Yield and nutritional quality of calabash tree fruit (Crescentia cujete) in silvopastoral systems: implications for on-field management

Yield and nutritional quality of calabash tree fruit (Crescentia cujete) in silvopastoral systems: implications for on-field management | 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 Yield and nutritional quality of calabash tree fruit (Crescentia cujete) in silvopastoral systems: implications for on-field management Diego A. Rojas-Meza, Eliel González-García, Enrique Murgueitio, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7551294/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 4 You are reading this latest preprint version Abstract The objective was to assess the effect of shade, pruning, and harvest time (seasonality) on the yield and nutritional composition of calabash tree fruit ( Crescentia cujete ). This fruit is used as livestock feed in silvopastoral systems in the dry South American tropics. Two hundred calabash trees were randomly distributed in a split-plot experimental design with four experimental treatments (n = 50) defined as: not shaded-not pruned trees (NSh-NPr), not shaded-pruned trees (NSh-Pr), shaded-not pruned trees (Sh-NPr) and shaded-pruned trees (Sh-Pr). Trees were monitored each 4 months over a 2-years total period and its fruits were classified as ripe, unripe and fallen fruits, whereas ripe fruits were collected and analyzed by its nutritional quality. The shade effect significantly decreased fruit yield. There was a significant interaction shade × time effect. The fruit yield decreased in October 2022 and February, June and October 2023, as well as the average fruit weight at the same harvesting times (except in October 2022). Pruning also showed a significant effect with lower weight and fruit yield. A significant interaction effect of pruning × time was reflected on lower unripe and fallen fruits, both in June and October 2023 (rainy season). Shade, pruning and seasonality did not affect the nutritional quality of fruits. Not pruned calabash tree under sunny conditions has proven to be the best strategy in order to obtain the greatest fruit yield for livestock feeding, ideal for converting conventional herbaceous pastures and deforested landscapes into silvopastoral systems as a sustainable alternative for livestock production in dry tropical savannas. shade pruning tropical tree livestock feed dry season Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Introduction Since their emergence in the 1980s, silvopastoral systems have consistently demonstrated significant productive, environmental, economic, and social benefits by integrating trees and shrubs with cattle grazing (Broom et al. 2013 ; Chará et al. 2019 ; 2024 ; De Macêdo Carvalho et al. 2024 ). Early research in tropical silvopastoral systems, featuring species like Leucaena leucocephala (Chará et al. 2019 ; López-Hernández et al. 2024 ) and more recently Leucaena diversifolia (Molina-Botero et al. 2024 ), Guazuma ulmifolia (Casanova-Lugo et al. 2014 ; Olivares-Pérez et al 2016 ; Hoosbeek et al. 2016 ), and Tithonia diversifolia (Rivera et al. 2024 ; Krüger et al. 2024 ; Bizzuti et al. 2025 ; Lopera-Marín et al. 2025 ), has fueled a growing interest in identifying and assessing novel, locally adapted botanical components for broader adoption (Meek et al. 2022; Visscher et al. 2024 ). This aligns with global initiatives, such as the FAO Globally Important Agricultural Heritage Systems Program - GIAHS (Koohafkan and Altieri 2011 ), which emphasize the critical importance of preserving agricultural systems—including their landscapes, agrobiodiversity, traditional knowledge, and associated cultures—as a pathway to sustainable rural development. The calabash tree ( Crescentia cujete ), an American tree native to the tropics and Caribbean (Arango-Ulloa et al. 2009 ), produces large fleshy fruits (averaging 800 g) with notable nutritional characteristics for animal feed (i.e., 9% crude protein, 10% ether extract, and 4.4 Mcal/kg gross energy). This species is particularly resilient, exhibiting fast growth, resistance to extreme weather fluctuations (intense dry and rainy seasons), and tolerance to moderate acidic and saline soils, allowing for consistent fruit and foliage production (Calle and Murgueitio 2020 ). Recognizing these attributes, local farmers have historically and empirically valorized calabash fruit and foliage for cattle feeding, particularly during periods of forage scarcity like dry seasons (Santoro et al. 2020 ; Botero-Arango et al. 2024 ). This empirical knowledge has spurred researcher interest in evaluating C. cujete in tropical livestock silvopastoral systems. The abundance of functional bio-compounds in foliage, fruits and bark (Alves and Santos 2019 ; Balogun and Sabiu 2021 ; Gonzales et al. 2022 ), and its nutritional composition and positive impact on animal performance (Botero and De La Ossa 2011 ; Rojas-Hernandez et al. 2015 ; Rahmaningsih et al. 2020; Adeyemi et al. 2021 ; Castañeda-Serrano et al. 2023 ) have been reported. While some studies have explored its inclusion in silvopastoral systems as a forage source (Cajas-Giron et al. 2001; Rodriguez and Roncallo 2013; Argüello-Rangel et al. 2019 ; 2020 ) and its fruit yield under wild conditions (Arenas 2004 ; Olivares-Pérez et al 2018 ), there remains a significant lack of comprehensive information regarding its full potential and agronomic performance as a consistent feed resource for tropical cattle within managed silvopastoral systems. For the first time, this study integrates C. cujete as a primary fruit provider for cattle feeding within a large-scale, on-farm silvopastoral system in tropical dry forest, moving beyond its typical dispersed presence in grasslands. This unique experimental setup allowed for the collection of novel and valuable data on the agronomic performance and nutritional composition of its fruits over time, specifically assessing production and quality during both rainy and dry seasons. Furthermore, the research investigates the influence of key management factors such as a shady environment on fruit yield and its nutritional quality. It was also hypothesized that pruning could stimulate both, shaded and full sunlight exposed trees, to produce greater amounts of fruit with better nutritional quality. The findings from this study are crucial for improving good management practices and decision-making processes within emerging sustainable silvopastoral systems, which offer a pathway not only to enhance animal productivity but also to reverse the environmental damage caused by intensive livestock practices, foster the recovery of adapted ancestral species, and enrich ecosystem biodiversity and services. Thus, the objective of this study was to assess the effect of shade, pruning, and harvest time (seasonality) on the yield and nutritional composition of calabash tree fruit ( C. cujete ) in silvopastoral systems in the tropical dry forest. Materials and methods Study area The study was carried out in the tropical dry forest agroecological zone (Holdridge et al., 1971), in the northeast of Colombian Caribbean region under commercial farm conditions i.e., the farm ‘ El Porvenir ', which is located at 80 m.a.s.l. in the municipality of Agustín Codazzi, which belongs to the department of Cesar, (10°05'48''N 73°23'58''W - Fig. 1 ). The soil type was loamy, with average pH of 6.9 and 1.7% of organic matter. Table 1 shows the physical-chemical characteristics of a mixed soil sample obtained from 12 points on the study area. Table 1 Soil characteristics in the study area. Item Value Sand (%) 28 Silt (%) 60 Clay (%) 12 Texture Silt loam pH 6.89 Organic matter (%) 1.74 Carbon (C, %) 1.01 Nitrogen (N, %) 0.09 Phosphorus (ppm) 99.05 Potassium (K, mEq/100g) 0.32 Calcium (Ca, mEq/100g) 10.79 Magnesium (Mg, mEq/100g) 2.42 Effective C.E.C (mEq/100g) 12.10 C/N ratio 11.22 Ca/Mg ratio 4.42 Ca/K ratio 39.55 Mg/K ratio 9.42 Ca + Mg/K ratio 49.00 C.E.C.: Cation Exchange Capacity The total area of the El Porvenir farm is 182 ha, mostly deserved to the extensive livestock production system, on which this study was carried out. Six ha from such surface were stablished since 2010 with a silvopastoral system including a wide presence of calabash tree with a 5 m × 5 m triangular planting frame (~ 2200 trees in the total area). The trees were planted on an herbaceous stratum composed by two native and improved tropical grasses ( Botriochloa pertusa and Megathyrsus maximus cv. Tanzania). In the area, large trees ( Albizia saman , Albizia guachapele , Albizia caribaea , Anacardium excelsum , Enterolobium cyclocarpum and Sterculia apetala ) were also established for many years before starting with the silvopastoral system project. Therefore, in such spatial distribution in the field, some trees were fully exposed whereas others did it under the shade of the accompanying species. Since 2014 to date (including the period of this study), the silvopastoral system has been continuously grazed by a portion of the herd (around 45 beef cows), following a rotational grazing system with the availability of shade, forage and calabash tree fruits, which is normally used as a complement or supplement in the feeding system, either ripe, fresh or ensiled, looking to match nutritional requirements, mainly during the dry season. Furthermore, local climatology was characterized. Information during the period of the study on the maximum, minimum and average temperature, as well as relative humidity and rainfall in the area, was provided by a meteorological station of the Colombian Institute of Hydrology, Meteorology and Environmental Studies (IDEAM), located 18 km distant from the study area at Motilonia research centre of the Colombian Agricultural Research Corporation (Agrosavia). The data were used as a reference for the present study (Fig. 2 ). Hence, the average of total annual rainfall was 1750 mm, average relative humidity was 65%, and average annual temperature was 28.8°C (min: 24.0°C; max: 34.3°C). Experimental design and data collection In order to assess the effect of shade, pruning and harvest time on fruit production and nutritional composition over time, a total and representative sample of 200 calabash trees was carefully selected from the aforementioned silvopastoral system. 100 of those trees were located under the shadow of larger companion trees (45,000 lux), whereas the remaining 100 were directly and fully exposed to sun (not shaded conditions − 115,000 lux). According to its location, the trees were randomly distributed in a split-plot experimental design. Thus, the experimental treatments were defined as the combination of each level of each factor with 50 not shaded – not pruned trees (NSh-NPr), 50 not shaded – pruned trees (NSh-Pr), 50 shaded – not pruned trees (Sh-NPr) and 50 shaded – pruned trees (Sh-Pr). Pruning was carried out using special shears with extension handles (Truper model 18410, Jilotepec, MX), which were disinfected with a solution of 50% commercial ethyl alcohol and 50% tincture of iodine before each tree was pruned. Three types of pruning were combined and carried out on each tree assigned to this practice under the two shade levels: i) sanitary pruning i.e., removing dry branches with sights of evident deterioration or possible disease; ii) production pruning i.e., removing branches located on the main stem (trunk), between the base of the canopy and the ground, as well as smaller secondary and tertiary branches without potential for fruit production located inside the canopy; iii) topping pruning i.e., removing the apex of the branches to remove overlapping and competition for light with branches of neighboring trees. For the most important cuts (trunk and main branches), the points on the trees were directly treated with 58.8% copper oxychloride to prevent further fungal contamination. These pruning guidelines are common in the region. The first pruning of the pre-selected trees was carried out in the first week of April, at the beginning of the first rainy season of the year, and was repeated every 6 months at the beginning of the rains (October 2022, then April and October 2023). Data collection A schematic representation of the sampling points comprised in the experimental design over a 2-year period (from February 2022 to February 2024) is presented in Fig. 3 . Ripe calabash tree fruits were scheduled to be collected periodically (every 4 months). The first was considered as a standardization harvest in February 2022, where all the fruits in the sampling trees were collected in order to allow a standardized maturity and four months age of fruits in the samples collected later in June and October 2022, February, June and October 2023, and February 2024 (Fig. 4 ). At each harvest, ripe fruits were collected, counted and weighed for each tree using a commercial electronic scale (ICM Model ACS-A9T, Medellín, Colombia) with an accuracy of +/- 5 g. In addition, green and fallen fruits were also counted and recorded in the monitoring sheet. During counting and weighing, the ripe fruits harvested from each half of the trees belonging to a same treatment (approximately 25 trees) were stockpiled separately, in order to obtain two stockpiles/treatment/harvest. At the end of each harvest, a representative aliquot of 10% of each stockpile was selected for further nutritional composition analyses. Laboratory analyses After each sampling, fruits were immediately transferred to the facilities of the Laboratorio de Nutrición Animal at the Universidad Francisco de Paula Santander (Ocaña province, Colombia). Prior to opening, fruits on each experimental treatment were weighed on electronic scale, opened using a handsaw and the pulp was removed from the shell, then weighed to be excluded from the initial weight. Pulp from all fruits was manually mixed into a polyethylene bowl until a soft and homogeneous mash was achieved in order to obtain a composed (representative) sample. These mixed samples were arranged in aluminium trays (which were previously weighed and labelled), and placed in a forced air circulation oven (IGS750 Thermo Scientific, Massachusetts, USA) at 55°C for 72 hours for calculating DM content. Subsequently, samples were transferred to the facilities of the Laboratorio de Biotecnología Ruminal at the Universidad Nacional de Colombia (Medellín), then ground in a Willey mill (Thomas Scientific, Swedesboro, NJ, USA) using a 1 mm sieve and analyzed for DM (AOAC, 934.01), Ash (AOAC, 942.05) and ethereal extract (EE) (AOAC, 920.39) according to Lee ( 1995 ). The total nitrogen (TN) was determined by distillation using a Kjeldhal equipment according to Latimer (2023; 2001.11) and crude protein (CP) was calculated as TN × 6.25. Gross energy (GE) was obtained by combusting samples in a calorimeter bomb (Parr Instrument Company Model 1341, Moline, IL, USA). The neutral detergent (NDF) and acid detergent (ADF) fibres were sequentially determined in an ANKOM 200 Fiber Analyzer (ANKOM Technology Corporation, Fairport, NY, USA) according to Van Soest et al. ( 1991 ). Statistical analysis Data on fruit production [harvested fruit (kg), mean weight of fruit (g), as well as harvested, unripe and fallen fruits (units)] were analysed using Linear Mixed Models (LMM) with an ANOVA procedure as a split-plot experimental design where shade, pruning and time effects were considered as fixed effects. The general model adjusted for each variable included the shade effect as a factor with two levels assigned to the main plot and the pruning effect as a factor with two levels assigned to the subplot (tree). The effect of 6 harvests along time (time effect) was assessed using a repeated measurements model and a block factor was considered to eliminate the soil effect. The full model (including repeated measures) was fitted by evaluating the unstructured, compound symmetry and autoregressive covariance model structures for each variable prior the data analysis were performed. Thus, the best model for data analysis was selected based on the lowest BIC criteria. Statistical analyses were performed using the lmer function of R Studio Software version 2024.12.1 (R Core Team, 2024) after testing the mathematical assumptions of the model (Shapiro-Wilk and Barlett test). When dataset did not meet the mathematical assumptions of the model, transformations of the logarithm family were applied. When the ANOVA result was significant, a post hoc LSD test using the emmeans function with Holm multiplicity adjustment was performed to compare the main effect of shade, pruning and time as well as the first-order shade × pruning, shade × time and pruning × time interactions and the second-order shade × pruning × time interaction. A significance level of 5% was used for all tests. In data regarding nutritional quality variables, Principal Components Analysis (PCA) were performed in order to explain possible variation on the fruit composition due to the effect of shade, pruning, harvest or the combination of pruning and shade levels. Results Table 2 shows the main effects and the first and second order interactions of shade, pruning, and harvesting time on calabash tree fruit production in silvopastoral systems. Table 2 Main effects, and first and second order interactions among the evaluated factors (shade, pruning and harvest time) on calabash tree fruit production under silvopastoral system conditions in the El Porvenir farm (located in the tropical dry forest of northern Colombia). Variable Effect, P value Sh Pr T Sh × Pr Sh × T Pr × T Sh × Pr × T Harvested fruit (kg) 0.0043 0.0242 < 0.0001 0.4513 < 0.0001 0.1697 0.1587 Average Fruit weight (g) 0.0264 0.0188 < 0.0001 0.1315 0.0053 0.4774 0.1889 Harvested fruits (units) 0.0031 0.0234 < 0.0001 0.6404 < 0.0001 0.2550 0.3485 Unripe fruits (units) 0.0002 0.0020 < 0.0001 0.1740 < 0.0001 0.0010 0.2660 Fallen fruits (units) 0.0097 0.0003 < 0.0001 0.5369 0.0107 0.0009 0.8696 Sh : shade; Pr : pruning; T : Harvesting time; Sh × Pr : interaction Shade × Pruning; Sh × T : interaction Shade × Time; Pr × T : interaction Pruning × Time; Sh × Pr × T : interaction Shade × Pruning × Time; P < 0.05 was considered as statistically significant. The main effect of shade resulted in a lower yield of fruit in all the assessed categories (number and kg of ripe harvested fruits, average fruit weight, as well as number of unripe and fallen fruits) when compared to those calabash tree located under sunny conditions. A significant interaction effect of shade × time was observed with a significant decrease in the number and kg of ripe fruit in calabash tree harvested in October 2022 and February, June and October 2023 (Fig. 4 A and B). Similarly, shaded trees showed lower average fruit weight at the same harvesting times through 2023 (Fig. 4 C). Interaction shade × time effect was also expressed with a significant decrease in the number of unripe fruits in all harvesting times except October 2022 (Fig. 5 A) and a lower number of fallen fruits in June 2022, October 2023 and February 2024 (Fig. 5 B). Lower number and kg of ripe harvested fruits/tree and average fruit weight as a consequence of the main effect of pruning in calabash tree was observed (Fig. 6 ) with no significant effect on the number of unripe and fallen fruits. Additionally, an interaction effect of pruning × time showed a decrease in the number of unripe and fallen fruits in pruned calabash trees in June and October 2023 (Fig. 7 ). In the context of harvesting time (seasonality), calabash trees were found to be generally more productive during the rainy season (June and October) compared to those harvested during the dry season (February). There was no interaction effect of shade × pruning and neither second order interaction effect of shade × pruning × time on any of the yield fruit assessed variables (P > 0.05), nor did any of the assessed factors modified the nutritional quality of the calabash tree fruits (Fig. 8 ). Detailed nutritional composition of calabash tree fruit in each experimental treatment is showed in Table 3 . Table 3 Nutritional composition of calabash tree fruit according with the experimental treatment (n = 12) Variable Treatment NSh-NPr NSh-Pr Sh-NPr Sh-Pr %DM 21.4 ± 1.6 21.0 ± 1.9 19.3 ± 3.2 19.1 ± 1.7 %NDF 22.2 ± 2.9 21.6 ± 2.5 22.4 ± 2.7 21.9 ± 3.0 %ADF 15.6 ± 2.3 15.0 ± 2.0 15.6 ± 1.9 14.8 ± 1.9 %CP 7.7 ± 0.9 7.8 ± 0.8 8.7 ± 1.1 9.0 ± 1.0 %EE 9.2 ± 1.3 8.4 ± 2.4 8.5 ± 2.1 9.3 ± 2.2 %Ash 5.0 ± 0.6 5.2 ± 0.6 5.0 ± 0.6 5.0 ± 0.6 GE (Mcal/kg of DM) 4.3 ± 0.1 4.3 ± 0.1 4.2 ± 0.1 4.3 ± 0.1 NSh-NPr : Not shaded – not pruned trees treatment; NSh-Pr : Not shaded – pruned trees treatment; Sh-NPr : Shaded – not pruned trees treatment; Sh-Pr : Shaded – pruned trees treatment; Discussion Calabash tree fruit yield Monitoring of calabash tree over a two consecutive years period showed a significant effect of shade and pruning expressed in a lower fruit yield. Additionally, time effect was mainly related to variations in rainfall patterns in this study with the higher fruit yield showed June and October (rainy season), with rain as the most determining factor of seasonality in the tropic (Vega-Ramos et al. 2024 ). Hence, interaction effect of shade × time on all the assessed variable revealed a negative effect of shade and lack of rains on the number, kg and average weight of ripe harvested fruits, as well as on the count of unripe and fallen fruits during the dry season. According to Lambers et al. ( 2008 ), Valverde-Rodriguez et al. (2019b) and Basave-Villalobos et al. ( 2022 ), a decrease in luminosity (irradiance) significantly reduces photosynthetic activity (expressed as the CO 2 assimilation rate), which directly affects energy availability and the supply of inputs for growth (in young plants) and flowering and fruiting (reproductive phase in mature plants). At the same time, the author states that, under these circumstances, a significant reduction in water supply could accentuate these effects, further reducing the growth rate or fruit production in either case (young or mature plants, respectively). This argument could explain the reduction in the number, kilograms and the average weight of the fruits harvested in our study. This could be interpreted as an adaptive mechanism of C. cujete which, under lower light exposure and water availability conditions, is probably forced to prioritize the use of smaller amounts of energy and bio-inputs on the maintenance of vital functions, thus partially compromising flowering and fruit production as a consequence of a lower photosynthetic rate (Givnish, 1988 ; Piña and Arboleda, 2010 ; Nina Junior et al., 2024 ; Patil et al., 2024 ). Thus, the sustained effect of shady environment was expressed in a lower fruits yield over time, compared to trees located under full sunshine exposure (Fig. 4 ). However, these effects were accentuated in both shaded and not shaded trees by the water restriction pulses corresponding to the dry season months (February 2023/2024; Figs. 2 and 4 ). The effect of time (seasonality) was notable either at intra and interannual levels. It was reflected as a lower number of harvested fruits in the period of lowest accumulated rainfall within each monitoring year (February 2023 and February 2024), and when comparing the 2nd monitoring year (30% less rainy) to the first one (Figs. 2 and 4 ). Finally, the fact that calabash tree fruit is mostly composed by water (~ 80% of its fresh matter; Table 3 ) could partially explain why a drastic and prolonged reduction on rainfall, although did not mean a risk for plant survival, could dramatically affect fruit yield, both in shaded and not shaded trees during the dry season (Galindo et al., 2017 ; Torrecillas et al., 2018 ; Fig. 4 ). The interaction shade × time effect due to the decrease in rainfall over second year (30% less rainy respect to the first year - Fig. 2 ) would also be the cause of the significant decrease in the average fruit weight/tree (Fig. 4 C) as previously discussed for number, kg and weight of ripe harvested fruits. Considering average fruit weight as the weight and number of ripe harvested fruits ratio (quotient), it behaves according the number and kg of ripe harvested fruits over time. The lower fruit yield in calabash trees under light restriction was reflected in lower unripe fruits over time (Figs. 4 and 5 ). Same behavior was observed during the second monitoring year with higher unripe fruits in shaded trees, which could be influenced by the overall increase of the total unripe fruits in the same period in both, shaded and not shaded trees (Fig. 5 ). The lower rainfall over the second year could have slowed down the ripening process (Lambers et al. 2008 ; Galindo et al. 2017 ; Valverde-Rodríguez et al. 2019a ), explaining the higher number of unripe fruits. This also can be evidenced in the deleterious decrease on the total ripe harvested fruits whatever the treatment (Fig. 4 ) over this period. In stressful situations such as drought, plants drop many unripe fruits as a physiological mechanism to ensure that the remaining fruits the plant is able to sustain reach maturity (Fernandes et al., 2018 ; De Souza et al., 2025 ). The dramatic increase in the number of fallen fruits over the second year could be explained due to the reduction in the rainfall, mainly in the dry season, which recorded accumulated rainfall of 317.6 mm and a total of 636 fallen fruits in the second-year vs 642.6 mm and 16 fallen fruits in the same month in the first year (Fig. 2 ), summed to the increase of squirrels ( Sciuridae ) population from April 2023, due to a nearby deforestation (Fig. 5 ). Contrary to our hypothesis, agronomical practice of pruning did not stimulate an increase in the ripe harvested fruit yield in calabash tree as in other tropical fruit trees (i.e., avocado, mango, guava). Changes in canopy of pruned trees, such as the regrowth of new branches and leaves precisely at the points where pruning was performed were observed through the months immediately following pruning. This would lead us to speculate that the potential surplus energy and nutrients not used to maintain the biomass removed from the canopy may have been used to replace the branches and leaves removed by pruning, instead of increasing the number or average weight of fruits, finally leading to the decrease on fruit yield, contrary to expected (Fig. 6 ). Similarly, pruning reduced the number of unripe and fallen fruits over time, with significant differences in June and October 2023 during the rainy season (Fig. 7 ). This behavior, similarly to interaction shade × time for these variables, could be influenced by the reduction on fruits yield due to pruning, that together to the alterations in the fruit yield pattern related to both decrease on rainfall or increased squirrel attacks over second monitoring year, could be statistically expressed in these differences, as previously discussed. Nutritional quality of calabash tree fruits Principal component analysis of calabash tree fruit nutritional quality did not show relevant differences due to the experimental treatments (Fig. 8 ; Table 3 ). The main limitation of this study was the chemical analysis of fruit nutritional composition from composed samples by treatment. This prevented us from achieving a significant number of replicates per treatment/harvest time, substantially affecting the power of the inferential statistical test. This led us to opt for the PCA method, which would allow us to demonstrate possible differences in composition and explain the possible relationship between the study factors and the fruit nutritional quality variables (Fig. 8 ). Future studies with a larger number of independent replicates that allows for inferential analysis to evaluate the effect of the factors on fruit composition with greater statistical power are recommended. Several studies assessing the effect of shade (Rozendaal et al. 2006 ; Poorter et al. 2019 ; Elshahat et al. 2025 ) and tree pruning (Marini 2009 ; Adhikari and Kandel 2015 ; Arredondo et al. 2022 ; Ali et al. 2025 ; Singh et al. 2025 ) on fruit yield, size and nutritional composition in citrus, fig, pitaya, guava and other tropical fruit trees, reports that changes on fruit yield and quality did not depend solely on the presence or absence of these factors (as was the case in the present study), but are influenced by the intensity and duration (in the case of shade) or the site, moment and frequency of its application (in the case of pruning). Likewise, its effects can vary as a result of its interaction with other external factors such as the edaphoclimatic conditions of the study area (Gratani 2014 ), planting density (Chithiraichelvan et al. 2017 ; Haque and Sakimin 2022 ; Ladon et al. 2024 ), as well as the species and its own phenological cycle, canopy architecture, pollinator activity, among others factors related to the plant species per se . Thereby, the results obtained in this pioneering study, far from searching definitive conclusions, search for significant contribution to establishing the interest and basis of what we consider an extensive line of research on a species that provides numerous attributes to different cultures spread across the vast tropical region of the world. Conclusions The presence of shade significantly reduced the amount and weight of calabash tree fruit harvested over time. These effects were more pronounced during the dry season. Therefore, shade is not recommended for calabash trees in silvopastoral systems alongside larger trees when the aim is adding value from fruit production as a feed resource for livestock. A decrease in the size and fruit yield due to shade also has negative implications related to harvest efficiency, since this increases the number of trees, time and labor required compared to not shaded trees. As an agronomic management practice, pruning did not improve fruit production and nutritional quality as expected; therefore, under the conditions of this study it is not recommended. The nutritional quality of calabash tree fruits remained unchanged due to shade, pruning or to the seasonal weather fluctuations typical of tropical dry forests. Based on these findings, not pruned trees located under total sunny conditions are considered the best strategies in order to obtain the greatest fruit production. Hence, the ability of calabash tree to yield more fruit in open spaces (with no shade) with agronomical practice of pruning being not required, make it ideal for converting herbaceous pastures and deforested landscapes into silvopastoral systems as a feasible sustainable livestock alternative in dry tropical savannas. The productive kinetics of calabash trees over time revealed a significant reduction on fruit yield during the dry season. Therefore, calabash tree response to complementary management practices such as fertilization based on the own manure utilization, strategic irrigation and fruit conservation techniques should be evaluated in future studies in order to improve productivity and biological activity of this systems during the dry season. Our results highlight the potential of the calabash tree as a source of livestock feed in silvopastoral systems, particularly during the dry season when the nutritional quality of forages as the main feed resource is affected by water restrictions. Declarations Founding statement : Ministry of Science, Technology and Innovation (MinCiencias) from Republic of Colombia – Doctoral scholarship abroad program – call N° 885 Universidad Nacional de Colombia – UNAL (Medellín headquarters) – Laboratorio de Biotecnología Ruminal – Colombia. Acknowledgments: We would like to thank José Félix Lafaurie and the staff of 'El Porvenir' farm for granting us access to the experimental areas and for providing all the assistance necessary to carry out activities during the experimental phase in the field. We would like to thank the Department of Animal Production and Animal Nutrition Laboratory at the Universidad Francisco de Paula Santander Ocaña for allowing us to use their laboratory facilities and equipment to dry and prepare samples for subsequent analysis. Author contributions Diego A. Rojas-Meza: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Validation, Visualization, Writing – original draft. Eliel Gonzalez-García: Conceptualization, Methodology, Supervision, Funding acquisition, Visualization, Review and editing. Enrique Murgueitio: Conceptualization. Guillermo Antonio Correa Londoño: Data curation, Formal analysis, Software. Milton Rivera Rojas: Methodology. Leonardo Manzano García: Conceptualization, Funding acquisition, Resources. Jordi Bartolomé Filella: Conceptualization, Methodology, Supervision, Visualization, Review and editing. Data availability: No datasets were generated during the current study Conflict of Interest The authors declare that they have no conflict of interest. References Adeyemi KD, Audu S, Oloke JA, et al (2021) Influence of Crescentia cujete and Launaea taraxacifolia leaves on growth, immune indices, gut microbiota, blood chemistry, carcass, and meat quality in broiler chickens. Trop Anim Health Prod 53:365. https://doi.org/10.1007/s11250-021-02812-1 Adhikari S, Kandel TP (2015) Effect of Time and Level of Pruning on Vegetative Growth, Flowering, Yield, and Quality of Guava. International Journal of Fruit Science 15:290–301. https://doi.org/10.1080/15538362.2015.1015762 Ali M, Akram MM, Iqbal A, et al (2025) Standardization of Pruning in Dense, High Dense, and Ultra-High Dense Psidium guajava L. Orchards under Drip Irrigation. 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PLoS ONE 19:e0309510. https://doi.org/10.1371/journal.pone.0309510 Visscher AM, Meli P, Fonte SJ, et al (2024) Agroforestry enhances biological activity, diversity and soil-based ecosystem functions in mountain agroecosystems of Latin America: A meta‐analysis. Global Change Biology 30:e17036. https://doi.org/10.1111/gcb.17036 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviewers invited by journal 30 Sep, 2025 Editor assigned by journal 15 Sep, 2025 Submission checks completed at journal 12 Sep, 2025 First submitted to journal 06 Sep, 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-7551294","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":515460577,"identity":"681133fc-c7d3-4a87-a57a-4cb4091e7deb","order_by":0,"name":"Diego A. 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Location of the Caribbean region in northern Colombia. \u003cstrong\u003eB\u003c/strong\u003e. In orange: area corresponding to the tropical dry forest biome in the Caribbean region. \u0026nbsp;Location of the Farm \u003cem\u003eEl Porvenir\u003c/em\u003e (study area). Adapted from Instituto Geográfico Agustín Codazzi de Colombia (IGAC, et al., 2007)\u003c/p\u003e","description":"","filename":"Picture1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7551294/v1/ae3d963298eba412eee84abf.jpg"},{"id":91451858,"identity":"2a4cefff-28d2-4016-832f-54fc4098d1f0","added_by":"auto","created_at":"2025-09-16 15:38:14","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":91887,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eBars: \u003c/strong\u003eMonthly\u003cstrong\u003e \u003c/strong\u003eaccumulate rainfall; \u003cstrong\u003eLines: \u003c/strong\u003eMonthly mean of maximum (upper), minimum (below) and average (middle) air temperature at the study zone; \u003cstrong\u003eDotted vertical line: \u003c/strong\u003eTemporal division between first and second monitoring year; \u003cstrong\u003eIn blue: \u003c/strong\u003eAccumulate rainfall at the moment of each fruit harvesting. (Data taken from the meteorological station of the Colombian Institute of Hydrology, Meteorology and Environmental Studies (IDEAM), at Motilonia research centre of the Colombian Agricultural Research Corporation (Agrosavia)\u003c/p\u003e","description":"","filename":"Picture2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7551294/v1/f9a44c1cae67b6eaac9040e4.jpg"},{"id":91453280,"identity":"537767b6-454a-433c-9728-d4f1d30a8429","added_by":"auto","created_at":"2025-09-16 15:46:14","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":26131,"visible":true,"origin":"","legend":"\u003cp\u003eDiagram representing the schedule followed for the measurements and/or agronomic interventions (fruit harvest and counting, calabash tree pruning) over time (Feb/22 to Feb/24)\u003c/p\u003e","description":"","filename":"Picture3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7551294/v1/fd4987724c75a8fce720214e.jpg"},{"id":91453281,"identity":"cc62512b-4f20-4132-b4e0-01f110c28955","added_by":"auto","created_at":"2025-09-16 15:46:14","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":242628,"visible":true,"origin":"","legend":"\u003cp\u003eInteraction effect of two levels of shade [not shaded (NSh) and shaded (Sh)] × time on the progression of: \u003cstrong\u003eA.\u003c/strong\u003e number of ripe harvested fruits/tree (\u003cem\u003eP \u003c/em\u003e\u0026lt;0.0001); \u003cstrong\u003eB. \u003c/strong\u003ekg of ripe harvested fruits/tree (\u003cem\u003eP \u003c/em\u003e\u0026lt; 0.0001) and \u003cstrong\u003eC.\u003c/strong\u003e average fruit weight/tree (\u003cem\u003eP \u003c/em\u003e= 0.0053). Statistical significance code of post-hoc test results: *** (\u003cem\u003eP value \u0026lt;\u003c/em\u003e0.001); ** (\u003cem\u003eP value between \u003c/em\u003e0.001 - 0.01); * (\u003cem\u003eP value between \u003c/em\u003e0.01 - 0.05)\u003c/p\u003e","description":"","filename":"Picture4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7551294/v1/c7add12b56fa3cefbe3cdb74.jpg"},{"id":91453287,"identity":"dc32d278-b901-4f7e-acd9-a37a18e6cc90","added_by":"auto","created_at":"2025-09-16 15:46:14","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":157424,"visible":true,"origin":"","legend":"\u003cp\u003eInteraction effect of two levels of shade [not shaded (NSh) and shaded (Sh)] × time on the progression of: \u003cstrong\u003eA. \u003c/strong\u003enumber of unripe fruits/tree (\u003cem\u003eP \u003c/em\u003e\u0026lt; 0.0001) and \u003cstrong\u003eB. \u003c/strong\u003enumber of fallen fruits/tree (\u003cem\u003eP\u003c/em\u003e= 0.0107). Statistical significance code of post-hoc test results: \u0026nbsp;*** (\u003cem\u003eP value \u0026lt;\u003c/em\u003e0.001); ** (\u003cem\u003eP value between \u003c/em\u003e0.001 - 0.01); * (\u003cem\u003eP value between \u003c/em\u003e0.01 - 0.05)\u003c/p\u003e","description":"","filename":"Picture5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7551294/v1/4194622b712d2839697df661.jpg"},{"id":91451864,"identity":"396ad77d-bcc2-4221-8e5d-2165c1255f1b","added_by":"auto","created_at":"2025-09-16 15:38:14","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":88880,"visible":true,"origin":"","legend":"\u003cp\u003eMain effect of two levels of pruning [not pruned (NPr) and pruned (Pr) trees] on: A. number of ripe harvested fruits/tree (P = 0.0234) and kg of ripe harvested fruit/tree (P = 0.0242); B. average fruit weight/tree (P = 0.0188); *: P value of post-hoc test between 0.01 - 0.05\u003c/p\u003e","description":"","filename":"Picture6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7551294/v1/b2cf0b9d5f3e7dcf84812670.jpg"},{"id":91454206,"identity":"b4b3c870-b959-498a-98e7-af13f132f212","added_by":"auto","created_at":"2025-09-16 15:54:14","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":148632,"visible":true,"origin":"","legend":"\u003cp\u003eInteraction effect of two levels of pruning [not pruned (NPr) and pruned (Pr)] × time on the progression of: \u003cstrong\u003eA.\u003c/strong\u003e number of unripe fruits/tree (\u003cem\u003eP \u003c/em\u003e= 0.0010) and \u003cstrong\u003eB. \u003c/strong\u003enumber of\u003cstrong\u003e \u003c/strong\u003efallen fruits/tree (\u003cem\u003eP =\u003c/em\u003e 0.0009). Statistical significance code of post-hoc test results: *** (\u003cem\u003eP value \u0026lt;\u003c/em\u003e0.001); ** (\u003cem\u003eP value between \u003c/em\u003e0.001 - 0.01); * (\u003cem\u003eP value between \u003c/em\u003e0.01 - 0.05)\u003c/p\u003e","description":"","filename":"Picture7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7551294/v1/af111cbbd75e408ad65b9014.jpg"},{"id":91453283,"identity":"c2b17193-34cd-4859-9ea9-239a563354e8","added_by":"auto","created_at":"2025-09-16 15:46:14","extension":"jpg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":23960,"visible":true,"origin":"","legend":"\u003cp\u003ePCA-Biplot score of all samples in experimental treatments compound by the four combinations of shade and pruning levels\u003c/p\u003e","description":"","filename":"Picture8.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7551294/v1/85a69c0f5e7c35b589b4ab98.jpg"},{"id":91816989,"identity":"0941da79-f976-47e4-9539-edadfe1dda19","added_by":"auto","created_at":"2025-09-22 06:53:15","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1692178,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7551294/v1/5b831abe-5197-4ce3-9445-6b5fe294c491.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Yield and nutritional quality of calabash tree fruit (Crescentia cujete) in silvopastoral systems: implications for on-field management","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSince their emergence in the 1980s, silvopastoral systems have consistently demonstrated significant productive, environmental, economic, and social benefits by integrating trees and shrubs with cattle grazing (Broom et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Char\u0026aacute; et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; De Mac\u0026ecirc;do Carvalho et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Early research in tropical silvopastoral systems, featuring species like \u003cem\u003eLeucaena leucocephala\u003c/em\u003e (Char\u0026aacute; et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; L\u0026oacute;pez-Hern\u0026aacute;ndez et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) and more recently \u003cem\u003eLeucaena diversifolia\u003c/em\u003e (Molina-Botero et al. \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), \u003cem\u003eGuazuma ulmifolia\u003c/em\u003e (Casanova-Lugo et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Olivares-P\u0026eacute;rez et al \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Hoosbeek et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), and \u003cem\u003eTithonia diversifolia\u003c/em\u003e (Rivera et al. \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Kr\u0026uuml;ger et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Bizzuti et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Lopera-Mar\u0026iacute;n et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2025\u003c/span\u003e), has fueled a growing interest in identifying and assessing novel, locally adapted botanical components for broader adoption (Meek et al. 2022; Visscher et al. \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). This aligns with global initiatives, such as the FAO Globally Important Agricultural Heritage Systems Program - GIAHS (Koohafkan and Altieri \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), which emphasize the critical importance of preserving agricultural systems\u0026mdash;including their landscapes, agrobiodiversity, traditional knowledge, and associated cultures\u0026mdash;as a pathway to sustainable rural development.\u003c/p\u003e\u003cp\u003eThe calabash tree (\u003cem\u003eCrescentia cujete\u003c/em\u003e), an American tree native to the tropics and Caribbean (Arango-Ulloa et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2009\u003c/span\u003e), produces large fleshy fruits (averaging 800 g) with notable nutritional characteristics for animal feed (i.e., 9% crude protein, 10% ether extract, and 4.4 Mcal/kg gross energy). This species is particularly resilient, exhibiting fast growth, resistance to extreme weather fluctuations (intense dry and rainy seasons), and tolerance to moderate acidic and saline soils, allowing for consistent fruit and foliage production (Calle and Murgueitio \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Recognizing these attributes, local farmers have historically and empirically valorized calabash fruit and foliage for cattle feeding, particularly during periods of forage scarcity like dry seasons (Santoro et al. \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Botero-Arango et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThis empirical knowledge has spurred researcher interest in evaluating \u003cem\u003eC. cujete\u003c/em\u003e in tropical livestock silvopastoral systems. The abundance of functional bio-compounds in foliage, fruits and bark (Alves and Santos \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Balogun and Sabiu \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Gonzales et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), and its nutritional composition and positive impact on animal performance (Botero and De La Ossa \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Rojas-Hernandez et al. \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Rahmaningsih et al. 2020; Adeyemi et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Casta\u0026ntilde;eda-Serrano et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) have been reported. While some studies have explored its inclusion in silvopastoral systems as a forage source (Cajas-Giron et al. 2001; Rodriguez and Roncallo 2013; Arg\u0026uuml;ello-Rangel et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) and its fruit yield under wild conditions (Arenas \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Olivares-P\u0026eacute;rez et al \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), there remains a significant lack of comprehensive information regarding its full potential and agronomic performance as a consistent feed resource for tropical cattle within managed silvopastoral systems.\u003c/p\u003e\u003cp\u003eFor the first time, this study integrates \u003cem\u003eC. cujete\u003c/em\u003e as a primary fruit provider for cattle feeding within a large-scale, on-farm silvopastoral system in tropical dry forest, moving beyond its typical dispersed presence in grasslands. This unique experimental setup allowed for the collection of novel and valuable data on the agronomic performance and nutritional composition of its fruits over time, specifically assessing production and quality during both rainy and dry seasons. Furthermore, the research investigates the influence of key management factors such as a shady environment on fruit yield and its nutritional quality. It was also hypothesized that pruning could stimulate both, shaded and full sunlight exposed trees, to produce greater amounts of fruit with better nutritional quality.\u003c/p\u003e\u003cp\u003eThe findings from this study are crucial for improving good management practices and decision-making processes within emerging sustainable silvopastoral systems, which offer a pathway not only to enhance animal productivity but also to reverse the environmental damage caused by intensive livestock practices, foster the recovery of adapted ancestral species, and enrich ecosystem biodiversity and services. Thus, the objective of this study was to assess the effect of shade, pruning, and harvest time (seasonality) on the yield and nutritional composition of calabash tree fruit (\u003cem\u003eC. cujete\u003c/em\u003e) in silvopastoral systems in the tropical dry forest.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy area\u003c/h2\u003e\u003cp\u003eThe study was carried out in the tropical dry forest agroecological zone (Holdridge et al., 1971), in the northeast of Colombian Caribbean region under commercial farm conditions i.e., the farm \u0026lsquo;\u003cem\u003eEl Porvenir\u003c/em\u003e', which is located at 80 m.a.s.l. in the municipality of Agust\u0026iacute;n Codazzi, which belongs to the department of Cesar, (10\u0026deg;05'48''N 73\u0026deg;23'58''W - Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The soil type was loamy, with average pH of 6.9 and 1.7% of organic matter. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows the physical-chemical characteristics of a mixed soil sample obtained from 12 points on the study area.\u003c/p\u003e\u003cp\u003e\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\u003eSoil characteristics in the study area.\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\u003eItem\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eValue\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSand (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e28\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSilt (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e60\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eClay (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTexture\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSilt loam\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003epH\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6.89\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOrganic matter (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.74\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCarbon (C, %)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNitrogen (N, %)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.09\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePhosphorus (ppm)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e99.05\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePotassium (K, mEq/100g)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.32\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCalcium (Ca, mEq/100g)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e10.79\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMagnesium (Mg, mEq/100g)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.42\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEffective C.E.C (mEq/100g)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12.10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eC/N ratio\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e11.22\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCa/Mg ratio\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.42\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCa/K ratio\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e39.55\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMg/K ratio\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e9.42\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCa\u0026thinsp;+\u0026thinsp;Mg/K ratio\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e49.00\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"2\"\u003eC.E.C.: Cation Exchange Capacity\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe total area of the \u003cem\u003eEl Porvenir\u003c/em\u003e farm is 182 ha, mostly deserved to the extensive livestock production system, on which this study was carried out. Six ha from such surface were stablished since 2010 with a silvopastoral system including a wide presence of calabash tree with a 5 m \u0026times; 5 m triangular planting frame (~\u0026thinsp;2200 trees in the total area). The trees were planted on an herbaceous stratum composed by two native and improved tropical grasses (\u003cem\u003eBotriochloa pertusa\u003c/em\u003e and \u003cem\u003eMegathyrsus maximus\u003c/em\u003e cv. Tanzania). In the area, large trees (\u003cem\u003eAlbizia saman\u003c/em\u003e, \u003cem\u003eAlbizia guachapele\u003c/em\u003e, \u003cem\u003eAlbizia caribaea\u003c/em\u003e, \u003cem\u003eAnacardium excelsum\u003c/em\u003e, \u003cem\u003eEnterolobium cyclocarpum\u003c/em\u003e and \u003cem\u003eSterculia apetala\u003c/em\u003e) were also established for many years before starting with the silvopastoral system project. Therefore, in such spatial distribution in the field, some trees were fully exposed whereas others did it under the shade of the accompanying species.\u003c/p\u003e\u003cp\u003eSince 2014 to date (including the period of this study), the silvopastoral system has been continuously grazed by a portion of the herd (around 45 beef cows), following a rotational grazing system with the availability of shade, forage and calabash tree fruits, which is normally used as a complement or supplement in the feeding system, either ripe, fresh or ensiled, looking to match nutritional requirements, mainly during the dry season.\u003c/p\u003e\u003cp\u003eFurthermore, local climatology was characterized. Information during the period of the study on the maximum, minimum and average temperature, as well as relative humidity and rainfall in the area, was provided by a meteorological station of the Colombian Institute of Hydrology, Meteorology and Environmental Studies (IDEAM), located 18 km distant from the study area at Motilonia research centre of the Colombian Agricultural Research Corporation (Agrosavia). The data were used as a reference for the present study (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Hence, the average of total annual rainfall was 1750 mm, average relative humidity was 65%, and average annual temperature was 28.8\u0026deg;C (min: 24.0\u0026deg;C; max: 34.3\u0026deg;C).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eExperimental design and data collection\u003c/h3\u003e\n\u003cp\u003eIn order to assess the effect of shade, pruning and harvest time on fruit production and nutritional composition over time, a total and representative sample of 200 calabash trees was carefully selected from the aforementioned silvopastoral system. 100 of those trees were located under the shadow of larger companion trees (45,000 lux), whereas the remaining 100 were directly and fully exposed to sun (not shaded conditions \u0026minus;\u0026thinsp;115,000 lux). According to its location, the trees were randomly distributed in a split-plot experimental design. Thus, the experimental treatments were defined as the combination of each level of each factor with 50 not shaded \u0026ndash; not pruned trees (NSh-NPr), 50 not shaded \u0026ndash; pruned trees (NSh-Pr), 50 shaded \u0026ndash; not pruned trees (Sh-NPr) and 50 shaded \u0026ndash; pruned trees (Sh-Pr).\u003c/p\u003e\u003cp\u003ePruning was carried out using special shears with extension handles (Truper model 18410, Jilotepec, MX), which were disinfected with a solution of 50% commercial ethyl alcohol and 50% tincture of iodine before each tree was pruned. Three types of pruning were combined and carried out on each tree assigned to this practice under the two shade levels: i) sanitary pruning i.e., removing dry branches with sights of evident deterioration or possible disease; ii) production pruning i.e., removing branches located on the main stem (trunk), between the base of the canopy and the ground, as well as smaller secondary and tertiary branches without potential for fruit production located inside the canopy; iii) topping pruning i.e., removing the apex of the branches to remove overlapping and competition for light with branches of neighboring trees. For the most important cuts (trunk and main branches), the points on the trees were directly treated with 58.8% copper oxychloride to prevent further fungal contamination. These pruning guidelines are common in the region. The first pruning of the pre-selected trees was carried out in the first week of April, at the beginning of the first rainy season of the year, and was repeated every 6 months at the beginning of the rains (October 2022, then April and October 2023).\u003c/p\u003e\n\u003ch3\u003eData collection\u003c/h3\u003e\n\u003cp\u003eA schematic representation of the sampling points comprised in the experimental design over a 2-year period (from February 2022 to February 2024) is presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. Ripe calabash tree fruits were scheduled to be collected periodically (every 4 months). The first was considered as a standardization harvest in February 2022, where all the fruits in the sampling trees were collected in order to allow a standardized maturity and four months age of fruits in the samples collected later in June and October 2022, February, June and October 2023, and February 2024 (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). At each harvest, ripe fruits were collected, counted and weighed for each tree using a commercial electronic scale (ICM Model ACS-A9T, Medell\u0026iacute;n, Colombia) with an accuracy of +/- 5 g. In addition, green and fallen fruits were also counted and recorded in the monitoring sheet. During counting and weighing, the ripe fruits harvested from each half of the trees belonging to a same treatment (approximately 25 trees) were stockpiled separately, in order to obtain two stockpiles/treatment/harvest. At the end of each harvest, a representative aliquot of 10% of each stockpile was selected for further nutritional composition analyses.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\n\u003ch3\u003eLaboratory analyses\u003c/h3\u003e\n\u003cp\u003eAfter each sampling, fruits were immediately transferred to the facilities of the \u003cem\u003eLaboratorio de Nutrici\u0026oacute;n Animal\u003c/em\u003e at the \u003cem\u003eUniversidad Francisco de Paula Santander\u003c/em\u003e (Oca\u0026ntilde;a province, Colombia). Prior to opening, fruits on each experimental treatment were weighed on electronic scale, opened using a handsaw and the pulp was removed from the shell, then weighed to be excluded from the initial weight. Pulp from all fruits was manually mixed into a polyethylene bowl until a soft and homogeneous mash was achieved in order to obtain a composed (representative) sample. These mixed samples were arranged in aluminium trays (which were previously weighed and labelled), and placed in a forced air circulation oven (IGS750 Thermo Scientific, Massachusetts, USA) at 55\u0026deg;C for 72 hours for calculating DM content. Subsequently, samples were transferred to the facilities of the \u003cem\u003eLaboratorio de Biotecnolog\u0026iacute;a Ruminal\u003c/em\u003e at the \u003cem\u003eUniversidad Nacional de Colombia\u003c/em\u003e (Medell\u0026iacute;n), then ground in a Willey mill (Thomas Scientific, Swedesboro, NJ, USA) using a 1 mm sieve and analyzed for DM (AOAC, 934.01), Ash (AOAC, 942.05) and ethereal extract (EE) (AOAC, 920.39) according to Lee (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e1995\u003c/span\u003e). The total nitrogen (TN) was determined by distillation using a Kjeldhal equipment according to Latimer (2023; 2001.11) and crude protein (CP) was calculated as TN \u0026times; 6.25. Gross energy (GE) was obtained by combusting samples in a calorimeter bomb (Parr Instrument Company Model 1341, Moline, IL, USA). The neutral detergent (NDF) and acid detergent (ADF) fibres were sequentially determined in an ANKOM\u003csup\u003e200\u003c/sup\u003e Fiber Analyzer (ANKOM Technology Corporation, Fairport, NY, USA) according to Van Soest et al. (\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e1991\u003c/span\u003e).\u003c/p\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eData on fruit production [harvested fruit (kg), mean weight of fruit (g), as well as harvested, unripe and fallen fruits (units)] were analysed using Linear Mixed Models (LMM) with an ANOVA procedure as a split-plot experimental design where shade, pruning and time effects were considered as fixed effects.\u003c/p\u003e\u003cp\u003eThe general model adjusted for each variable included the shade effect as a factor with two levels assigned to the main plot and the pruning effect as a factor with two levels assigned to the subplot (tree). The effect of 6 harvests along time (time effect) was assessed using a repeated measurements model and a block factor was considered to eliminate the soil effect. The full model (including repeated measures) was fitted by evaluating the unstructured, compound symmetry and autoregressive covariance model structures for each variable prior the data analysis were performed. Thus, the best model for data analysis was selected based on the lowest BIC criteria. Statistical analyses were performed using the \u003cem\u003elmer\u003c/em\u003e function of R Studio Software version 2024.12.1 (R Core Team, 2024) after testing the mathematical assumptions of the model (Shapiro-Wilk and Barlett test). When dataset did not meet the mathematical assumptions of the model, transformations of the logarithm family were applied.\u003c/p\u003e\u003cp\u003eWhen the ANOVA result was significant, a post hoc LSD test using the \u003cem\u003eemmeans\u003c/em\u003e function with Holm multiplicity adjustment was performed to compare the main effect of shade, pruning and time as well as the first-order shade \u0026times; pruning, shade \u0026times; time and pruning \u0026times; time interactions and the second-order shade \u0026times; pruning \u0026times; time interaction. A significance level of 5% was used for all tests.\u003c/p\u003e\u003cp\u003eIn data regarding nutritional quality variables, Principal Components Analysis (PCA) were performed in order to explain possible variation on the fruit composition due to the effect of shade, pruning, harvest or the combination of pruning and shade levels.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows the main effects and the first and second order interactions of shade, pruning, and harvesting time on calabash tree fruit production in silvopastoral systems.\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\u003eMain effects, and first and second order interactions among the evaluated factors (shade, pruning and harvest time) on calabash tree fruit production under silvopastoral system conditions in the \u003cem\u003eEl Porvenir\u003c/em\u003e farm (located in the tropical dry forest of northern Colombia).\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"8\"\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\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"7\" nameend=\"c8\" namest=\"c2\"\u003e\u003cp\u003eEffect, \u003cem\u003eP value\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSh\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePr\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eT\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eSh \u0026times; Pr\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eSh \u0026times; T\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003ePr \u0026times; T\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eSh \u0026times; Pr \u0026times; T\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHarvested fruit (kg)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.0043\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.0242\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.4513\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.1697\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.1587\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAverage Fruit weight (g)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.0264\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.0188\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.1315\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.0053\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.4774\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.1889\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHarvested fruits (units)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.0031\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.0234\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.6404\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.2550\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.3485\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUnripe fruits (units)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.0002\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.0020\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.1740\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.0010\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.2660\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFallen fruits (units)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.0097\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.0003\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.5369\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.0107\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.0009\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.8696\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"8\"\u003e\u003cb\u003eSh\u003c/b\u003e: shade; \u003cb\u003ePr\u003c/b\u003e: pruning; \u003cb\u003eT\u003c/b\u003e: Harvesting time; \u003cb\u003eSh \u0026times; Pr\u003c/b\u003e: interaction Shade \u0026times; Pruning; \u003cb\u003eSh \u0026times; T\u003c/b\u003e: interaction Shade \u0026times; Time; \u003cb\u003ePr \u0026times; T\u003c/b\u003e: interaction Pruning \u0026times; Time; \u003cb\u003eSh \u0026times; Pr \u0026times; T\u003c/b\u003e: interaction Shade \u0026times; Pruning \u0026times; Time; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;\u003cem\u003e0.05\u003c/em\u003e was considered as statistically significant.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe main effect of shade resulted in a lower yield of fruit in all the assessed categories (number and kg of ripe harvested fruits, average fruit weight, as well as number of unripe and fallen fruits) when compared to those calabash tree located under sunny conditions. A significant interaction effect of shade \u0026times; time was observed with a significant decrease in the number and kg of ripe fruit in calabash tree harvested in October 2022 and February, June and October 2023 (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA and B). Similarly, shaded trees showed lower average fruit weight at the same harvesting times through 2023 (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC).\u003c/p\u003e\u003cp\u003eInteraction shade \u0026times; time effect was also expressed with a significant decrease in the number of unripe fruits in all harvesting times except October 2022 (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA) and a lower number of fallen fruits in June 2022, October 2023 and February 2024 (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eLower number and kg of ripe harvested fruits/tree and average fruit weight as a consequence of the main effect of pruning in calabash tree was observed (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e6\u003c/span\u003e) with no significant effect on the number of unripe and fallen fruits. Additionally, an interaction effect of pruning \u0026times; time showed a decrease in the number of unripe and fallen fruits in pruned calabash trees in June and October 2023 (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eIn the context of harvesting time (seasonality), calabash trees were found to be generally more productive during the rainy season (June and October) compared to those harvested during the dry season (February). There was no interaction effect of shade \u0026times; pruning and neither second order interaction effect of shade \u0026times; pruning \u0026times; time on any of the yield fruit assessed variables (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05), nor did any of the assessed factors modified the nutritional quality of the calabash tree fruits (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e). Detailed nutritional composition of calabash tree fruit in each experimental treatment is showed in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\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\u003eNutritional composition of calabash tree fruit according with the experimental treatment (n\u0026thinsp;=\u0026thinsp;12)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"5\" nameend=\"c6\" namest=\"c2\"\u003e\u003cp\u003eTreatment\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNSh-NPr\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNSh-Pr\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSh-NPr\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eSh-Pr\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e%DM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e21.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e21.0\u0026thinsp;\u0026plusmn;\u0026thinsp;1.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e19.3\u0026thinsp;\u0026plusmn;\u0026thinsp;3.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e19.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e%NDF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e22.2\u0026thinsp;\u0026plusmn;\u0026thinsp;2.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e21.6\u0026thinsp;\u0026plusmn;\u0026thinsp;2.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e22.4\u0026thinsp;\u0026plusmn;\u0026thinsp;2.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e21.9\u0026thinsp;\u0026plusmn;\u0026thinsp;3.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e%ADF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e15.6\u0026thinsp;\u0026plusmn;\u0026thinsp;2.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e15.0\u0026thinsp;\u0026plusmn;\u0026thinsp;2.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e15.6\u0026thinsp;\u0026plusmn;\u0026thinsp;1.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e14.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e%CP\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e7.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e7.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e8.7\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e9.0\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e%EE\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e9.2\u0026thinsp;\u0026plusmn;\u0026thinsp;1.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e8.4\u0026thinsp;\u0026plusmn;\u0026thinsp;2.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e8.5\u0026thinsp;\u0026plusmn;\u0026thinsp;2.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e9.3\u0026thinsp;\u0026plusmn;\u0026thinsp;2.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e%Ash\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e5.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e5.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e5.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e5.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGE (Mcal/kg of DM)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e4.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e4.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e4.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e4.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003cb\u003eNSh-NPr\u003c/b\u003e: Not shaded \u0026ndash; not pruned trees treatment; \u003cb\u003eNSh-Pr\u003c/b\u003e: Not shaded \u0026ndash; pruned trees treatment; \u003cb\u003eSh-NPr\u003c/b\u003e: Shaded \u0026ndash; not pruned trees treatment; \u003cb\u003eSh-Pr\u003c/b\u003e: Shaded \u0026ndash; pruned trees treatment;\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003eCalabash tree fruit yield\u003c/h2\u003e\u003cp\u003eMonitoring of calabash tree over a two consecutive years period showed a significant effect of shade and pruning expressed in a lower fruit yield. Additionally, time effect was mainly related to variations in rainfall patterns in this study with the higher fruit yield showed June and October (rainy season), with rain as the most determining factor of seasonality in the tropic (Vega-Ramos et al. \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Hence, interaction effect of shade \u0026times; time on all the assessed variable revealed a negative effect of shade and lack of rains on the number, kg and average weight of ripe harvested fruits, as well as on the count of unripe and fallen fruits during the dry season. According to Lambers et al. (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2008\u003c/span\u003e), Valverde-Rodriguez et al. (2019b) and Basave-Villalobos et al. (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), a decrease in luminosity (irradiance) significantly reduces photosynthetic activity (expressed as the CO\u003csub\u003e2\u003c/sub\u003e assimilation rate), which directly affects energy availability and the supply of inputs for growth (in young plants) and flowering and fruiting (reproductive phase in mature plants). At the same time, the author states that, under these circumstances, a significant reduction in water supply could accentuate these effects, further reducing the growth rate or fruit production in either case (young or mature plants, respectively). This argument could explain the reduction in the number, kilograms and the average weight of the fruits harvested in our study. This could be interpreted as an adaptive mechanism of \u003cem\u003eC. cujete\u003c/em\u003e which, under lower light exposure and water availability conditions, is probably forced to prioritize the use of smaller amounts of energy and bio-inputs on the maintenance of vital functions, thus partially compromising flowering and fruit production as a consequence of a lower photosynthetic rate (Givnish, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e1988\u003c/span\u003e; Pi\u0026ntilde;a and Arboleda, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Nina Junior et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Patil et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThus, the sustained effect of shady environment was expressed in a lower fruits yield over time, compared to trees located under full sunshine exposure (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). However, these effects were accentuated in both shaded and not shaded trees by the water restriction pulses corresponding to the dry season months (February 2023/2024; Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The effect of time (seasonality) was notable either at intra and interannual levels. It was reflected as a lower number of harvested fruits in the period of lowest accumulated rainfall within each monitoring year (February 2023 and February 2024), and when comparing the 2nd monitoring year (30% less rainy) to the first one (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Finally, the fact that calabash tree fruit is mostly composed by water (~\u0026thinsp;80% of its fresh matter; Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) could partially explain why a drastic and prolonged reduction on rainfall, although did not mean a risk for plant survival, could dramatically affect fruit yield, both in shaded and not shaded trees during the dry season (Galindo et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Torrecillas et al., \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe interaction shade \u0026times; time effect due to the decrease in rainfall over second year (30% less rainy respect to the first year - Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) would also be the cause of the significant decrease in the average fruit weight/tree (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC) as previously discussed for number, kg and weight of ripe harvested fruits. Considering average fruit weight as the weight and number of ripe harvested fruits ratio (quotient), it behaves according the number and kg of ripe harvested fruits over time.\u003c/p\u003e\u003cp\u003eThe lower fruit yield in calabash trees under light restriction was reflected in lower unripe fruits over time (Figs.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e and \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Same behavior was observed during the second monitoring year with higher unripe fruits in shaded trees, which could be influenced by the overall increase of the total unripe fruits in the same period in both, shaded and not shaded trees (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). The lower rainfall over the second year could have slowed down the ripening process (Lambers et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Galindo et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Valverde-Rodr\u0026iacute;guez et al. \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2019a\u003c/span\u003e), explaining the higher number of unripe fruits. This also can be evidenced in the deleterious decrease on the total ripe harvested fruits whatever the treatment (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e) over this period. In stressful situations such as drought, plants drop many unripe fruits as a physiological mechanism to ensure that the remaining fruits the plant is able to sustain reach maturity (Fernandes et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; De Souza et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe dramatic increase in the number of fallen fruits over the second year could be explained due to the reduction in the rainfall, mainly in the dry season, which recorded accumulated rainfall of 317.6 mm and a total of 636 fallen fruits in the second-year \u003cem\u003evs\u003c/em\u003e 642.6 mm and 16 fallen fruits in the same month in the first year (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), summed to the increase of squirrels (\u003cem\u003eSciuridae\u003c/em\u003e) population from April 2023, due to a nearby deforestation (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eContrary to our hypothesis, agronomical practice of pruning did not stimulate an increase in the ripe harvested fruit yield in calabash tree as in other tropical fruit trees (i.e., avocado, mango, guava). Changes in canopy of pruned trees, such as the regrowth of new branches and leaves precisely at the points where pruning was performed were observed through the months immediately following pruning. This would lead us to speculate that the potential surplus energy and nutrients not used to maintain the biomass removed from the canopy may have been used to replace the branches and leaves removed by pruning, instead of increasing the number or average weight of fruits, finally leading to the decrease on fruit yield, contrary to expected (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eSimilarly, pruning reduced the number of unripe and fallen fruits over time, with significant differences in June and October 2023 during the rainy season (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e7\u003c/span\u003e). This behavior, similarly to interaction shade \u0026times; time for these variables, could be influenced by the reduction on fruits yield due to pruning, that together to the alterations in the fruit yield pattern related to both decrease on rainfall or increased squirrel attacks over second monitoring year, could be statistically expressed in these differences, as previously discussed.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eNutritional quality of calabash tree fruits\u003c/h2\u003e\u003cp\u003ePrincipal component analysis of calabash tree fruit nutritional quality did not show relevant differences due to the experimental treatments (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e; Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe main limitation of this study was the chemical analysis of fruit nutritional composition from composed samples by treatment. This prevented us from achieving a significant number of replicates per treatment/harvest time, substantially affecting the power of the inferential statistical test. This led us to opt for the PCA method, which would allow us to demonstrate possible differences in composition and explain the possible relationship between the study factors and the fruit nutritional quality variables (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e). Future studies with a larger number of independent replicates that allows for inferential analysis to evaluate the effect of the factors on fruit composition with greater statistical power are recommended.\u003c/p\u003e\u003cp\u003eSeveral studies assessing the effect of shade (Rozendaal et al. \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Poorter et al. \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Elshahat et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) and tree pruning (Marini \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Adhikari and Kandel \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Arredondo et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Ali et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Singh et al. \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) on fruit yield, size and nutritional composition in citrus, fig, pitaya, guava and other tropical fruit trees, reports that changes on fruit yield and quality did not depend solely on the presence or absence of these factors (as was the case in the present study), but are influenced by the intensity and duration (in the case of shade) or the site, moment and frequency of its application (in the case of pruning). Likewise, its effects can vary as a result of its interaction with other external factors such as the edaphoclimatic conditions of the study area (Gratani \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), planting density (Chithiraichelvan et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Haque and Sakimin \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Ladon et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), as well as the species and its own phenological cycle, canopy architecture, pollinator activity, among others factors related to the plant species \u003cem\u003eper se\u003c/em\u003e.\u003c/p\u003e\u003cp\u003eThereby, the results obtained in this pioneering study, far from searching definitive conclusions, search for significant contribution to establishing the interest and basis of what we consider an extensive line of research on a species that provides numerous attributes to different cultures spread across the vast tropical region of the world.\u003c/p\u003e\u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThe presence of shade significantly reduced the amount and weight of calabash tree fruit harvested over time. These effects were more pronounced during the dry season. Therefore, shade is not recommended for calabash trees in silvopastoral systems alongside larger trees when the aim is adding value from fruit production as a feed resource for livestock. A decrease in the size and fruit yield due to shade also has negative implications related to harvest efficiency, since this increases the number of trees, time and labor required compared to not shaded trees.\u003c/p\u003e\u003cp\u003eAs an agronomic management practice, pruning did not improve fruit production and nutritional quality as expected; therefore, under the conditions of this study it is not recommended. The nutritional quality of calabash tree fruits remained unchanged due to shade, pruning or to the seasonal weather fluctuations typical of tropical dry forests.\u003c/p\u003e\u003cp\u003eBased on these findings, not pruned trees located under total sunny conditions are considered the best strategies in order to obtain the greatest fruit production. Hence, the ability of calabash tree to yield more fruit in open spaces (with no shade) with agronomical practice of pruning being not required, make it ideal for converting herbaceous pastures and deforested landscapes into silvopastoral systems as a feasible sustainable livestock alternative in dry tropical savannas.\u003c/p\u003e\u003cp\u003eThe productive kinetics of calabash trees over time revealed a significant reduction on fruit yield during the dry season. Therefore, calabash tree response to complementary management practices such as fertilization based on the own manure utilization, strategic irrigation and fruit conservation techniques should be evaluated in future studies in order to improve productivity and biological activity of this systems during the dry season.\u003c/p\u003e\u003cp\u003eOur results highlight the potential of the calabash tree as a source of livestock feed in silvopastoral systems, particularly during the dry season when the nutritional quality of forages as the main feed resource is affected by water restrictions.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFounding\u003c/strong\u003e\u003cstrong\u003estatement\u003c/strong\u003e\u003cstrong\u003e:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eMinistry of Science, Technology and Innovation (MinCiencias) from Republic of Colombia\u003cstrong\u003e\u0026nbsp;–\u0026nbsp;\u003c/strong\u003eDoctoral scholarship abroad program – call N° 885\u003c/li\u003e\n \u003cli\u003eUniversidad Nacional de Colombia – UNAL (Medellín headquarters) – Laboratorio de Biotecnología Ruminal – Colombia.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eWe would like to thank José Félix Lafaurie and the staff of 'El Porvenir' farm for granting us access to the experimental areas and for providing all the assistance necessary to carry out activities during the experimental phase in the field.\u003c/li\u003e\n \u003cli\u003eWe would like to thank the Department of Animal Production and Animal Nutrition Laboratory at the Universidad Francisco de Paula Santander Ocaña for allowing us to use their laboratory facilities and equipment to dry and prepare samples for subsequent analysis.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDiego A. Rojas-Meza:\u0026nbsp;\u003c/strong\u003eConceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Validation, Visualization, Writing – original draft. \u003cstrong\u003eEliel Gonzalez-García:\u0026nbsp;\u003c/strong\u003eConceptualization, Methodology, Supervision, Funding acquisition, Visualization, Review and editing. \u003cstrong\u003eEnrique Murgueitio:\u0026nbsp;\u003c/strong\u003eConceptualization.\u003cstrong\u003e\u0026nbsp;Guillermo Antonio Correa Londoño:\u0026nbsp;\u003c/strong\u003eData curation, Formal analysis, Software.\u003cstrong\u003e\u0026nbsp;Milton Rivera Rojas:\u0026nbsp;\u003c/strong\u003eMethodology.\u003cstrong\u003e\u0026nbsp;Leonardo Manzano García:\u0026nbsp;\u003c/strong\u003eConceptualization, Funding acquisition, Resources.\u003cstrong\u003e\u0026nbsp;Jordi Bartolomé Filella:\u0026nbsp;\u003c/strong\u003eConceptualization, Methodology, Supervision, Visualization, Review and editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo datasets were generated during the current study\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no conflict of interest.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAdeyemi KD, Audu S, Oloke JA, et al (2021) Influence of Crescentia cujete and Launaea taraxacifolia leaves on growth, immune indices, gut microbiota, blood chemistry, carcass, and meat quality in broiler chickens. 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Global Change Biology 30:e17036. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/gcb.17036\u003c/span\u003e\u003cspan address=\"10.1111/gcb.17036\" 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":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"agroforestry-systems","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"agfo","sideBox":"Learn more about [Agroforestry Systems](http://link.springer.com/journal/10457)","snPcode":"10457","submissionUrl":"https://submission.nature.com/new-submission/10457/3","title":"Agroforestry Systems","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"shade, pruning, tropical tree, livestock feed, dry season","lastPublishedDoi":"10.21203/rs.3.rs-7551294/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7551294/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe objective was to assess the effect of shade, pruning, and harvest time (seasonality) on the yield and nutritional composition of calabash tree fruit (\u003cem\u003eCrescentia cujete\u003c/em\u003e). This fruit is used as livestock feed in silvopastoral systems in the dry South American tropics. Two hundred calabash trees were randomly distributed in a split-plot experimental design with four experimental treatments (n\u0026thinsp;=\u0026thinsp;50) defined as: not shaded-not pruned trees (NSh-NPr), not shaded-pruned trees (NSh-Pr), shaded-not pruned trees (Sh-NPr) and shaded-pruned trees (Sh-Pr). Trees were monitored each 4 months over a 2-years total period and its fruits were classified as ripe, unripe and fallen fruits, whereas ripe fruits were collected and analyzed by its nutritional quality. The shade effect significantly decreased fruit yield. There was a significant interaction shade \u0026times; time effect. The fruit yield decreased in October 2022 and February, June and October 2023, as well as the average fruit weight at the same harvesting times (except in October 2022). Pruning also showed a significant effect with lower weight and fruit yield. A significant interaction effect of pruning \u0026times; time was reflected on lower unripe and fallen fruits, both in June and October 2023 (rainy season). Shade, pruning and seasonality did not affect the nutritional quality of fruits. Not pruned calabash tree under sunny conditions has proven to be the best strategy in order to obtain the greatest fruit yield for livestock feeding, ideal for converting conventional herbaceous pastures and deforested landscapes into silvopastoral systems as a sustainable alternative for livestock production in dry tropical savannas.\u003c/p\u003e","manuscriptTitle":"Yield and nutritional quality of calabash tree fruit (Crescentia cujete) in silvopastoral systems: implications for on-field management","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-16 15:38:09","doi":"10.21203/rs.3.rs-7551294/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewersInvited","content":"","date":"2025-09-30T16:22:06+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-15T16:07:05+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-12T11:48:44+00:00","index":"","fulltext":""},{"type":"submitted","content":"Agroforestry Systems","date":"2025-09-06T13:28:32+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"agroforestry-systems","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"agfo","sideBox":"Learn more about [Agroforestry Systems](http://link.springer.com/journal/10457)","snPcode":"10457","submissionUrl":"https://submission.nature.com/new-submission/10457/3","title":"Agroforestry Systems","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"dd109d75-7681-4a36-9937-00a84ab25372","owner":[],"postedDate":"September 16th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-09-30T16:38:10+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-16 15:38:09","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7551294","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7551294","identity":"rs-7551294","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}