strategies based on both surface and deeper layers ensures sustained cacao productivity over multiple crop cycles [ 9 ]. The availability ranges for K⁺ in the 0–10 cm layer were 11% higher than those observed in the 0–20 cm layer (Table 3 ). This difference arises from nutrient cycling and organic matter decomposition, as a significant portion of the cacao root system is concentrated in the topsoil, where decomposition of plant residues actively enriches K⁺ content. Additionally, K⁺ has low mobility in soil, which results in its accumulation in surface layers where organic matter is more abundant [ 4 ]. Compared to previous studies, our findings suggest a lower suitable range for K⁺ in the 0–20 cm layer than the values recommended by Chepote et al. [ 28 ] (≥ 98 mg dm⁻³) and Souza Júnior et al. [ 4 ] (90–120 mg dm⁻³). This lower range indicates that reducing fertilizer applications may be a viable option without negatively impacting cacao productivity, leading to more efficient soil management strategies. K⁺ plays a crucial role in cacao production and is one of the most limiting nutrients for cacao yield [ 30 ]. Given that K⁺ accumulates heavily in fruit husks and is the second most exported nutrient via cacao seeds [ 15 ], maintaining optimal soil levels is essential. However, excessive K⁺ can disrupt Ca²⁺ and Mg²⁺ uptake, altering their K/Ca and K/Mg ratios, potentially affecting plant growth [ 31 ]. This reinforces the importance of defining excess nutrient availability classes as established in this study [ 18 ]. The Ca²⁺ range in the 0–20 cm layer was 23 to 47 mmolc dm⁻³, close to the 30 to 50 mmolc dm⁻³ recommended by Souza Júnior et al. [ 4 ] for cacao cultivation. In deeper layers (0–40 cm), Oliveira et al. [ 29 ] suggested a sufficient range of 12 to 39 mmolc dm⁻³, reinforcing the importance of evaluating soil fertility beyond surface layers. Interestingly, the Ca²⁺ range in the 0–10 cm layer was 34% higher than in the 0–20 cm layer (Table 3 ). Cacao plantations rarely exhibit Ca²⁺ deficiency compared to other macronutrients [ 32 , 15 ]. However, calcium deficiency can occur in highly weathered and acidic soils, reducing productivity [ 33 , 4 ]. Ensuring an adequate Ca²⁺ supply can significantly enhance bean production, but excessive levels may negatively affect cacao growth, as observed in the "tendency to excess" and "excess" classes identified in this study [ 14 ]. Similarly, Mg²⁺ availability in the 0–20 cm layer ranged from 7 to 16 mmolc dm⁻³, consistent with the 10 to 16 mmolc dm⁻³ proposed by Souza Júnior et al. [ 4 ]. However, the lower limit in our findings was below the 13 to 16 mmolc dm⁻³ recommended by Malavolta [ 33 ]. In the 0–10 cm layer, Mg²⁺ availability was 22% higher than in the 0–20 cm layer (Table 3 ). The cacao tree has a high demand for Mg²⁺ [ 12 ], making adequate Mg²⁺ levels critical for productivity sustainability [ 34 ]. However, excessive Mg²⁺ concentrations can interfere with Ca²⁺ and K⁺ absorption, altering nutrient balance [ 17 , 6 ]. This underscores the importance of monitoring not only individual nutrient concentrations but also their equimolar ratios, particularly for exchangeable cations. The balance between Ca²⁺ and Mg²⁺ in the soil affects nutrient uptake by plants. While often considered crucial for nutrient availability, some studies suggest that specific Ca/Mg ratios may have limited direct effects on uptake [ 32 , 15 , 14 ]. Instead, nutrient leaching is driven more by soil properties and environmental conditions than strict nutrient ratios. Root absorption mechanisms further influence Ca²⁺ and Mg²⁺ uptake. High Mg²⁺ levels can inhibit Ca²⁺ absorption and vice versa, due to competitive uptake at the root level [ 34 , 33 ]. Physiologically, Ca²⁺ is critical for cell wall structure and intracellular signaling, while Mg²⁺ serves as a central component of chlorophyll and enzyme activation [ 15 ]. An imbalance between these nutrients can disrupt essential physiological functions, impacting plant growth and productivity. Maintaining a balanced Ca/Mg ratio is essential to prevent nutrient excesses and ensure optimal physiological processes in cacao. This balance, however, varies according to plant species and environmental conditions [ 17 ], reinforcing the need for tailored soil management strategies. The optimal Ca/Mg ratio observed in this study ranged from 1.6 to 3.9 in the 0–10 cm layer and 1.5 to 3.8 in the 0–20 cm layer (Table 3 ), values consistent with those suggested by Souza Júnior et al. [ 4 ] (2.0 to 4.0) and Chepote et al. [ 28 ] (3.0). Given the high magnesium demand of cacao, it is expected that its optimal Ca/Mg ratio would be narrower, as confirmed in this study. Similarly, the Ca/K ratio exhibited consistency across both layers, with values ranging from 8.8 to 22.3 in the 0–10 cm layer and 8.0 to 21.9 in the 0–20 cm layer (Table 3 ). However, the Mg/K ratio showed some variations, particularly in its upper range, despite having similar lower limits—2.2 for the 0–10 cm layer and 2.0 for the 0–20 cm layer (Table 3 ). Importantly, no prior studies specifically suggest appropriate Ca/K or Mg/K ratios for cacao, reinforcing the novelty of our findings. Working with cacao seedlings, Morais and Cabala-Rosand [ 16 ] established the optimal nutrient ratios for the crop, finding that the best plant growth occurred when the equimolar ratio of (Ca + Mg)/K was between 16 and 24.5. Our results align closely with these findings, revealing ranges of 11 to 31 for the 0–10 cm layer and 10 to 24 for the 0–20 cm layer (Table 3 ). These values reinforce the importance of maintaining balanced nutrient ratios to optimize cacao productivity, particularly considering its high demand for both Ca²⁺ and Mg²⁺. It is important to highlight that these findings do not suggest that fertilization and liming recommendations should rely exclusively on the 0–10 cm layer. As reported in previous studies, deeper soil layers (e.g., 20–40 cm) must also be calibrated in perennial crops like cacao, given their extensive root systems and nutrient uptake beyond surface layers [ 3 , 29 ]. Therefore, data from the 0–10 cm layer should complement, rather than replace, information obtained from the 0–20 cm layer, ensuring comprehensive nutrient management strategies. These findings advance our understanding of nutrient dynamics in cacao cultivation, particularly regarding the optimal Ca/Mg, Ca/K, Mg/K, and (Ca + Mg)/K ratios across different soil layers. Establishing precise reference ranges tailored to cacao’s specific nutritional needs will enhance fertilization strategies, improve soil management, and potentially refine recommendations for long-term crop sustainability. 5. Conclusion Nutrient availability classes for K + , Ca 2+ e Mg 2+ were established for cacao trees, along with the ratios Ca/Mg, Ca/K, Mg/K, and (Ca + Mg)/K, in soil layers of 0–10 cm and 0–20 cm. This study provides novel reference values for the "tendency to excess" and "excess" ranges. For the 0–20 cm soil layer, the suitable availability ranges for Ca 2+ and Mg 2+ are similar to those reported in the literature; however, the suitable ranges for K + are lower. For the 0–10 cm soil layer, the ranges identified for the crop are unprecedented and can support the fertilization process, potentially complementing or replacing the information traditionally obtained from the 0–20 cm layer. Declarations Acknowledgements The authors thank the Brazilian cocoa farmers whose farms were available for this study, the Universidade Estadual de Santa Cruz (UESC), Mondelez International, and the Centro de Inovação do Cacau (CIC), under the agreement RD-15540. J.S. is also acknowledged for the CAPES Program – PDPG-SEMIARIDO (Support for the Brazilian Semiarid Region) postdoctoral project, grant number 88887.809620/2023-00. Funding This work is a result of the partnership between Mondelez International and the Universidade Estadual de Santa Cruz (UESC), under the financial management of the Centro de Inovação do Cacau (CIC). It also received support from the CAPES Program – PDPG-SEMIARIDO (Support for the Brazilian Semiarid Region) under grant number 88887.809620/2023-00. Data Availability The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. Competing Interests The authors declare no competing interests . Ethics Approval Not applicable. This study did not involve human participants, human data, or animals. Consent to Participate Not applicable. Consent to Publish Not applicable. Clinical trial number Not applicable. Author Contribution A.O. was responsible for data collection, experimental work, and draft review, contributing to conceptualization and methodology. J.S. was responsible for statistical analysis, data organization, writing the review, and final revisions of the manuscript. J.N. contributed to conceptualization, data curation, methodology, and supervision. D.A. was responsible for funding acquisition and writing review. J.O. contributed to conceptualization, data curation, methodology, and supervision. All authors contributed to the study's conception and design, commented on previous versions of the manuscript, and have read and approved the final manuscript. References Larrauri OM, Neira DP, Montiel MS. Indicators for the analysis of peasant women’s equity and empowerment situations in a sustainability framework: A case study of cocoa production in Ecuador. Sustainability. 2016;8(12):1231. https://doi.org/10.3390/su8121231 . Foundation WC. World Cocoa Foundation. www.worldcocoafoundation.org. 2014. Raimi A, Adeleke R, Roopnarin A. Soil fertility challenges and biofertiliser as a viable alternative for increasing smallholder farmer crop productivity in Sub-saharan Africa. Cogent Food Agric. 2017;3(1):1400933. https://doi.org/10.1080/23311932.2017.1400933 . Souza Júnior JO, Sodré GA, Neves JCL. Fertilidade do solo, correção da acidez e recomendação de adubação para o cacaueiro. In: Souza Júnior JO. (Org.). Cacau: cultivo, pesquisa e inovação. Ilhéus: Editus, 2018; pp. 333–377. https://doi.org/10.7476/9786586213188 Marrocos PC, Loureiro GAH, Araújo QR, Sodré GA, Ahnert D, Baligar VC. Mineral nutrient ratios and cocoa productivity. J Plant Nutr. 2020;43(15):2368–82. https://doi.org/10.1080/01904167.2020.1771582 . Bahia BL, Souza Junior JO, Fernandes LV, Neves JC. Reference values and diagnostic ranges to assess the degree of nutritional balance for cocoa plants. Spanish Journal of Agricultural Research, 2021; 19(1):e0801, 2021. https://doi.org/10.5424/sjar/2021191-17478 Martins PFS, Augusto SG. Propriedades físicas do solo e sistema radicular do cacaueiro, da pupunheira e do açaizeiro na Amazônia oriental. Revista Ceres. 2012;59(5):723–30. https://doi.org/10.1590/S0034-737X2012000500020 . Dantas PAS. Relação entre fertilidade do solo e nutrição do cacaueiro no sul da Bahia. Dissertação (Mestrado em Produção Vegetal). Ilhéus: Universidade Estadual de Santa Cruz; 2011. p. 85. Ronquim CC. Conceitos de fertilidade do solo e manejo adequado para as regiões tropicais. Campinas: Embrapa Monitoramento por Satélite. 2010. https://www.infoteca.cnptia.embrapa.br/infoteca/handle/doc/882598 Oliveira FHT, Arruda JA, Silva IF, Alves JC. Amostragem para avaliação da fertilidade do solo em função do instrumento de coleta das amostras e de tipos de preparo do solo. Revista Brasileira de Ciência do Solo. 2007;31(5):973–83. https://doi.org/10.1590/S0100-06832007000500014 . Cantarutti R, Barros NF, Martinez H, Novais R. Avaliação da fertilidade do solo e recomendação de fertilizantes. In: Novais RF, Alvarez VH, Barros NF, Fontes RLF, Cantarutti RB, Neves JCL, editors. Fertilidade do solo. Viçosa: Sociedade Brasileira de Ciência do Solo; 2007. pp. 769–850. Souza Júnior JO, Marrocos PCL, Neves JCL. Diagnose nutricional para o cacaueiro. In: Souza Júnior JO. (Org.). Cacau: cultivo, pesquisa e inovação. Ilhéus: Editus, 2018; 305–332. https://doi.org/10.7476/9786586213188 Watanabe K, FukuzawaY, Kawasaki SI, Ueno M, Kawamitsu Y. Effects of potassium chloride and potassium sulfate on sucrose concentration in sugarcane juice under pot conditions. Sugar Tech. 2016;18:258–65. https://doi.org/10.1007/s12355-015-0392-z . Lubis ST, Putra ETS, Kurniasih B. Anatomical characteristics of cocoa plant roots as affected by the levels of calcium fertilization. Ilmu Pertanian (Agricultural Science). 2022;7(2):68–74. https://doi.org/10.3390/su8121231 . Aikpokpodion P. Nutrients dynamics in cocoa soils, leaf and beans in Ondo state, Nigeria. J Agricultural Sci. 2010;1(1):1–9. https://doi.org/10.1080/09766898.2010.11884647 . Morais FIO, Cabala-Rosand FP. Efeitos dos equilíbrios entre cálcio, magnésio e potássio no crescimento do cacaueiro. Revista Theobroma. 1971;1(3):21–32. Vliet JAV, Giller K. Mineral nutrition of cocoa: a review. Adv Agron. 2017;141:185–270. https://doi.org/10.1016/bs.agron.2016.10.017 . Lima Neto AJ, Natale W, Deus JAL, Rozane DE. Establishment of critical nutrient levels in the soil and leaf of -Prata? banana using the boundary line. Sci Hort. 2024;328:112923. https://doi.org/10.1016/j.scienta.2024.112923 . Duarte IN, Pereira HS, Korndorfer GH. Lixiviação de potássio proveniente do termopotássio. Pesquisa Agropecuária Trop. 2013;43(2):195–200. https://doi.org/10.1590/S1983-40632013000200003 . Yost R, Attanandana T. Predicting and testing site-specific potassium fertilization of maize in soils of the tropics-An example from Thailand. Soil Sci. 2006;171(12):968–80. https://doi.org/10.1097/01.ss.0000235846.25450.ee . Freire FJ, Silva FC, Carvalho ML, Venegas VHA. Modelagem para otimização da calagem e adubação na cultura de cana-de-açúcar. Bioenergia em Revista: Diálogos. 2022;12(2):09–29. http://www.alice.cnptia.embrapa.br/alice/handle/doc/1151514 . Webb R. Use of the boundary line in the analysis of biological data. J Hortic Sci. 1972;47(3):309–19. https://doi.org/10.1080/00221589.1972.11514472 . Walworth JL, Letzsch WS, Sumner ME. Use of boundary lines in establishing diagnostic norms. Soil Sci Soc Am J. 1986;50:123–8. Guimarães GGF, Deus JAL, Lima Neto AJ. Boundary line method to update critical soil phosphorus and potassium levels in banana plantations in Santa Catarina. Revista Brasileira de Fruticultura. 2023;45:e–979. https://dx.doi.org/10.1590/0100-29452023979 . Schnug E, Heym J, Achwan F. Establishing critical values for soil and plant analysis by means of the boundary line development system (bolides). Commun Soil Sci Plant Anal. 1996;27(13–14):2739–48. https://doi.org/10.1080/00103629609369736 . Teixeira PC, Donagemma GK, Fontana A, Teixeira WG. Manual de métodos de análise de solo. 3 ed. Brasília: Embrapa, 2017; 573 p. https://www.embrapa.br/busca-de-publicacoes/-/publicacao/1085209/manual-de-metodos-de-analise-de-solo Fernandes LV. Normas e determinação de faixas de suficiência para diagnose foliar com base no crescimento relativo de eucalipto. Dissertação (Mestrado em Solos e Nutrição de Plantas), Universidade Federal de Viçosa, Viçosa. 2010; 83 p. https://locus.ufv.br//handle/123456789/5440 Chepote RE, Sodré GA, Reis EL, Pacheco RG, Marrocos PCL, Valle RR. Recomendações de corretivos e fertilizantes na cultura do cacaueiro no sul da Bahia. Ilhéus: CEPLAC/CEPEC, 2013; 44 p. https://www.gov.br/agricultura/pt-br/assuntos/ceplac/publicacoes/boletins-tecnicos-bahia/bt-203.pdf Oliveira MG, Partelli FL, Cavalcanti AC, Gontijo I, Vieira HD. Soil patterns and foliar standards for two cocoa clones in the states of Espírito Santo and Bahia, Brazil. Ciência Rural. 2019;49(10):e20180686. https://doi.org/10.1590/0103-8478cr20180686 . Ajiboye G, Jaiyeoba J, Olaniyan J, Olaiya A. The characteristics and suitability of the soils of some major cocoa growing areas of Nigeria: Tung Iga of Cross River. Agrosearch. 2015;15(1):101–16. Sodré GA, Venturini MT, Ribeiro DO, Marrocos PCL. Extrato da casca do fruto do cacaueiro como fertilizante potássico no crescimento de mudas de cacaueiro. Revista Brasileira de Fruticultura. 2012;34:881–7. https://doi.org/10.1590/S0100-29452012000300030 . Ipinmoroti R, Aikpokpodion P, Akanbi O. Nutritional assessment of cocoa plots for soil fertility management on some cocoa farms in Nigeria. In: Proceedings of 16th International Cocoa Research Conference Held at Grand Hyatt Hotel, Nusa Dua, Bali, Indonesia. [S.l.: s.n.], 2009; pp. 1481–1485. Malavolta E. Manual de calagem e adubação das principais culturas. São Paulo: Agronômica Ceres, 1987; 497 p. Kongor JE, Boecky P, Vermeir P, Van de Walle D, Baert G, Afokwa EO, Dewettinck K. Assessment of soil fertility and quality for improved cocoa production in six cocoa growing regions in Ghana. Agroforest Syst. 2019;93:1455–67. https://doi.org/10.1007/s10457-018-0253-3 . Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 04 Dec, 2025 Read the published version in Discover Soil → Version 1 posted Editorial decision: Revision requested 08 Aug, 2025 Reviews received at journal 19 Jul, 2025 Reviewers agreed at journal 17 Jul, 2025 Reviewers agreed at journal 07 Jul, 2025 Reviews received at journal 03 Jul, 2025 Reviewers agreed at journal 03 Jul, 2025 Reviewers invited by journal 02 Jul, 2025 Editor invited by journal 24 Jun, 2025 Editor assigned by journal 21 Jun, 2025 Submission checks completed at journal 21 Jun, 2025 First submitted to journal 17 Jun, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6916464","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":480182719,"identity":"c94f96ca-4597-48f2-878e-0ebe2b5aa7d3","order_by":0,"name":"Amanda Santos Oliveira","email":"","orcid":"","institution":"State University of Santa Cruz","correspondingAuthor":false,"prefix":"","firstName":"Amanda","middleName":"Santos","lastName":"Oliveira","suffix":""},{"id":480182720,"identity":"d4a390ba-bd26-4f64-ae0a-7745de68b04f","order_by":1,"name":"Jerusa Schneider","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAz0lEQVRIiWNgGAWjYBACxgYGNiAlAaSZD4BFDEjQwpZAnBYgYINq5TEgTgtz/+FnjwsqLGT7pc98k/jwx47BXPoAAYfNSDM3nnFGwnhmX+42yZltyQyWfQmEtPCwSfO2SSRuOMO7TZq34QCDwRkCDmPsPwPU8k8icf8ZnmfSf/4Qo6UhB6ilAWgLD9A6BjZitMxIM5PmOSYB9A+bsWVvWzKPZQ8BLYbAEJPmqamT7e9hfnjjxx87OXMeQloa0AQIaWBgkCeoYhSMglEwCkYBAGlQO/SzuzsbAAAAAElFTkSuQmCC","orcid":"","institution":"State University of Santa Cruz","correspondingAuthor":true,"prefix":"","firstName":"Jerusa","middleName":"","lastName":"Schneider","suffix":""},{"id":480182721,"identity":"78f94e3a-949d-4c0a-b42b-23cbdd400886","order_by":2,"name":"Júlio César Lima Neves","email":"","orcid":"","institution":"State University of Santa Cruz","correspondingAuthor":false,"prefix":"","firstName":"Júlio","middleName":"César Lima","lastName":"Neves","suffix":""},{"id":480182722,"identity":"96fb2cb6-9628-496d-9ea7-e45cbe66974c","order_by":3,"name":"Dario Ahnert","email":"","orcid":"","institution":"State University of Santa Cruz","correspondingAuthor":false,"prefix":"","firstName":"Dario","middleName":"","lastName":"Ahnert","suffix":""},{"id":480182723,"identity":"b5d9cd94-ccb5-484c-b53e-763794be4d28","order_by":4,"name":"José Olimpio Souza Junior","email":"","orcid":"","institution":"State University of Santa Cruz","correspondingAuthor":false,"prefix":"","firstName":"José","middleName":"Olimpio Souza","lastName":"Junior","suffix":""}],"badges":[],"createdAt":"2025-06-17 16:53:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6916464/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6916464/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s44378-025-00129-1","type":"published","date":"2025-12-05T00:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":86001646,"identity":"8d74d2a6-1531-4600-bac0-8ac1d7cb64ac","added_by":"auto","created_at":"2025-07-04 07:39:54","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":346307,"visible":true,"origin":"","legend":"\u003cp\u003eSoil taxonomy map of the southern Bahia region, Brazil, indicating the location of the 15 experimental areas of the Renova Cacau project.\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-6916464/v1/21cf67bba9493ae524f144e5.png"},{"id":86000896,"identity":"cd2233ee-08c1-4f6a-bb0d-cbac9dec108d","added_by":"auto","created_at":"2025-07-04 07:31:54","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":423119,"visible":true,"origin":"","legend":"\u003cp\u003ePotential productivity response curves of cacao trees to exchangeable potassium (K\u003csup\u003e+\u003c/sup\u003e) contents in soil layers of 0-10 cm (A) and 0-20 cm (B) over three years of cultivation in experimental areas in southern Bahia, Brazil.\u003c/p\u003e\n\u003cp\u003eLegend: the arrow in the figures indicates the intersection between the end of the first regression model (ŷ\u003csub\u003e1\u003c/sub\u003e) and the beginning of the second regression model (ŷ\u003csub\u003e2\u003c/sub\u003e).\u003c/p\u003e\n\u003cp\u003e**, *, and \u003csup\u003eo\u003c/sup\u003e indicate significance at the 0.01, 0.05, and 0.10 contents, respectively, according to the \u003cem\u003et\u003c/em\u003e-test.\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-6916464/v1/20cd0c0c54e38a43783d0b86.png"},{"id":86001645,"identity":"e2cf975c-a845-4a14-a174-f43cfd7277cb","added_by":"auto","created_at":"2025-07-04 07:39:54","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":461843,"visible":true,"origin":"","legend":"\u003cp\u003ePotential productivity response curves of cacao trees to exchangeable calcium (Ca\u003csup\u003e2+\u003c/sup\u003e) contents in soil layers of 0-10 cm (A) and 0-20 cm (B) over three years of cultivation in experimental areas in southern Bahia, Brazil.\u003c/p\u003e\n\u003cp\u003eLegend: the arrow in the figures indicates the intersection between the end of the first regression model (ŷ\u003csub\u003e1\u003c/sub\u003e) and the beginning of the second regression model (ŷ\u003csub\u003e2\u003c/sub\u003e).\u003c/p\u003e\n\u003cp\u003e**, *, and \u003csup\u003eo\u003c/sup\u003e indicate significance at the 0.01, 0.05, and 0.10 contents, respectively, according to the \u003cem\u003et\u003c/em\u003e-test.\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-6916464/v1/8dcd198fac524eb6a051f0aa.png"},{"id":86000899,"identity":"f20a0b91-4f69-46d8-9d85-262b0bdb61c0","added_by":"auto","created_at":"2025-07-04 07:31:54","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":481207,"visible":true,"origin":"","legend":"\u003cp\u003ePotential productivity response curves of cacao trees to exchangeable magnesium (Mg\u003csup\u003e2+\u003c/sup\u003e) contents in soil layers of 0-10 cm (A) and 0-20 cm (B) over three years of cultivation in experimental areas in southern Bahia, Brazil.\u003c/p\u003e\n\u003cp\u003eLegend: the arrow in the figures indicates the intersection between the end of the first regression model (ŷ\u003csub\u003e1\u003c/sub\u003e) and the beginning of the second regression model (ŷ\u003csub\u003e2\u003c/sub\u003e).\u003c/p\u003e\n\u003cp\u003e**, *, and \u003csup\u003eo\u003c/sup\u003e indicate significance at the 0.01, 0.05, and 0.10 contents, respectively, according to the \u003cem\u003et\u003c/em\u003e-test.\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-6916464/v1/7aac35211fec39b22f910ecc.png"},{"id":86001647,"identity":"d2c64ad1-10df-4600-bbe9-6d6cc9873a74","added_by":"auto","created_at":"2025-07-04 07:39:54","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":460791,"visible":true,"origin":"","legend":"\u003cp\u003ePotential productivity response curves of cacao trees to the exchangeable calcium to magnesium ratio (Ca/Mg) in soil layers of 0-10 cm (A) and 0-20 cm (B), over three years of cultivation, in experimental areas in southern Bahia, Brazil.\u003c/p\u003e\n\u003cp\u003eLegend: the arrow in the figures indicates the intersection between the end of the first regression model (ŷ\u003csub\u003e1\u003c/sub\u003e) and the beginning of the second regression model (ŷ\u003csub\u003e2\u003c/sub\u003e).\u003c/p\u003e\n\u003cp\u003e**, *, and \u003csup\u003eo\u003c/sup\u003e indicate significance at the 0.01, 0.05, and 0.10 contents, respectively, according to the \u003cem\u003et\u003c/em\u003e-test\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-6916464/v1/a7adfa74efcf27093da1d0b3.png"},{"id":86002105,"identity":"7dc26a93-e955-4f70-891f-57c4dfc46e18","added_by":"auto","created_at":"2025-07-04 07:47:54","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":464735,"visible":true,"origin":"","legend":"\u003cp\u003ePotential productivity response curves of cacao trees to the exchangeable calcium to potassium ratio (Ca/K) in soil layers of 0-10 cm (A) and 0-20 cm (B) over three years of cultivation in experimental areas in southern Bahia, Brazil.\u003c/p\u003e\n\u003cp\u003eLegend: the arrow in the figures indicates the intersection between the end of the first regression model (ŷ\u003csub\u003e1\u003c/sub\u003e) and the beginning of the second regression model (ŷ\u003csub\u003e2\u003c/sub\u003e).\u003c/p\u003e\n\u003cp\u003e**, *, and \u003csup\u003eo\u003c/sup\u003e indicate significance at the 0.01, 0.05, and 0.10 contents, respectively, according to the \u003cem\u003et\u003c/em\u003e-test.\u003c/p\u003e","description":"","filename":"image6.png","url":"https://assets-eu.researchsquare.com/files/rs-6916464/v1/0a23762c49a625893a025705.png"},{"id":86002106,"identity":"f8ebba29-d69f-413e-9583-914fe5b1eb4b","added_by":"auto","created_at":"2025-07-04 07:47:55","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":411684,"visible":true,"origin":"","legend":"\u003cp\u003ePotential productivity response curves of cacao trees to the exchangeable magnesium to potassium ratio (Mg/K) in soil layers of 0-10 cm (A) and 0-20 cm (B) over three years of cultivation in experimental areas in southern Bahia, Brazil.\u003c/p\u003e\n\u003cp\u003eLegend: the arrow in the figures indicates the intersection between the end of the first regression model (ŷ\u003csub\u003e1\u003c/sub\u003e) and the beginning of the second regression model (ŷ\u003csub\u003e2\u003c/sub\u003e).\u003c/p\u003e\n\u003cp\u003e**, *, and \u003csup\u003eo\u003c/sup\u003e indicate significance at the 0.01, 0.05, and 0.10 contents, respectively, according to the \u003cem\u003et\u003c/em\u003e-test.\u003c/p\u003e","description":"","filename":"image7.png","url":"https://assets-eu.researchsquare.com/files/rs-6916464/v1/b67303d1af7dd7a207612e46.png"},{"id":86000906,"identity":"ec28b9e6-9786-49c8-ae1f-bdb51df7c093","added_by":"auto","created_at":"2025-07-04 07:31:54","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":467126,"visible":true,"origin":"","legend":"\u003cp\u003ePotential productivity response curves of cacao trees to the ratio of exchangeable bases Ca\u003csup\u003e2+ \u003c/sup\u003eplus Mg\u003csup\u003e2+ \u003c/sup\u003edivided by K\u003csup\u003e+ \u003c/sup\u003e[(Ca+Mg)/K)] in soil layers of 0-10 cm (A) and 0-20 cm (B), over three years of cultivation, in experimental areas in southern Bahia, Brazil.\u003c/p\u003e\n\u003cp\u003eLegend: the arrow in the figures indicates the intersection between the end of the first regression model (ŷ\u003csub\u003e1\u003c/sub\u003e) and the beginning of the second regression model (ŷ\u003csub\u003e2\u003c/sub\u003e).\u003c/p\u003e\n\u003cp\u003e**, *, and \u003csup\u003eo\u003c/sup\u003e indicate significance at the 0.01, 0.05, and 0.10 contents, respectively, according to the \u003cem\u003et\u003c/em\u003e-test.\u003c/p\u003e","description":"","filename":"image8.png","url":"https://assets-eu.researchsquare.com/files/rs-6916464/v1/ec88c7692a20f6e2438d46ea.png"},{"id":100056587,"identity":"8f6b79c0-fd6f-457e-8440-a9021022afbe","added_by":"auto","created_at":"2026-01-12 14:07:27","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3684090,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6916464/v1/acd9bde0-4116-492e-ab39-c007d09c6e1a.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eBoundary Line Analysis: A Study to Establish Cationic Macronutrient Availability Classes in Cocoa Trees in Brazil\u003c/p\u003e","fulltext":[{"header":"1. INTRODUCTION","content":"\u003cp\u003eCacao (\u003cem\u003eTheobroma cacao\u003c/em\u003e L.) has historically shaped the organizational processes of various cultures and continues to significantly influence important socioeconomic changes in many countries worldwide [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. This is particularly evident in the context of family farming, which encompasses between five to six million small cacao farms worldwide [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAlthough there are regional variations in cacao production, the highest yields are observed in areas with favorable climatic conditions and farming systems that incorporate genetic improvement and new cultivation technologies [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. In this context, successfully managing cacao trees is challenging, and plant nutrition remains one of the most crucial components [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAs an arboreal species, the cacao tree has a deep root system; however, its roots are primarily concentrated in the more superficial layers of the soil. Consequently, the most commonly analyzed layer for soil fertility assessment and recommendations regarding liming and fertilization is the 0‒20 cm depth [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. At depths greater than 20 cm, the biomass of the root system in adult cacao trees is significantly reduced, with the quantity of fine roots in the 0‒10 cm layer potentially being more than twice that found in the 10‒20 cm layer [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Furthermore, correlations between nutrient concentrations in leaves and soil are stronger in the 0‒10 cm layer [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], indicating that this layer is particularly relevant for evaluating nutrient availability for the crop, especially for nutrients with lower mobility in the soil. To ensure proper nutrition and sustained productivity over successive crop cycles, soils designated for cultivation must provide adequate amounts of water and nutrients [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThus, soil chemical analysis is crucial tool for assessing soil fertility. It plays a key role in determining fertilizer doses, aiming to correct nutritional deficiencies and ensure the adequate supply of nutrients. This approach enhances productivity and improves resource use efficiency [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSouza J\u0026uacute;nior et al. [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] examined the classification and interpretation of chemical attributes of soils for cocoa cultivation. They found that much of the existing research on this topic is outdated, and its findings need to be reassessed. This is primarily due to the fact that the genetic materials currently in use have a significantly higher production potential than those employed in previous crops.\u003c/p\u003e \u003cp\u003eCationic macronutrients such as potassium (K\u003csup\u003e+\u003c/sup\u003e), calcium (Ca\u003csup\u003e2+\u003c/sup\u003e), and magnesium (Mg\u003csup\u003e2+\u003c/sup\u003e) are vital for the nutrition of cacao trees. Potassium improves resistance to abiotic stresses and diseases and participates in physiological functions such as enzyme activation and photosynthesis [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Calcium maintains cellular integrity, regulates stomatal opening, and plays a crucial role in nutrient absorption, all of which directly impact plant development and productivity [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Magnesium, an essential component of chlorophyll, is fundamental not only for photosynthesis but also for ATP synthesis and enzyme activation [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Maintaining a balance between Ca\u0026sup2;⁺ and Mg\u0026sup2;⁺ in the soil is fundamental for efficient nutrient uptake, as the ratios of Ca/Mg, Ca/K, Mg/K, and (Ca\u0026thinsp;+\u0026thinsp;Mg)/K influence nutrient availability and overall plant health [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. An imbalance in these ratios can compromise nutrient absorption, affecting physiological processes such as water regulation, enzyme activity, and structural integrity [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. In tropical soils, high rainfall and leaching can result in significant K\u003csup\u003e+\u003c/sup\u003e losses, requiring careful management to prevent deficiencies [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Therefore, the analysis and management of cationic macronutrients and their ratios are essential for optimizing cacao tree productivity and health.\u003c/p\u003e \u003cp\u003eGiven these considerations, new studies are required to update or establish nutrient availability classifications that support more precise fertilization recommendations aligned with the needs of modern cacao cultivars [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn this context, the use of mathematical models to relate soil nutrient content and crop productivity emerges as an innovative approach to address this gap. The Boundary Line (BL) approach, proposed by Webb [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], offers a framework for analyzing the relationship between independent and dependent variables through scatter plots [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. The BL represents the upper boundary portion of the dataset, highlighting the strongest connection within specific value ranges [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. By defining optimal performance within the population, the BL approach allows for the isolation of the effects of a specific production factor on crop productivity, even when other factors vary [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. However, data points below this limit indicate that the dependent variable (productivity) may be influenced by unexamined factors [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn agricultural research, the BL framework enables the analysis of extensive data from commercial and experimental crops cultivated under diverse conditions, with the goal of identifying high-yield populations and their associated nutrient profiles [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTherefore, this study aimed to establish new categories for the availability of exchangeable cationic macronutrients in cacao trees across two soil layers (0\u0026ndash;10 cm and 0\u0026ndash;20 cm) using the BL approach. This framework seeks to refine nutrient availability classifications and improve fertilization recommendations, ensuring optimal cacao tree productivity and economic returns.\u003c/p\u003e"},{"header":"2. METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Setting up and description of experimental conditions\u003c/h2\u003e \u003cp\u003eA database from the Renova Cacau project, established in 2015 and concluded in 2022, was used. This database contains information on cacao bean productivity and soil nutrient contents. The project consists of a full factorial design, with three renewal methods of old cacao plantations and five genetic materials, each replicated twice per experimental area (EA).\u003c/p\u003e \u003cp\u003eThe study was conducted over three consecutive years (2020\u0026ndash;2022), encompassing 15 experimental areas installed in 15 commercial cacao farms, each corresponding to a single EA, located in 11 municipalities in the southern region of Bahia, Brazil. The study area spans latitudes 13\u0026deg;11'35'' S to 15\u0026deg;26'00\" S and longitudes 39\u0026deg;06'36\" W to 39\u0026deg;35'18\" W. The soils in this region exhibit substantial variability, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, which maps the different soil types across the study area and the location of the experimental farms.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eThe three methods of renovation are: R1 \u0026ndash; grafting onto basal shoots of old cacao trees, followed by their gradual removal; R2 \u0026ndash; planting new grafted seedlings and gradually removing the old cacao trees; and R3 \u0026ndash; removing old cacao trees and planting banana plants for temporary shading, followed by planting new grafted seedlings. The five genetic materials were: CCN 51, CP 49, FA 13, PS 1319, SJ 02.\u003c/p\u003e \u003cp\u003eEach EA covered 3,000 m\u0026sup2; and was distributed across the region to encompass a wide diversity of soils cultivated with cacao trees. The plot consists of 10 cacao trees per genotype and renewal method, with five of these trees making up the productive plot (cacao trees whose yields were assessed), totaling 300 cacao trees per EA.\u003c/p\u003e \u003cp\u003eBefore setting up the experiments, soil samples were collected (20 simple samples per composite sample at depths of 0\u0026ndash;20 cm and 20\u0026ndash;40 cm) and analyzed for their chemical properties. These analyses were used to recommend liming and gypsum application for cacao cultivation, following the criteria proposed by Souza J\u0026uacute;nior et al. [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], for cocoa trees, whereby: liming was carried out in the EA that had base saturation (V) of less than 65% in the 0\u0026ndash;20 cm soil layer, with the aim of increasing V to 75%, considering a reaction depth of 5 cm. Gypsum application was carried out in the AE that had aluminum saturation (m) greater than 20% in the 20\u0026ndash;40 cm soil layer, with the aim of reducing m to 20, considering the 30 cm thick reaction layer.\u003c/p\u003e \u003cp\u003eLimestone and gypsum were manually applied to cover the entire soil surface without being incorporated into it. This surface application of limestone motivated the consideration of a shallower reaction depth of 5 cm for liming. By the final year of this study (2022), no additional applications of limestone and/or gypsum had been made.\u003c/p\u003e \u003cp\u003eFor the renewal methods involving seedling planting (R2 and R3), grafting with the five genetic materials was performed on seedlings approximately 75 days after sowing. The cacao seedlings were planted approximately eight months after sowing in cylindrical pits measuring 60 cm in depth and 20 cm in diameter. Each pit was supplemented with 120 g of single superphosphate, 5 g of potassium chloride, 40 g of dolomitic limestone, 15 g of FTE BR-12 (containing 9% Zn, 1.8% B, 0.8% Cu, 2.1% Mn, and 0.1% Mo), and 2 dm\u003csup\u003e3\u003c/sup\u003e of chicken manure [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn the first two years, the plants received establishment fertilization, with the annual dose divided into four applications [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. For R2 and R3, 500 and 800 grams per plant per year of NPK 16-16-16 fertilizer were used in the first and second years, respectively. This latter amount was also applied annually in R1 (renewal method via grafting on basal shoots).\u003c/p\u003e \u003cp\u003eFrom the third year of the experiment onwards, fertilizer doses were tailored for each experimental area (EA) based on the most recent soil analysis of the 0\u0026ndash;10 cm layer, following the recommendations of Souza J\u0026uacute;nior et al. [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. The annual doses of nitrogen (N), phosphorus (P), and potassium (K) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) were divided into four applications, using urea, monoammonium phosphate or triple superphosphate, and potassium chloride as sources.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAnnual fertilization with N, P, and K from the third to the seventh year of the experiment, based on soil P and K contents.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"12\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eYear\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c7\" namest=\"c3\"\u003e \u003cp\u003eP content in the soil\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c12\" namest=\"c8\"\u003e \u003cp\u003eK content in the soil\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c7\" namest=\"c3\"\u003e \u003cp\u003e--------- mg dm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e -----------\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c12\" namest=\"c8\"\u003e \u003cp\u003e-------------- mg dm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e --------------\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;8\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8\u0026ndash;15\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16\u0026ndash;30\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e31\u0026ndash;60\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;60\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;40\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e40\u0026ndash;89\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003e90\u0026ndash;120\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003e121\u0026ndash;180\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;180\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eN, kg ha\u003c/b\u003e\u003csup\u003e\u003cb\u003e\u0026minus;\u0026thinsp;1\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c7\" namest=\"c3\"\u003e \u003cp\u003e\u003cb\u003eP\u003c/b\u003e\u003csub\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sub\u003e\u003cb\u003eO\u003c/b\u003e\u003csub\u003e\u003cb\u003e5\u003c/b\u003e\u003c/sub\u003e, \u003cb\u003ekg ha\u003c/b\u003e\u003csup\u003e\u003cb\u003e\u0026minus;\u0026thinsp;1\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c12\" namest=\"c8\"\u003e \u003cp\u003e\u003cb\u003eK\u003c/b\u003e\u003csub\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sub\u003e\u003cb\u003eO, kg ha\u003c/b\u003e\u003csup\u003e\u003cb\u003e\u0026minus;\u0026thinsp;1\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u0026ordm; e 4\u0026ordm;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e175\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e260\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e190\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e330\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e240\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e170\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u0026ordm; a 7\u0026ordm;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e220\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e290\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e220\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e155\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e370\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e280\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eMicronutrient fertilization was applied once a year with the following doses: 1.0 kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e of B (for EA with B in the soil less than 0.7 mg dm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e); 2.0 kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e of Cu (for EA with Cu in the soil less than 2.0 mg dm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e) and 2.5 or 5.0 kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e of Zn (for EA with Zn in the soil between 3.5 and 5.0 mg dm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e or less than 3.5 mg dm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e of Zn, respectively). The sources used were boric acid and copper and zinc sulphates. These fertilizers were dissolved in water, and the solution was applied and mixed into chicken litter. A volume of 250 cm\u0026sup3; of this chicken litter was then applied to each plant in order to provide the aforementioned micronutrient doses.\u003c/p\u003e \u003cp\u003eDuring the experiment, we took several measures to manage the environment. We used a brush cutter to remove invasive plants, pruned diseased plant material affected by witches' broom disease, and applied registered agricultural pesticides to control pests and diseases as needed.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Database\u003c/h2\u003e \u003cp\u003eData from three years, 2020 to 2022, were used, during which the EA had been established for five to seven years, making the productivity results representative. The study evaluated 13 to 17 EA per year, located across 11 municipalities in southern Bahia, Brazil.\u003c/p\u003e \u003cp\u003eFor soil analyses, six sample plots were considered in each experimental area (three renewal methods and two repetitions), with each sample plot comprising an area covering 50 cacao trees (five clones and 10 cacao trees per clone). Soil samples were collected from the 0\u0026ndash;10 cm and 10\u0026ndash;20 cm layers (20 simple samples per composite sample) over the three years evaluated. The analytical methodologies employed are described by Teixeira et al. [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], with K\u003csup\u003e+\u003c/sup\u003e extracted using Mehlich-1 and Ca\u003csup\u003e2+\u003c/sup\u003e and Mg\u003csup\u003e2+\u003c/sup\u003e extracted using 1.0 mol/L KCl. Additionally, the equimolar ratios of Ca/Mg, Ca/K, Mg/K, and (Ca\u0026thinsp;+\u0026thinsp;Mg)/K were calculated. The nutrient contents and their respective ratios for the 0\u0026ndash;20 cm soil layer were estimated by averaging the values from the 0\u0026ndash;10 cm and 10\u0026ndash;20 cm layers.\u003c/p\u003e \u003cp\u003eFor estimating productivity, the average yield of the useful plot (five cacao trees per clone) was considered, with healthy fruits being harvested and counted monthly. The annual yields, measured in kilograms of dry beans per plant, were calculated by multiplying the total number of fruits harvested each year by the average weight of dry beans per fruit for each clone. The fruit index was determined as the average weight of dry beans per fruit, with 40 fruits per clone evaluated per experimental area per year, after the fresh beans were dried.\u003c/p\u003e \u003cp\u003eData on productivity over three years (considering different ages and climatic conditions), three renewal methods, and five clones were used. To ensure consistency in productivity measurement, we chose to use relative yield (RY). RY is calculated as follows: (RY\u0026thinsp;=\u0026thinsp;average productivity of the useful plot / highest productivity for each clone, renewal method, and year) * 100, expressed as a percentage. Subsequently, the average RY of the five clones forming the soil sample plot was calculated. Finally, for each year, the average relative yield (ARY) was determined using the formula: ARY = (average RY of the useful plots of the five clones / highest average RY for each year) * 100, expressed as a percentage. The dataset consisted of 270 observations, considering the three years of evaluation, three renewal methods, and two repetitions per EA.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Data processing and statistical analysis\u003c/h2\u003e \u003cp\u003eThe cacao bean yield and the nutrient contents in the soil of the respective sample plots were plotted using Microsoft Excel\u0026reg; to generate scatter plots for each nutrient in the two soil layers studied (0\u0026ndash;10 cm and 0\u0026ndash;20 cm). After plotting the scatter plots, we were able to visualize the boundary population within the point cloud that best represented the relationship between ARY (dependent variable) and soil nutrient content (independent variable) across the intervals corresponding to the upper limits or upper boundary region [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTo select the (x,y) pairs corresponding to the upper limit of the relationship between ARY and soil nutrient content or ratios established in the scatter plots, these pairs were obtained manually. Subsequently, using the SigmaPlot 10.1 software, regression models were fitted to relate ARY with the nutrient content or ratios in the soil samples taken from the upper boundary.\u003c/p\u003e \u003cp\u003eThese two variables did not allow for the selection of a single regression model that fit the data satisfactorily. Therefore, we decided to use two models for the same dataset, with the endpoint of the first model (ŷ\u003csub\u003e1\u003c/sub\u003e) serving as the intersection point with the start of the second model (ŷ\u003csub\u003e2\u003c/sub\u003e). The two selected regression models were those that demonstrated the best biological relevance and fit the data well, showing the highest adjusted R\u003csup\u003e2\u003c/sup\u003e and having coefficients significant at the 10% content according to the \u003cem\u003et\u003c/em\u003e-test.\u003c/p\u003e \u003cp\u003eTo define the availability classes for nutrient contents or their relationships in each soil layer, we adapted the criteria presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, adapted from Fernandes [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLimits for establishing nutrient sufficiency ranges in soil based on the average relative yield (ARY) of cacao trees\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSufficiency range\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eARY (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVery low\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;40 a\u0026thinsp;\u0026lt;\u0026thinsp;70\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;70 a\u0026thinsp;\u0026lt;\u0026thinsp;90\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh or adequate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;90 a\u0026thinsp;\u0026le;\u0026thinsp;100\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVery high\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;90 a\u0026thinsp;\u0026lt;\u0026thinsp;100, to the right of the maximum\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTendency to excess\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;70 to \u0026lt;\u0026thinsp;90, to the right of the maximum\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExcess\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;70, to the right of the maximum\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eIn exponential models, it was not possible to mathematically determine the nutrient content in the soil required to achieve the maximum estimated ARY, as these models are asymptotic. In this study, the nutrient content (or the ratio between them) required to achieve maximum ARY was estimated by averaging the values calculated at two points to obtain 90% ARY: one to the left of the maximum point (lower limit of the adequate range) and one to the right of the maximum point (lower limit of the excess trend range) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"3. RESULTS","content":"\u003cp\u003eFor the three macronutrients and their equimolar relationships, broad plateaus were observed, separating the regions of deficiency and excess. This made it impossible to use a single regression model to explain the relationship between nutrient content in the soil (or their ratios) and average relative yield (ARY). Therefore, in all scenarios, two regression models were employed. The endpoint of the first model (ŷ\u003csub\u003e1\u003c/sub\u003e) served as the starting point for the second model (ŷ\u003csub\u003e2\u003c/sub\u003e). In general, regardless of the nutrient or their interactions and soil layer, the selected models demonstrated significant coefficients and strong predictive ability, with most determination coefficients (R\u003csup\u003e2\u003c/sup\u003e) exceeding 0.90.\u003c/p\u003e \u003cp\u003eThe variation of ARY as a function of exchangeable potassium (K\u003csup\u003e+\u003c/sup\u003e) content in the soil showed similarity for both layers (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). Initially, a linear response was observed (ŷ\u003csub\u003e1\u003c/sub\u003e), followed by a quadratic regression (ŷ\u003csub\u003e2\u003c/sub\u003e). During the linear phase, each 1.0 mg dm⁻\u0026sup3; increase in K⁺ resulted in ARY increases of 1.37 percentage points in the 0\u0026ndash;10 cm layer and 1.99 percentage points in the 0\u0026ndash;20 cm layer (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eThe potential productivity response curves of cacao trees to Ca\u003csup\u003e2+\u003c/sup\u003e contents in the 0\u0026ndash;10 cm and 0\u0026ndash;20 cm soil layers are shown in Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB, respectively. In both layers, an initial linear response (ŷ\u003csub\u003e1\u003c/sub\u003e) was observed, indicating that for each 1.0 mmol\u003csub\u003ec\u003c/sub\u003e dm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e of Ca\u003csup\u003e2+\u003c/sup\u003e in the 0\u0026ndash;10 cm and 0\u0026ndash;20 cm soil layers, there are respective increases of 2.46 and 3.47 percentage points in ARY (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). On the other hand, for the second model (ŷ\u003csub\u003e2\u003c/sub\u003e), the best fit was achieved with the exponential model for the 0\u0026ndash;10 cm layer (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA) and the quadratic model for the 0\u0026ndash;20 cm layer (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eThe potential productivity response curves of cacao trees in relation to Mg\u003csup\u003e2+\u003c/sup\u003e contents in the 0\u0026ndash;10 cm and 0\u0026ndash;20 cm soil layers (Figs.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA and \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB) showed similar patterns to those of Ca\u003csup\u003e2+\u003c/sup\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). However, the sequence of the selected models differed, with the first being exponential (ŷ\u003csub\u003e1\u003c/sub\u003e) and the second linear (ŷ\u003csub\u003e2\u003c/sub\u003e). Based on ŷ\u003csub\u003e1\u003c/sub\u003e, it can be estimated that an increase from 3.5 to 7.0 mmol\u003csub\u003ec\u003c/sub\u003e dm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e of Mg\u003csup\u003e2+\u003c/sup\u003e in the 0\u0026ndash;10 cm layer would result in the ARY rising from 25.8\u0026ndash;91.3%, representing a 65.5 percentage point increase (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). A variation in Mg\u0026sup2;⁺ concentration from 2.0 to 6.0 mmol\u003csub\u003ec\u003c/sub\u003e dm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e of Mg\u003csup\u003e2+\u003c/sup\u003ein the 0\u0026ndash;20 cm soil layer would result in an estimated increase in ARY from 21.2\u0026ndash;90.5%, representing a 69.3 percentage point rise (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eThe variation in ARY as a function of the soil Ca/Mg ratio followed a similar trend in both layers (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e), resembling the patterns observed for Ca\u0026sup2;⁺ and Mg\u0026sup2;⁺ (Figs.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, respectively). However, the plateau associated with the Ca/Mg ratio was broader than those of the individual nutrients, suggesting greater flexibility in cacao nutrient balance. The linear regression slope coefficients (ŷ1) indicate that each 0.1 unit increase in the Ca/Mg ratio led to ARY increases of 19.8 percentage points in the 0\u0026ndash;10 cm layer and 10.5 percentage points in the 0\u0026ndash;20 cm layer (Figs.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA and \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eThe variation of ARY in relation to the Ca/K ratio initially showed similar trends in both layers, with the first model (ŷ1) exhibiting an exponential response (Figs.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA and \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB). However, the plateau observed in the 0\u0026ndash;10 cm layer (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA) was broader than that in the 0\u0026ndash;20 cm layer (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB). In both layers, the second model (ŷ2) also followed an exponential pattern (Figs.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA and \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eThe potential response curves of cacao tree productivity to the Mg/K ratio in the 0\u0026ndash;10 cm and 0\u0026ndash;20 cm soil layers (Figs.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA and \u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eB) showed similar patterns in the selected models, both initially exhibiting a linear behavior (ŷ\u003csub\u003e1\u003c/sub\u003e). The slope coefficients of ŷ\u003csub\u003e1\u003c/sub\u003e indicate that for every 0.1 unit increase in the Mg/K ratio in the 0\u0026ndash;10 cm and 0\u0026ndash;20 cm soil layers, there were corresponding increases of 42.3 and 51.0 percentage points in ARY, respectively (Figs.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA and \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB). Regarding the second model (ŷ\u003csub\u003e2\u003c/sub\u003e), the best fit was achieved with the quadratic model for both layers. However, in the excess region for the Mg/K ratio, the 0\u0026ndash;20 cm layer (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eB) showed a more pronounced decrease in ARY compared to the 0\u0026ndash;10 cm layer (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eConsidering the linear models (ŷ\u003csub\u003e1\u003c/sub\u003e), it can be estimated that for each unit increase in the (Ca\u0026thinsp;+\u0026thinsp;Mg)/K ratio in the 0\u0026ndash;10 cm and 0\u0026ndash;20 cm soil layers, there are increases of 20.9 and 22.0 percentage points in ARY, respectively (Figs.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA and \u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eB). For both layers, the second selected model (ŷ\u003csub\u003e2\u003c/sub\u003e) was the exponential one (Figs.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eA and \u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eB).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eDefined availability classes for nutrient contents and their equimolar ratios ranged from \"very low\" to \"excessive\" in both layers (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), according to the criteria in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. However, the \"very low\" availability class was not established for K⁺, Ca\u0026sup2;⁺, Ca/Mg, Ca/K, and Mg/K in the 0\u0026ndash;10 cm layer, nor for Ca\u0026sup2;⁺, Ca/Mg, and Mg/K in the 0\u0026ndash;20 cm layer, as these fell outside the sampling range (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Nonetheless, availability classes for \"tendency to excess\" and \"excess\" were identified across all nutrients and ratios\u0026mdash;novel findings for cacao cultivation.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAvailability classes of exchangeable cationic macronutrients for cacao trees in two soil layers in experimental areas in southern Bahia, Brazil.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAttribute\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnit\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eVery low\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMedium\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eHigh or adequate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eVery high\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eTendency to excess\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eExcess\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eARY\u003csup\u003e1/\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;40\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;40 a\u0026thinsp;\u0026lt;\u0026thinsp;70\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;70 a\u0026thinsp;\u0026lt;\u0026thinsp;90\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;90 a\u0026thinsp;\u0026le;\u0026thinsp;100\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;100 a\u0026thinsp;\u0026ge;\u0026thinsp;90\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;90 a\u0026thinsp;\u0026ge;\u0026thinsp;70\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;70\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"8\" nameend=\"c9\" namest=\"c2\"\u003e \u003cp\u003eLayer 0\u0026ndash;10 cm\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eK\u003c/b\u003e\u003csup\u003e\u003cb\u003e+\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emg dm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e42\u0026ndash;56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e57\u0026ndash;101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e102\u0026ndash;181\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e182\u0026ndash;248\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;248\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCa\u003c/b\u003e\u003csup\u003e\u003cb\u003e2+\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emmol\u003csub\u003ec\u003c/sub\u003e dm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e24\u0026ndash;31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e32\u0026ndash;62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e63\u0026ndash;91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e92\u0026ndash;106\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;106\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMg\u003c/b\u003e\u003csup\u003e\u003cb\u003e2+\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emmol\u003csub\u003ec\u003c/sub\u003e dm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4\u0026ndash;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6\u0026ndash;7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8\u0026ndash;20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e21\u0026ndash;32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e33\u0026ndash;37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;37\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCa/Mg\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;1,4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1,4\u0026thinsp;\u0026minus;\u0026thinsp;1,5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1,6\u0026thinsp;\u0026minus;\u0026thinsp;3,9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4,0\u0026ndash;6,1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6,2\u0026ndash;6,4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;6,4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCa/K\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;6,6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6,6\u0026ndash;8,7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8,8\u0026ndash;22,3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e22,4\u0026ndash;45,5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e45,5\u0026ndash;47,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;47\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMg/K\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;1,8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1,8\u0026thinsp;\u0026minus;\u0026thinsp;2,1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2,2\u0026ndash;8,9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9,0\u0026ndash;16,8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e16,9\u0026ndash;21,9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;21,9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e(Ca\u0026thinsp;+\u0026thinsp;Mg)/K\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7\u0026ndash;8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9\u0026ndash;10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11\u0026ndash;31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e32\u0026ndash;51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e52\u0026ndash;70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;70\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c9\" namest=\"c2\"\u003e \u003cp\u003e\u003cb\u003eLayer 0\u0026ndash;20 cm\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eK\u003c/b\u003e\u003csup\u003e\u003cb\u003e+\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emg dm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22\u0026ndash;37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e38\u0026ndash;47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e48\u0026ndash;94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e95\u0026ndash;164\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e165\u0026ndash;218\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;218\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCa\u003c/b\u003e\u003csup\u003e\u003cb\u003e2+\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emmol\u003csub\u003ec\u003c/sub\u003e dm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e18\u0026ndash;22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e23\u0026ndash;47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e48\u0026ndash;77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e78\u0026ndash;100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;100\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMg\u003c/b\u003e\u003csup\u003e\u003cb\u003e2+\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emmol\u003csub\u003ec\u003c/sub\u003e dm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u0026ndash;4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5\u0026ndash;6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7\u0026ndash;16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e17\u0026ndash;25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e26\u0026ndash;30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCa/Mg\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;1,3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1,3\u0026thinsp;\u0026minus;\u0026thinsp;1,4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1,5\u0026thinsp;\u0026minus;\u0026thinsp;3,8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3,9\u0026thinsp;\u0026minus;\u0026thinsp;6,1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6,2\u0026ndash;6,6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;6,6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCa/K\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;4,9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4,9\u0026thinsp;\u0026minus;\u0026thinsp;6,1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6,2\u0026ndash;7,9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8,0\u0026ndash;21,9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e22,0\u0026ndash;31,2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e31,3\u0026ndash;39,1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;39,2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMg/K\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;1,4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1,4\u0026thinsp;\u0026minus;\u0026thinsp;1,7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1,7\u0026thinsp;\u0026minus;\u0026thinsp;2,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2,1\u0026ndash;13,7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e13,8\u0026ndash;21,1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;21,1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e(Ca\u0026thinsp;+\u0026thinsp;Mg)/K\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6\u0026ndash;7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8\u0026ndash;9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10\u0026ndash;24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e25\u0026ndash;37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e38\u0026ndash;65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;65\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003csup\u003e1/\u003c/sup\u003eARY: average relative yield\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eFor all three nutrients, as expected, their contents in all availability classes were higher in the 0\u0026ndash;10 cm layer compared to the 0\u0026ndash;20 cm layer, reflecting nutrient accumulation in the upper soil layers due to cycling processes.\u003c/p\u003e \u003cp\u003eFor the 0\u0026ndash;20 cm soil layer, the K⁺ content within the adequate availability class ranged from 48 to 94 mg dm⁻\u0026sup3; (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). In contrast, the suitable range for the 0\u0026ndash;10 cm layer was slightly higher, spanning from 57 to 101 mg dm⁻\u0026sup3;, representing an 11% increase compared to the deeper layer.\u003c/p\u003e \u003cp\u003eConsidering Ca\u0026sup2;⁺ concentration, the adequate availability range in the 0\u0026ndash;20 cm soil layer was determined to be between 23 and 47 mmolc dm⁻\u0026sup3; (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Meanwhile, in the 0\u0026ndash;10 cm layer, the appropriate range extended from 32 to 62 mmolc dm⁻\u0026sup3;, averaging 34% higher than the deeper layer.\u003c/p\u003e \u003cp\u003eFor Mg\u0026sup2;⁺, the adequate availability range in the 0\u0026ndash;20 cm soil layer was defined as 7 to 16 mmolc dm⁻\u0026sup3; (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). In the 0\u0026ndash;10 cm layer, however, the suitable range was found to be slightly broader, between 8 and 20 mmolc dm⁻\u0026sup3;.\u003c/p\u003e \u003cp\u003eRegarding nutrient ratios, the optimal Ca/Mg ratio was similar across both layers, ranging from 1.6 to 3.9 in the 0\u0026ndash;10 cm layer and 1.5 to 3.8 in the 0\u0026ndash;20 cm layer (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). These values align with previous recommendations for cacao but confirm a narrower optimal range, likely due to the crop\u0026rsquo;s high magnesium demand.\u003c/p\u003e \u003cp\u003eThe optimal Ca/K ratio was consistent between the layers, varying from 8.8 to 22.3 in the 0\u0026ndash;10 cm layer and 8.0 to 21.9 in the 0\u0026ndash;20 cm layer (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). However, the adequate Mg/K ratio exhibited slight differences between the two layers. The lower limit was similar for both layers, at 2.2 in the 0\u0026ndash;10 cm and 2.0 in the 0\u0026ndash;20 cm layer (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFinally, the optimal (Ca\u0026thinsp;+\u0026thinsp;Mg)/K ratio obtained in this study ranged from 11 to 31 in the 0\u0026ndash;10 cm layer and 10 to 24 in the 0\u0026ndash;20 cm layer (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). These values closely align with previous findings for cacao seedlings but provide an extended range that accommodates field conditions.\u003c/p\u003e"},{"header":"4. DISCUSSION","content":"\u003cp\u003eThe established nutrient availability ranges in this study align with values found in previous literature [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. However, our findings refine these ranges by introducing the \"tendency to excess\" and \"excess\" classes, which had not previously been reported for cacao. This distinction provides a more comprehensive understanding of nutrient dynamics in cacao cultivation, highlighting the importance of monitoring nutrient levels beyond traditional adequate ranges (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe 0\u0026ndash;10 cm soil layer plays a significant role in cacao nutrition due to nutrient cycling, organic matter deposition, and a higher concentration of fine roots compared to deeper layers [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Studies show that nutrient availability in this layer correlates strongly with leaf nutrient content [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], making it important for assessing nutrient uptake, especially for less mobile nutrients like Ca\u0026sup2;⁺ and Mg\u0026sup2;⁺. However, the 0\u0026ndash;20 cm layer remains the standard for soil fertility evaluation and fertilization recommendations [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWhile deeper soil layers contribute to overall nutrient uptake, the analysis of the 0\u0026ndash;10 cm layer provides critical insights that can complement traditional assessments in the 0\u0026ndash;20 cm layer. Previous studies highlight the need for calibration beyond superficial layers (e.g., 20\u0026ndash;40 cm) in perennial crops [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e], but our findings suggest that refining fertilization strategies based on both surface and deeper layers ensures sustained cacao productivity over multiple crop cycles [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe availability ranges for K⁺ in the 0\u0026ndash;10 cm layer were 11% higher than those observed in the 0\u0026ndash;20 cm layer (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). This difference arises from nutrient cycling and organic matter decomposition, as a significant portion of the cacao root system is concentrated in the topsoil, where decomposition of plant residues actively enriches K⁺ content. Additionally, K⁺ has low mobility in soil, which results in its accumulation in surface layers where organic matter is more abundant [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eCompared to previous studies, our findings suggest a lower suitable range for K⁺ in the 0\u0026ndash;20 cm layer than the values recommended by Chepote et al. [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] (\u0026ge;\u0026thinsp;98 mg dm⁻\u0026sup3;) and Souza J\u0026uacute;nior et al. [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] (90\u0026ndash;120 mg dm⁻\u0026sup3;). This lower range indicates that reducing fertilizer applications may be a viable option without negatively impacting cacao productivity, leading to more efficient soil management strategies.\u003c/p\u003e \u003cp\u003eK⁺ plays a crucial role in cacao production and is one of the most limiting nutrients for cacao yield [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Given that K⁺ accumulates heavily in fruit husks and is the second most exported nutrient via cacao seeds [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], maintaining optimal soil levels is essential. However, excessive K⁺ can disrupt Ca\u0026sup2;⁺ and Mg\u0026sup2;⁺ uptake, altering their K/Ca and K/Mg ratios, potentially affecting plant growth [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. This reinforces the importance of defining excess nutrient availability classes as established in this study [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe Ca\u0026sup2;⁺ range in the 0\u0026ndash;20 cm layer was 23 to 47 mmolc dm⁻\u0026sup3;, close to the 30 to 50 mmolc dm⁻\u0026sup3; recommended by Souza J\u0026uacute;nior et al. [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] for cacao cultivation. In deeper layers (0\u0026ndash;40 cm), Oliveira et al. [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e] suggested a sufficient range of 12 to 39 mmolc dm⁻\u0026sup3;, reinforcing the importance of evaluating soil fertility beyond surface layers.\u003c/p\u003e \u003cp\u003eInterestingly, the Ca\u0026sup2;⁺ range in the 0\u0026ndash;10 cm layer was 34% higher than in the 0\u0026ndash;20 cm layer (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Cacao plantations rarely exhibit Ca\u0026sup2;⁺ deficiency compared to other macronutrients [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. However, calcium deficiency can occur in highly weathered and acidic soils, reducing productivity [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Ensuring an adequate Ca\u0026sup2;⁺ supply can significantly enhance bean production, but excessive levels may negatively affect cacao growth, as observed in the \"tendency to excess\" and \"excess\" classes identified in this study [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSimilarly, Mg\u0026sup2;⁺ availability in the 0\u0026ndash;20 cm layer ranged from 7 to 16 mmolc dm⁻\u0026sup3;, consistent with the 10 to 16 mmolc dm⁻\u0026sup3; proposed by Souza J\u0026uacute;nior et al. [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. However, the lower limit in our findings was below the 13 to 16 mmolc dm⁻\u0026sup3; recommended by Malavolta [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. In the 0\u0026ndash;10 cm layer, Mg\u0026sup2;⁺ availability was 22% higher than in the 0\u0026ndash;20 cm layer (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe cacao tree has a high demand for Mg\u0026sup2;⁺ [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], making adequate Mg\u0026sup2;⁺ levels critical for productivity sustainability [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. However, excessive Mg\u0026sup2;⁺ concentrations can interfere with Ca\u0026sup2;⁺ and K⁺ absorption, altering nutrient balance [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. This underscores the importance of monitoring not only individual nutrient concentrations but also their equimolar ratios, particularly for exchangeable cations.\u003c/p\u003e \u003cp\u003eThe balance between Ca\u0026sup2;⁺ and Mg\u0026sup2;⁺ in the soil affects nutrient uptake by plants. While often considered crucial for nutrient availability, some studies suggest that specific Ca/Mg ratios may have limited direct effects on uptake [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Instead, nutrient leaching is driven more by soil properties and environmental conditions than strict nutrient ratios.\u003c/p\u003e \u003cp\u003eRoot absorption mechanisms further influence Ca\u0026sup2;⁺ and Mg\u0026sup2;⁺ uptake. High Mg\u0026sup2;⁺ levels can inhibit Ca\u0026sup2;⁺ absorption and vice versa, due to competitive uptake at the root level [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Physiologically, Ca\u0026sup2;⁺ is critical for cell wall structure and intracellular signaling, while Mg\u0026sup2;⁺ serves as a central component of chlorophyll and enzyme activation [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. An imbalance between these nutrients can disrupt essential physiological functions, impacting plant growth and productivity.\u003c/p\u003e \u003cp\u003eMaintaining a balanced Ca/Mg ratio is essential to prevent nutrient excesses and ensure optimal physiological processes in cacao. This balance, however, varies according to plant species and environmental conditions [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], reinforcing the need for tailored soil management strategies. The optimal Ca/Mg ratio observed in this study ranged from 1.6 to 3.9 in the 0\u0026ndash;10 cm layer and 1.5 to 3.8 in the 0\u0026ndash;20 cm layer (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), values consistent with those suggested by Souza J\u0026uacute;nior et al. [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] (2.0 to 4.0) and Chepote et al. [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] (3.0). Given the high magnesium demand of cacao, it is expected that its optimal Ca/Mg ratio would be narrower, as confirmed in this study.\u003c/p\u003e \u003cp\u003eSimilarly, the Ca/K ratio exhibited consistency across both layers, with values ranging from 8.8 to 22.3 in the 0\u0026ndash;10 cm layer and 8.0 to 21.9 in the 0\u0026ndash;20 cm layer (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). However, the Mg/K ratio showed some variations, particularly in its upper range, despite having similar lower limits\u0026mdash;2.2 for the 0\u0026ndash;10 cm layer and 2.0 for the 0\u0026ndash;20 cm layer (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Importantly, no prior studies specifically suggest appropriate Ca/K or Mg/K ratios for cacao, reinforcing the novelty of our findings.\u003c/p\u003e \u003cp\u003eWorking with cacao seedlings, Morais and Cabala-Rosand [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] established the optimal nutrient ratios for the crop, finding that the best plant growth occurred when the equimolar ratio of (Ca\u0026thinsp;+\u0026thinsp;Mg)/K was between 16 and 24.5. Our results align closely with these findings, revealing ranges of 11 to 31 for the 0\u0026ndash;10 cm layer and 10 to 24 for the 0\u0026ndash;20 cm layer (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). These values reinforce the importance of maintaining balanced nutrient ratios to optimize cacao productivity, particularly considering its high demand for both Ca\u0026sup2;⁺ and Mg\u0026sup2;⁺.\u003c/p\u003e \u003cp\u003eIt is important to highlight that these findings do not suggest that fertilization and liming recommendations should rely exclusively on the 0\u0026ndash;10 cm layer. As reported in previous studies, deeper soil layers (e.g., 20\u0026ndash;40 cm) must also be calibrated in perennial crops like cacao, given their extensive root systems and nutrient uptake beyond surface layers [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Therefore, data from the 0\u0026ndash;10 cm layer should complement, rather than replace, information obtained from the 0\u0026ndash;20 cm layer, ensuring comprehensive nutrient management strategies.\u003c/p\u003e \u003cp\u003eThese findings advance our understanding of nutrient dynamics in cacao cultivation, particularly regarding the optimal Ca/Mg, Ca/K, Mg/K, and (Ca\u0026thinsp;+\u0026thinsp;Mg)/K ratios across different soil layers. Establishing precise reference ranges tailored to cacao\u0026rsquo;s specific nutritional needs will enhance fertilization strategies, improve soil management, and potentially refine recommendations for long-term crop sustainability.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eNutrient availability classes for K\u003csup\u003e+\u003c/sup\u003e, Ca\u003csup\u003e2+\u003c/sup\u003e e Mg\u003csup\u003e2+\u003c/sup\u003e were established for cacao trees, along with the ratios Ca/Mg, Ca/K, Mg/K, and (Ca\u0026thinsp;+\u0026thinsp;Mg)/K, in soil layers of 0\u0026ndash;10 cm and 0\u0026ndash;20 cm. This study provides novel reference values for the \"tendency to excess\" and \"excess\" ranges.\u003c/p\u003e \u003cp\u003eFor the 0\u0026ndash;20 cm soil layer, the suitable availability ranges for Ca\u003csup\u003e2+\u003c/sup\u003e and Mg\u003csup\u003e2+\u003c/sup\u003e are similar to those reported in the literature; however, the suitable ranges for K\u003csup\u003e+\u003c/sup\u003e are lower.\u003c/p\u003e \u003cp\u003eFor the 0\u0026ndash;10 cm soil layer, the ranges identified for the crop are unprecedented and can support the fertilization process, potentially complementing or replacing the information traditionally obtained from the 0\u0026ndash;20 cm layer.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors thank the Brazilian cocoa farmers whose farms were available for this study, the Universidade Estadual de Santa Cruz (UESC), Mondelez International, and the Centro de Inova\u0026ccedil;\u0026atilde;o do Cacau (CIC), under the agreement RD-15540. J.S. is also acknowledged for the CAPES Program \u0026ndash; PDPG-SEMIARIDO (Support for the Brazilian Semiarid Region) postdoctoral project, grant number 88887.809620/2023-00.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work is a result of the partnership between Mondelez International and the Universidade Estadual de Santa Cruz (UESC), under the financial management of the Centro de Inova\u0026ccedil;\u0026atilde;o do Cacau (CIC). It also received support from the CAPES Program \u0026ndash; PDPG-SEMIARIDO (Support for the Brazilian Semiarid Region) under grant number 88887.809620/2023-00.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics Approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable. This study did not involve human participants, human data, or animals.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Publish\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA.O. was responsible for data collection, experimental work, and draft review, contributing to conceptualization and methodology. J.S. was responsible for statistical analysis, data organization, writing the review, and final revisions of the manuscript. J.N. contributed to conceptualization, data curation, methodology, and supervision. D.A. was responsible for funding acquisition and writing review. J.O. contributed to conceptualization, data curation, methodology, and supervision. All authors contributed to the study\u0026apos;s conception and design, commented on previous versions of the manuscript, and have read and approved the final manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eLarrauri OM, Neira DP, Montiel MS. Indicators for the analysis of peasant women\u0026rsquo;s equity and empowerment situations in a sustainability framework: A case study of cocoa production in Ecuador. Sustainability. 2016;8(12):1231. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/su8121231\u003c/span\u003e\u003cspan address=\"10.3390/su8121231\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFoundation WC. World Cocoa Foundation. www.worldcocoafoundation.org. 2014.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRaimi A, Adeleke R, Roopnarin A. Soil fertility challenges and biofertiliser as a viable alternative for increasing smallholder farmer crop productivity in Sub-saharan Africa. Cogent Food Agric. 2017;3(1):1400933. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/23311932.2017.1400933\u003c/span\u003e\u003cspan address=\"10.1080/23311932.2017.1400933\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSouza J\u0026uacute;nior JO, Sodr\u0026eacute; GA, Neves JCL. Fertilidade do solo, corre\u0026ccedil;\u0026atilde;o da acidez e recomenda\u0026ccedil;\u0026atilde;o de aduba\u0026ccedil;\u0026atilde;o para o cacaueiro. In: Souza J\u0026uacute;nior JO. (Org.). Cacau: cultivo, pesquisa e inova\u0026ccedil;\u0026atilde;o. Ilh\u0026eacute;us: Editus, 2018; pp. 333\u0026ndash;377. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.7476/9786586213188\u003c/span\u003e\u003cspan address=\"10.7476/9786586213188\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMarrocos PC, Loureiro GAH, Ara\u0026uacute;jo QR, Sodr\u0026eacute; GA, Ahnert D, Baligar VC. Mineral nutrient ratios and cocoa productivity. J Plant Nutr. 2020;43(15):2368\u0026ndash;82. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/01904167.2020.1771582\u003c/span\u003e\u003cspan address=\"10.1080/01904167.2020.1771582\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBahia BL, Souza Junior JO, Fernandes LV, Neves JC. Reference values and diagnostic ranges to assess the degree of nutritional balance for cocoa plants. Spanish Journal of Agricultural Research, 2021; 19(1):e0801, 2021. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.5424/sjar/2021191-17478\u003c/span\u003e\u003cspan address=\"10.5424/sjar/2021191-17478\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMartins PFS, Augusto SG. Propriedades f\u0026iacute;sicas do solo e sistema radicular do cacaueiro, da pupunheira e do a\u0026ccedil;aizeiro na Amaz\u0026ocirc;nia oriental. Revista Ceres. 2012;59(5):723\u0026ndash;30. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1590/S0034-737X2012000500020\u003c/span\u003e\u003cspan address=\"10.1590/S0034-737X2012000500020\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDantas PAS. Rela\u0026ccedil;\u0026atilde;o entre fertilidade do solo e nutri\u0026ccedil;\u0026atilde;o do cacaueiro no sul da Bahia. Disserta\u0026ccedil;\u0026atilde;o (Mestrado em Produ\u0026ccedil;\u0026atilde;o Vegetal). Ilh\u0026eacute;us: Universidade Estadual de Santa Cruz; 2011. p. 85.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRonquim CC. Conceitos de fertilidade do solo e manejo adequado para as regi\u0026otilde;es tropicais. Campinas: Embrapa Monitoramento por Sat\u0026eacute;lite. 2010. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.infoteca.cnptia.embrapa.br/infoteca/handle/doc/882598\u003c/span\u003e\u003cspan address=\"https://www.infoteca.cnptia.embrapa.br/infoteca/handle/doc/882598\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOliveira FHT, Arruda JA, Silva IF, Alves JC. Amostragem para avalia\u0026ccedil;\u0026atilde;o da fertilidade do solo em fun\u0026ccedil;\u0026atilde;o do instrumento de coleta das amostras e de tipos de preparo do solo. Revista Brasileira de Ci\u0026ecirc;ncia do Solo. 2007;31(5):973\u0026ndash;83. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1590/S0100-06832007000500014\u003c/span\u003e\u003cspan address=\"10.1590/S0100-06832007000500014\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCantarutti R, Barros NF, Martinez H, Novais R. Avalia\u0026ccedil;\u0026atilde;o da fertilidade do solo e recomenda\u0026ccedil;\u0026atilde;o de fertilizantes. In: Novais RF, Alvarez VH, Barros NF, Fontes RLF, Cantarutti RB, Neves JCL, editors. Fertilidade do solo. Vi\u0026ccedil;osa: Sociedade Brasileira de Ci\u0026ecirc;ncia do Solo; 2007. pp. 769\u0026ndash;850.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSouza J\u0026uacute;nior JO, Marrocos PCL, Neves JCL. Diagnose nutricional para o cacaueiro. In: Souza J\u0026uacute;nior JO. (Org.). Cacau: cultivo, pesquisa e inova\u0026ccedil;\u0026atilde;o. Ilh\u0026eacute;us: Editus, 2018; 305\u0026ndash;332. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.7476/9786586213188\u003c/span\u003e\u003cspan address=\"10.7476/9786586213188\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWatanabe K, FukuzawaY, Kawasaki SI, Ueno M, Kawamitsu Y. Effects of potassium chloride and potassium sulfate on sucrose concentration in sugarcane juice under pot conditions. Sugar Tech. 2016;18:258\u0026ndash;65. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s12355-015-0392-z\u003c/span\u003e\u003cspan address=\"10.1007/s12355-015-0392-z\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLubis ST, Putra ETS, Kurniasih B. Anatomical characteristics of cocoa plant roots as affected by the levels of calcium fertilization. Ilmu Pertanian (Agricultural Science). 2022;7(2):68\u0026ndash;74. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/su8121231\u003c/span\u003e\u003cspan address=\"10.3390/su8121231\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAikpokpodion P. Nutrients dynamics in cocoa soils, leaf and beans in Ondo state, Nigeria. J Agricultural Sci. 2010;1(1):1\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/09766898.2010.11884647\u003c/span\u003e\u003cspan address=\"10.1080/09766898.2010.11884647\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMorais FIO, Cabala-Rosand FP. Efeitos dos equil\u0026iacute;brios entre c\u0026aacute;lcio, magn\u0026eacute;sio e pot\u0026aacute;ssio no crescimento do cacaueiro. Revista Theobroma. 1971;1(3):21\u0026ndash;32.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVliet JAV, Giller K. Mineral nutrition of cocoa: a review. Adv Agron. 2017;141:185\u0026ndash;270. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/bs.agron.2016.10.017\u003c/span\u003e\u003cspan address=\"10.1016/bs.agron.2016.10.017\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLima Neto AJ, Natale W, Deus JAL, Rozane DE. Establishment of critical nutrient levels in the soil and leaf of -Prata? banana using the boundary line. Sci Hort. 2024;328:112923. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.scienta.2024.112923\u003c/span\u003e\u003cspan address=\"10.1016/j.scienta.2024.112923\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDuarte IN, Pereira HS, Korndorfer GH. Lixivia\u0026ccedil;\u0026atilde;o de pot\u0026aacute;ssio proveniente do termopot\u0026aacute;ssio. Pesquisa Agropecu\u0026aacute;ria Trop. 2013;43(2):195\u0026ndash;200. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1590/S1983-40632013000200003\u003c/span\u003e\u003cspan address=\"10.1590/S1983-40632013000200003\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYost R, Attanandana T. Predicting and testing site-specific potassium fertilization of maize in soils of the tropics-An example from Thailand. Soil Sci. 2006;171(12):968\u0026ndash;80. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1097/01.ss.0000235846.25450.ee\u003c/span\u003e\u003cspan address=\"10.1097/01.ss.0000235846.25450.ee\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFreire FJ, Silva FC, Carvalho ML, Venegas VHA. Modelagem para otimiza\u0026ccedil;\u0026atilde;o da calagem e aduba\u0026ccedil;\u0026atilde;o na cultura de cana-de-a\u0026ccedil;\u0026uacute;car. Bioenergia em Revista: Di\u0026aacute;logos. 2022;12(2):09\u0026ndash;29. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.alice.cnptia.embrapa.br/alice/handle/doc/1151514\u003c/span\u003e\u003cspan address=\"http://www.alice.cnptia.embrapa.br/alice/handle/doc/1151514\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWebb R. Use of the boundary line in the analysis of biological data. J Hortic Sci. 1972;47(3):309\u0026ndash;19. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/00221589.1972.11514472\u003c/span\u003e\u003cspan address=\"10.1080/00221589.1972.11514472\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWalworth JL, Letzsch WS, Sumner ME. Use of boundary lines in establishing diagnostic norms. Soil Sci Soc Am J. 1986;50:123\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGuimar\u0026atilde;es GGF, Deus JAL, Lima Neto AJ. Boundary line method to update critical soil phosphorus and potassium levels in banana plantations in Santa Catarina. Revista Brasileira de Fruticultura. 2023;45:e\u0026ndash;979. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://dx.doi.org/10.1590/0100-29452023979\u003c/span\u003e\u003cspan address=\"10.1590/0100-29452023979\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchnug E, Heym J, Achwan F. Establishing critical values for soil and plant analysis by means of the boundary line development system (bolides). Commun Soil Sci Plant Anal. 1996;27(13\u0026ndash;14):2739\u0026ndash;48. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/00103629609369736\u003c/span\u003e\u003cspan address=\"10.1080/00103629609369736\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTeixeira PC, Donagemma GK, Fontana A, Teixeira WG. Manual de m\u0026eacute;todos de an\u0026aacute;lise de solo. 3 ed. Bras\u0026iacute;lia: Embrapa, 2017; 573 p. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.embrapa.br/busca-de-publicacoes/-/publicacao/1085209/manual-de-metodos-de-analise-de-solo\u003c/span\u003e\u003cspan address=\"https://www.embrapa.br/busca-de-publicacoes/-/publicacao/1085209/manual-de-metodos-de-analise-de-solo\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFernandes LV. Normas e determina\u0026ccedil;\u0026atilde;o de faixas de sufici\u0026ecirc;ncia para diagnose foliar com base no crescimento relativo de eucalipto. Disserta\u0026ccedil;\u0026atilde;o (Mestrado em Solos e Nutri\u0026ccedil;\u0026atilde;o de Plantas), Universidade Federal de Vi\u0026ccedil;osa, Vi\u0026ccedil;osa. 2010; 83 p. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://locus.ufv.br//handle/123456789/5440\u003c/span\u003e\u003cspan address=\"https://locus.ufv.br//handle/123456789/5440\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChepote RE, Sodr\u0026eacute; GA, Reis EL, Pacheco RG, Marrocos PCL, Valle RR. Recomenda\u0026ccedil;\u0026otilde;es de corretivos e fertilizantes na cultura do cacaueiro no sul da Bahia. Ilh\u0026eacute;us: CEPLAC/CEPEC, 2013; 44 p. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.gov.br/agricultura/pt-br/assuntos/ceplac/publicacoes/boletins-tecnicos-bahia/bt-203.pdf\u003c/span\u003e\u003cspan address=\"https://www.gov.br/agricultura/pt-br/assuntos/ceplac/publicacoes/boletins-tecnicos-bahia/bt-203.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOliveira MG, Partelli FL, Cavalcanti AC, Gontijo I, Vieira HD. Soil patterns and foliar standards for two cocoa clones in the states of Esp\u0026iacute;rito Santo and Bahia, Brazil. Ci\u0026ecirc;ncia Rural. 2019;49(10):e20180686. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1590/0103-8478cr20180686\u003c/span\u003e\u003cspan address=\"10.1590/0103-8478cr20180686\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAjiboye G, Jaiyeoba J, Olaniyan J, Olaiya A. The characteristics and suitability of the soils of some major cocoa growing areas of Nigeria: Tung Iga of Cross River. Agrosearch. 2015;15(1):101\u0026ndash;16.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSodr\u0026eacute; GA, Venturini MT, Ribeiro DO, Marrocos PCL. Extrato da casca do fruto do cacaueiro como fertilizante pot\u0026aacute;ssico no crescimento de mudas de cacaueiro. Revista Brasileira de Fruticultura. 2012;34:881\u0026ndash;7. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1590/S0100-29452012000300030\u003c/span\u003e\u003cspan address=\"10.1590/S0100-29452012000300030\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIpinmoroti R, Aikpokpodion P, Akanbi O. Nutritional assessment of cocoa plots for soil fertility management on some cocoa farms in Nigeria. In: Proceedings of 16th International Cocoa Research Conference Held at Grand Hyatt Hotel, Nusa Dua, Bali, Indonesia. [S.l.: s.n.], 2009; pp. 1481\u0026ndash;1485.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMalavolta E. Manual de calagem e aduba\u0026ccedil;\u0026atilde;o das principais culturas. S\u0026atilde;o Paulo: Agron\u0026ocirc;mica Ceres, 1987; 497 p.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKongor JE, Boecky P, Vermeir P, Van de Walle D, Baert G, Afokwa EO, Dewettinck K. Assessment of soil fertility and quality for improved cocoa production in six cocoa growing regions in Ghana. Agroforest Syst. 2019;93:1455\u0026ndash;67. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s10457-018-0253-3\u003c/span\u003e\u003cspan address=\"10.1007/s10457-018-0253-3\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"discover-soil","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Soil](https://link.springer.com/journal/44378)","snPcode":"44378","submissionUrl":"https://submission.nature.com/new-submission/44378/3","title":"Discover Soil","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Cocoa cultivation, soil sampling, soil fertility, sufficiency ranges, fertilizer recommendations","lastPublishedDoi":"10.21203/rs.3.rs-6916464/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6916464/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eTo ensure high cacao yields, assessing soil fertility is crucial for appropriate amendment and fertilizer use. This study uses the boundary line method to determine new cationic macronutrient availability classes for cacao at two soil depths (0\u0026ndash;10 cm and 0\u0026ndash;20 cm), aiming for accurate fertilization recommendations for modern cacao cultivars. We analyzed a database from 15 experimental areas in southern Bahia, Brazil, collecting soil samples from two depths (0\u0026ndash;10 cm and 0\u0026ndash;20 cm) to measure K\u003csup\u003e+\u003c/sup\u003e, Ca\u003csup\u003e2+\u003c/sup\u003e, Mg\u003csup\u003e2+\u003c/sup\u003e, and their ratios (Ca/Mg, Ca/K, Mg/K, (Ca\u0026thinsp;+\u0026thinsp;Mg)/K). The boundary line analysis helped identify potential response curves for cacao productivity, establishing seven nutrient availability classes from very low to excess. For the 0\u0026ndash;20 cm soil layer, the adequate ranges for Ca\u003csup\u003e2+\u003c/sup\u003e (100\u0026ndash;200 mg dm\u003csup\u003e-3\u003c/sup\u003e) and Mg\u003csup\u003e2+\u003c/sup\u003e (40\u0026ndash;80 mg dm\u003csup\u003e-3\u003c/sup\u003e) matched literature, while the K\u003csup\u003e+\u003c/sup\u003e range (48\u0026ndash;94 mg dm\u003csup\u003e-3\u003c/sup\u003e) was lower, potentially reducing potassium fertilizer use. In the 0\u0026ndash;10 cm soil layer, the ranges were: K\u003csup\u003e+\u003c/sup\u003e (57\u0026ndash;101 mg dm\u003csup\u003e-3\u003c/sup\u003e), Ca\u003csup\u003e2+\u003c/sup\u003e (110\u0026ndash;220 mg dm\u003csup\u003e-3\u003c/sup\u003e), and Mg\u003csup\u003e2+\u003c/sup\u003e (45\u0026ndash;90 mg dm\u003csup\u003e-3\u003c/sup\u003e), indicating higher nutrient accumulation. This study also provided the first specific adequate availability classes for Ca/K (10\u0026ndash;20) and Mg/K (2\u0026ndash;4) ratios. The research established reference values for \"tendency to excess\" and \"excess\" classes, providing a nuanced understanding of nutrient dynamics in cacao cultivation and offering precise fertilization recommendations to enhance productivity. These findings support the fertilization process, complementing or replacing information from the 0\u0026ndash;20 cm layer.\u003c/p\u003e","manuscriptTitle":"Boundary Line Analysis: A Study to Establish Cationic Macronutrient Availability Classes in Cocoa Trees in Brazil","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-04 07:31:49","doi":"10.21203/rs.3.rs-6916464/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-08-08T08:22:13+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-19T21:18:12+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"13238581171434345666273819827116990388","date":"2025-07-17T15:06:15+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"138663473810576197379734268109590329349","date":"2025-07-07T13:17:31+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-03T12:16:39+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"327741825753110972186961749586103044647","date":"2025-07-03T11:39:46+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-07-02T14:25:42+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-06-24T10:19:31+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-06-21T10:48:55+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-06-21T10:48:03+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Soil","date":"2025-06-17T16:45:52+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"discover-soil","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Soil](https://link.springer.com/journal/44378)","snPcode":"44378","submissionUrl":"https://submission.nature.com/new-submission/44378/3","title":"Discover Soil","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"4b89eada-3abb-495a-8c30-88344db5d0c7","owner":[],"postedDate":"July 4th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-01-12T14:34:46+00:00","versionOfRecord":{"articleIdentity":"rs-6916464","link":"https://doi.org/10.1007/s44378-025-00129-1","journal":{"identity":"discover-soil","isVorOnly":false,"title":"Discover Soil"},"publishedOn":"2025-12-05 00:00:00","publishedOnDateReadable":"December 5th, 2025"},"versionCreatedAt":"2025-07-04 07:31:49","video":"","vorDoi":"10.1007/s44378-025-00129-1","vorDoiUrl":"https://doi.org/10.1007/s44378-025-00129-1","workflowStages":[]},"version":"v1","identity":"rs-6916464","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6916464","identity":"rs-6916464","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}