Prospecting elite donor plants and characterization of endogenous hormonal status in seeds of Brazilian chestnuts (Lecythidaceae)

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This study aimed to: (1) demarcate and characterize phenotypically and genotypically both species; (2) analyze seed biometric and physiological traits; (3) investigate seed hormonal composition and its influence on germination; and (4) assess early seedling phenotypes. L. pisonis showed higher genetic diversity than L. lanceolata . Seedling emergence was highest in seeds from specific trees: 1 and 2 ( L. pisonis ) and 1, 2, 4, 5, and 6 ( L. lanceolata ). Abscisic acid (ABA) and 1-aminocyclopropane-1-carboxylic acid (ACC) were negatively correlated with seed growth in both species. In L. pisonis , methyl jasmonate (MeJA) in the endosperm correlated positively with seedling emergence, while MeJA in the tegument negatively affected shoot formation in both species. In L. lanceolata , ABA in the seed coat positively influenced mean emergence time, suggesting a dormancy mechanism. These findings enhance the understanding of seed physiology and early development in L. pisonis and L. lanceolata , offering key insights for future propagation and commercial cultivation efforts. Biological sciences/Developmental biology Biological sciences/Ecology Biological sciences/Physiology Biological sciences/Plant sciences Earth and environmental sciences/Ecology Genetic divergence Seedling emergence Seedling phenotyping Seed vigor Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Introduction Globally, Brazil is the country with the highest biodiversity and the second-largest area covered by natural forests 1 . The Amazon Forest and the Atlantic Forest biodiversity hotspot harbor species of chestnuts called Lecythis pisonis Cambess. and Lecythis lanceolata Poir., whose nuts are rich in nutrients and antioxidant compounds 2 . The high nutritional potential of these nuts makes them novel unconventional foods to be introduced into human consumption, mainly as a source of selenium 3 . This can be observed in the trees of Bertholletia excelsa Humn. & Bonpl., which belongs to the same family (Lecythidaceae) as the species studied, whose nuts are appreciated worldwide and considered one of the main products of Amazonian extractivism 4 . The lack of information related to the germination behavior and growth of seedlings of both species is the main problem of this study. This information is essential for the production of seedlings in forest nurseries, whether for reforestation purposes or for commercial purposes of non-timber resources aimed at selling nuts. Germination behavior varies depending on the species, and it is necessary to understand whether there is any type of physical or physiological impediment that hinders this process and the formation of normal seedlings, being the seed germination is related to a rigorous endogenous hormonal balance established through signaling pathways and specific genes 5 . The breaking of physiological seed dormancy is mainly associated with the loss of sensitivity of abscisic acid, which acts by inactivating the transcription of genes involved in germination processes and promotes the transcription of genes responsible for the catabolism of gibberellic acid. The gibberellic acid produced in the embryo and released in the aleurone layer induces the synthesis of α-amylases and proteases that are released in the endosperm to start the synthesis of starch degradation, and its catabolism interrupts this process that allows the nutrition of the embryo 6 . The hormones present in seeds also induce the growth of seedlings, through an antagonistic relationship between auxin/cytokinin. Auxins are responsible for apical dominance, height growth, and root formation, while cytokinins induce the formation of lateral shoots and participate in cell division processes 7 . After the seedlings have grown, the highest quality ones should be selected for planting in the field. This selection is carried out through phenotypic characteristics of rusticity, such as the collar diameter, which usually indicates a greater ability to adapt to adverse conditions, contributing to the reduction of project costs caused by low survival 8 . During seed harvesting, another important factor that must be analyzed is the genetic diversity of the mother trees. It is known that approximately 50% of Lecythidaceae are found in forest fragments of the Amazon rainforest, sites of auto-endemism, and extreme deforestation 9 . Forest fragmentation and isolation of tree populations lead to a decrease in the genetic diversity of their descendants 10 . To ensure the selection of sufficiently diverse populations, genotypic diversity of molecular markers must be considered together with phenotypic diversity 11 . Parent trees can be selected based on desirable phenotypes, allowing the identification of new individuals for genetic improvement programs 12 . The analyses of phenotypic characteristics are efficient for a better understanding of the genotype/environment interaction, aiming at efficient use of genetic resources and, in the future, the production of young forests with improved genetic structures 13 . L. pisonis trees with greater crown circumference tend to produce fruits with large seeds 14 , which is an important characteristic for the food industry, since consumers already prefer larger nuts 15 . Observations in L. pisonis show that extra-large fruits produce large seeds in smaller numbers 14 . Mother trees spend less energy in producing small seeds when compared to large seeds. However, large seeds are more resistant to adverse environmental conditions but are often attacked by rodents 16 . Large seeds can also positively influence seedling germination, vigor, and growth 17 . Given this information, the aim of this study was (1) to demarcate and phenotypically and genotypically characterize a group of trees belonging to the species L. pisonis and L. lanceolata ; (2) biometrically and physiologically characterize its seeds; (3) understand the hormonal composition of its seeds and the effect of these hormones on germination and (4) phenotypically characterize seedlings at an initial stage of growth. Methods Geographic coordinates and matrix characterization Seeds from six trees of L. pisonis (Lp) and six trees of L. lanceolata (Ll) were collected in the municipalities of Laranja da Terra (trees 1 and 2 of L. pisonis ), Cachoeiro de Itapemirim (trees 3, 4 and 5 of L. pisonis ), Alegre (tree 6 of L. pisonis ), and Mimoso do Sul (trees 1, 2, 3, 4, 5 and 6 of L. lanceolata ), Espírito Santo, Brazil (Fig. 1 ). The trees of L. pisonis and L. lanceolata were observed from flowering (oct/2017) until the beginning of the opening of the first fruits (oct/2018), with the opening of the pixidio indicating the ideal point of harvest. The trees were climbed with the aid of a seat belt and aluminum ladder, and all the fruits produced in 2018 were harvested with the aid of an adjustable aluminum pruner and later the total number of fruits was counted. The trees were characterized in terms of height (m) using a Suunto ® PM-5/360PC clinometer, diameter at breast height (cm), larger canopy diameter (m), smaller crown diameter (m), and crown circumference (m) using measuring tape. The age of all trees collected was also identified through dendrochronological analyses. At least two wood samples were taken from each tree using an increment borer. The samples were obtained perpendicular to each other, measuring 0.5 mm in diameter, at a height of 1.30 m above the ground in the bark-pith direction. The collected samples were carefully polished using a variety of sandpaper, ranging from 80 to 1200 grains per square millimeter, to highlight the transverse plane. The annual rings were counted and analyzed by scanning the samples at 1200 dpi (Fig. 2 ). The temperature (°C), precipitation (mm), and water balance (mm) of the locations of each tree studied were analyzed, aiming to characterize the environment and explain possible results related to fruit production and endogenous concentration of hormones in the seeds. Between October 2017 and August 2018, the average annual temperatures in the harvest regions ranged from 20.08°C (Mimoso do Sul) to 24.21°C (Cachoeiro de Itapemirim) (Fig. 3 a). Generally, temperatures were higher between September and April (rainy season). Potential evapotranspiration increased in summer (December to March) and decreased in winter (June to September) in all municipalities (Fig. 3 b). Rainfall increased in October (spring) and was high until the end of summer (March), resulting in a water surplus. Water deficiency was almost always positive or close to zero. The most significant increase in water deficiency was observed from May to August 2018, when evapotranspiration surpassed rainfall (Fig. 3 c). Seed biometrics For the biometric analysis of seeds from L. pisonis and L. lanceolata trees, four replicates with 25 seeds, i.e. a total of 100 seeds per tree, were studied, which were arranged in a completely randomized design. Seed length, seed largest width, and seed smallest width, as well as the thickness of the integument in the hilum region and aerial part, were measured with a digital caliper (Snauzer ® , precision 0.01 mm). Seed mass, endosperm mass, and integument mass were determined using an analytical balance (Mars ® AY220, precision 0.0001 g). Seed volume was measured by immersion in water according to Archimedes' principle (density H2O = 1 g cm - 3 ), and the seed density (g cm - 3 ) was calculated by the ratio: seed mass/seed volume. Seedling emergence, vigor, and phenotyping The seeds of L. pisonis and L. lanceolata were collected from pixid type fruits, originating from inflorescences. The seeds were arranged in a randomized block design, with four replicates of 25 seeds per matrix tree, and sown in polypropylene tubes with a capacity of 280 cm 3 containing Vivato ® substrate. The tubes were kept in a shade house covered with polyethylene mesh, which reduced the ligh t intensity by 50%. Emergence (%) was evaluated according to Brasil 22 . The emergence speed index (ESI) was calculated using the formula ESI = E 1 /N 1 +...+ E n /N n , where E 1 and E n represent the number of emerged seedlings in each count, and N 1 to N n represents the number of days elapsed between sowing and each count 23 . The mean time of emergence (MTE, days) was evaluated using the formula MTE = Σn i t i /Σn i , where n i represents the number of germinated seeds at each count and it is the time elapsed between emergence and the last count 24 . At 160 days after sowing, seedling samples were randomly selected within each repetition, the seedlings were organized in a randomized block design, consisting of four replicates with 12 seedlings each, totaling 48 seedlings (Fig. 4 a-n). The characteristics evaluated in the seedlings were: the length of the aerial part (cm), main root length (cm), leaf length (cm), and leaf width (cm) were evaluated using a ruler graduated in millimeters. The collar diameter (mm) and main root diameter (mm) were measured using a digital caliper (Snauzer ® , precision 0.01 mm). The diameter of the lateral root (mm) and leaf thickness (mm) were measured using a digital micrometer (Digimess ® ). Root volume (cm 3 ) was measured by immersion in water according to Archimedes' principle (density H 2 O = 1 g cm - 3 ). The number of lateral roots, number of leaves, number of shoots, and number of stems were counted. Shoot dry mass (g), dry root mass (g), and total dry mass (g) were measured in a hot-air oven (Adamo ® ) until constant weight was attained. Root density (g cm - 3 ) was calculated using the formula dry root mass/root volume. Dickson's quality index was calculated using the formula: total dry mass/(length of the aerial part/collar diameter) + shoot dry mass/dry root mass 25 . The length of the aerial part/number of leaves, length of the aerial part/number of lateral roots, length of the aerial part/collar diameter, shoot dry mass/dry root mass, number of lateral roots/main root length, and number of shoots/main root length ratios were calculated. Colorimetry parameters in leaf (L*, a*, b*, C*, and H°) were measured using a CR-10 digital colorimeter (Konica Minolta ® ); whereas the SPAD index was assessed using a SPAD-502 Plus chlorophyll meter (Konica Minolta ® ). Analysis of hormones/precursors in seeds Hormonal extraction from the seed integument and endosperm was performed according to Forcat et al. 26 , with some modifications 27 . Six L. pisonis and six L. lanceolata trees, laid out in a completely randomized design with four replicates of 0.110 g each, were used. The tegument and endosperm samples were macerated separately in methanol:isopropanol:acetic acid extraction solution (20:79:1 v:v:v) and 400 µL of the extract was placed in pre-cooled microtubes. The microtubes were vortexed four times for 20 s, sonicated for 10 min, placed on ice for 30 min, sonicated for another 10 min, and finally centrifuged at 13000 rpm for 10 min at 4°C. After repeating the post-maceration steps, the supernatant was filtered into microtubes using syringe filters (PVDF 13 mm × 0.22 µm). Samples (5 µL) were injected in an ultra-high-performance liquid chromatography system coupled to a triple quadrupole mass spectrometer (Agilent Technologies; model 6430). Chromatographic separation was performed using a Zorbax Eclipse Plus C18 column in series with a Zorbax SB-C18 guard column (Agilent Technologies). The solvents used were acetic acid (0.02%) in water and acetic acid (0.02%) in acetonitrile, with a flow rate of 0.3 mL min - 1 and a temperature of 30°C. Electrospray ionization mass spectrometry was applied by adjusting the gas temperature to 300°C, nitrogen to 10 L min - 1 , nebulizer to 35 psi, and capillary voltage to 4000 V. The peaks of gibberellic acid (GA 3 ), indole-3-acetic acid (IAA), zeatin (ZT), abscisic acid (ABA), jasmonic acid (JA), methyl jasmonate (MeJA), salicylic acid (SA), and the ethylene precursor 1-aminocyclopropane-1-carboxylic acid (ACC) were obtained. Multiple reaction monitoring allowed for the individual mass to be monitored via molecular fragmentation tests: ZT (220/136), ACC (102.1/56.2), ABA (263/153), IAA (176/130), SA (137/93), GA 3 (345/142.9), and JA (209/59). Scanning was carried out in positive (ZT, IAA, and ACC) and negative (ABA, SA, GA 3 , and JA) modes; absolute quantification was based on a calibration curve (0.1 to 200 ng) constructed with the standard of each hormone. The area of each peak was derived using Skyline ® Software, and the masses were subsequently calculated in ng g - 1 of fresh mass, using the equation Y = X, where Y is the peak area. Genotyping of inter simple sequence repeat (ISSR) markers Genomic DNA extraction DNA was extracted from the leaves of L. pisonis and L. lanceolata trees, following maceration in liquid nitrogen according to Doyle and Doyle 28 . Macerated tissue (50 mg) was transferred to microtubes containing 700 µL of 200 mM Tris-HCl (pH 7.5), 288 mM NaCl, 25 mM cetyltrimethylammonium bromide, 0.5% sodium dodecyl sulfate, 0.2% beta-mercaptoethanol, and 1% polyvinylpyrrolidone. The samples were placed in a dry bath for 30 min at 65°C and homogenized every 10 min. Next, 650 µL of chloroform:isoamyl alcohol 24:1 (v:v) was added, the samples were homogenized for 5 min, and centrifuged at 12000 rpm for 10 min. The supernatant was decanted, and the extraction plus centrifugation steps were repeated twice. DNA was precipitated with ice-cold isopropanol and 230 µL of ammonium acetate and then centrifuged at 12000 rpm for 10 min. The DNA precipitate was washed three times with 250 µL of 70% alcohol and centrifuged at 12000 rpm for 3 min. The samples were then placed in a dry bath and resuspended in 40 µL TE buffer with RNase (40 µg mL − 1 ), followed by incubation at 37°C for 30 min. A Nanodrop 2000 Spectrophotometer (Thermo Scientific®) was used to analyze the quality and quantity of DNA. DNA integrity was analyzed on 1.2% agarose gels using a Bio-Rad GelDoc™ XR photo-documenter. DNA amplification and electrophoresis After extraction of genomic DNA, amplification and electrophoresis were performed as described by Rosa et al. 3 , with some modifications. The following 11 ISSR primers (with their respective ringing temperatures indicated in parenthesis) were used: UBC 841, UBC 852, UBC 853, UBC 868, UBC 873, UBC 880, UBC 812, and UBC 818 (50°C); UBC 808, UBC 826, and UBC 811 (56°C). Amplification conditions were as follows: 1× buffer; 1 U Taq DNA polymerase in 0.2 µL; 0.8 µM primer, 0.8 mM dNTPs, 2 mM MgCl 2 ; 7 ng genomic DNA, and 7.8 µL H 2 O for a final volume of 15 µL. Amplification was carried out in a Veriti 96-Well Thermal Cycler (Applied Biosystems®) with the following program: 4 min denaturation at 94°C, followed by 40 cycles of 1 min at 94°C for denaturation, 1 min at T °C for specific annealing of each primer, 1 min at 72°C for extension, and 5 min at 72°C for the final extension step. The amplification products were separated on a 1.2% agarose gel run at 80 V for 2 h, stained with GelRed® dye, and documented on a GelDoc™ XR. Statistical analysis Analysis of variance and Tukey’s test ( p > 0.05 ) were performed for the completely randomized design and randomized block design experiments, the F test ( p > 0.05 ) for the hormonal characterization of the integument and endosperm, and Pearson correlation for comparison of all parameters. ISSR data were fed into a Jaccard dissimilarity matrix and grouped by the unweighted pair group method with arithmetic mean (UPGMA) to obtain genetic similarity estimates. Phenotypic and hormonal diversity was estimated using phenotypic and hormonal characteristics analyzed by the Mahalanobis dissimilarity matrix and the UPGMA. Path analysis based on the estimated Pearson correlation coefficients (rxy) was performed in R 29 , using the package biotools 30 , 31 , to examine the direct and indirect effects of a group of independent variables over dependent variables. In the first group, the independent variables indole-3-acetic acid, zeatin, abscisic acid, and methyl jasmonate in tegument and endosperm were coupled to the dependent variables emergence, emergence speed index, and mean time of emergence. In another group of independent variables, indole-3-acetic acid in tegument and endosperm, zeatin in tegument and endosperm, indole-3-acetic acid in tegument/zeatin in tegument ratio, indole-3-acetic acid in endosperm/zeatin in endosperm ratio, methyl jasmonate in tegument and endosperm were coupled to number of shoots as dependent variable. The following variation was found: R_squared: 0.851 to 0.998 and residual effect: 0.046 to 0.385. Results The height of L. pisonis trees varied between 13.68 (tree 5) and 36.68 m (tree 4), with the highest diameter at breast height and crown circumference values observed in trees 1 (91.99 cm and 62.83 m) and 2 (70.35 cm and 56.55 m, respectively). Compared to other L. pisonis trees, which produced between 23 and 51 fruits, trees 1 and 2 yielded 300 and 200 fruits, respectively. L. lanceolata trees were smaller in size, ranging from 8 (tree 5) to 14 m (tree 6), with tree 6 displaying the largest diameter at breast height (56.50 cm), crown circumference (43.35 m), and number of fruits produced (126 fruits) (Table 1 ). The age of L. pisonis trees ranged from 16 to 28 years while L. lanceolata trees ranged from 18 to 52 years old. L. pisonis , despite having younger trees, shows a wider range of fruit production, varying from 23 to 300 fruits as the trees age. In contrast, L. lanceolata , with older trees, maintains a more consistent production over time, with fruit numbers ranging from 20 to 126. Table 1 Characterization of growth of trees from L. pisonis and L. lanceolata in terms of height (H, m), diameter at breast height (DBH, cm), larger crown diameter (CD >, m), smaller crown diameter (CD CD < CC NFT Age L. pisonis 1 32.50 91.99 19.00 21.00 62.83 300 28 2 23.00 70.35 19.00 17.00 56.55 200 25 3 18.68 33.00 12.00 8.30 31.89 51 21 4 36.68 51.00 19.00 12.80 49.95 23 16 5 13.68 27.00 10.50 7.20 27.80 29 16 6 18.00 91.80 17.00 15.00 50.26 25 23 Mean 23.75 60.85 16.08 13.55 46.54 104.66 21.5 L. lanceolata 1 10.00 28.80 8.50 8.30 26.39 25 20 2 10.00 19.60 6.60 6.50 20.58 48 18 3 10.50 21.25 9.00 8.90 28.12 48 20 4 10.50 20.50 8.80 7.10 24.97 55 24 5 8.00 20.00 7.80 7.20 23.56 20 23 6 14.00 56.50 14.30 13.30 43.35 126 52 Mean 10.50 27.77 9.16 8.55 27.82 53.66 26.17 As shown in Table 2 , the highest seedling emergence (93%) and emergence speed index of seedlings were observed in the 1 tree of L. pisonis after 53 days. Emergence was similar in the 2 trees of L. pisonis (88%), but the emergence speed index was lower, causing the mean time of emergence to be delayed to 68 days. Additionally, L. pisonis 2 trees showed elevated seed mass (7.70 g), seed volume (7.90 cm 3 ), and endosperm mass (4.62 g). Endosperm mass was also high in the 3 (4.17 g) and 5 (4.34 g) trees of L. pisonis . Among L. lanceolata trees, seedling emergence was greatest in 1, 2, 4, 5, and 6 (Emergence Mean = 81.4%). Notably, tree 5 showed the highest seed vigor, with a mean time of emergence of only 51.58 days. The 3 trees exhibited the lowest seedling emergence (60%); however, the seeds of this tree displayed the highest seed mass (9.16 g) and endosperm mass (4.51 g) (Table 2 ), which are important characteristics for the chestnut market. Table 2 Emergence (E, %), emergence speed index (ESI), mean time of emergence (MTE, days), seed mass (SM, g), endosperm mass (EM, g), tegument mass (TM, g), seed volume (SV, cm 3 ), seed density (SD, g cm - 3 ), seed length (SL, mm), smaller seed width ( SW, mm), tegument thickness in the aerial part region (ITAPR, mm) and tegument thickness in the hilum region (ITHR, mm) of seeds from different trees of L. pisonis and L. lanceolata Trees E ESI MTE SM EM TM SV L. pisonis 1 93.00a 1 0.45a 53.75ab 5.87c 3.58cd 2.06c 6.08c 2 88.00ab 0.38b 62.25a 7.70a 4.62a 2.90ab 7.90a 3 3.00e 0.01e 28.50b 6.86b 4.17abc 2.42bc 7.22b 4 62.67c 0.30c 54.67ab 4.03d 3.20d 2.29c 4.13d 5 46.67d 0.21d 59.00ab 5.47c 4.34ab 3.29a 6.58bc 6 81.33b 0.44a 48.65ab 5.96c 3.69bcd 2.51bc 6.02c L. lanceolata 1 80.00a 0.34b 63.80bc 6.05c 3.32b 3.08bc 6.57c 2 77.33a 0.31bc 68.06b 7.66b 3.69b 3.04c 9.95a 3 60.00b 0.23c 71.67ab 9.16a 4.51a 3.64ab 9.47ab 4 87.00a 0.39ab 60.59bc 4.61d 2.13c 1.96d 4.86d 5 87.00a 0.44a 51.58c 4.65d 2.65c 1.90d 4.95d 6 76.00a 0.22c 82.86a 7.51b 3.32b 4.06a 8.46b Trees SD SL SW ITAPR ITHR L. pisonis 1 0.97ab 36.67d 17.92bc 21.97ab 1.95ab 2.25 ns 2 0.98ab 38.66c 18.67ab 22.72a 1.80b 2.28 3 0.95ab 43.98a 17.83c 21.22b 1.77b 2.24 4 1.13a 31.37e 15.24d 19.87c 2.15ab 2.48 5 0.83b 42.11b 18.99a 22.50a 2.60a 2.68 6 0.99ab 36.52d 17.32c 21.04b 2.00ab 2.60 L. lanceolata 1 0.92ab 35.88c 18.22b 22.99ab 2.59ab 3.22ab 2 0.77c 42.75b 21.23a 23.55ab 2.39abc 2.87bc 3 0.92ab 43.32b 20.98a 22.65b 2.29bc 2.64c 4 0.95a 33.57d 15.84c 19.11c 2.06c 2.51c 5 0.94a 35.75c 16.93bc 19.16c 2.12c 2.49c 6 0.89b 45.54a 20.90a 24.52a 2.72a 3.29a 1 Means followed by the same letter in the column do not differ by Tukey's test ( p > 0.05 ) between L. pisonis and L. lanceolata . For all L. pisonis trees, there is a higher IAA/ZT ratio and a higher concentration of ACC in the endosperm of the seeds when compared to the tegument. ABA concentrations are higher in the tegument of all seeds when compared to the endosperm. JA concentrations were higher in the tegument, except for seeds from tree 1. MeJA concentrations were also higher in the seed tegument, except for seeds from 2 and 3 trees. The SA also obtained higher concentrations in the seeds tegument, except for the 4 and 6 trees (Fig. 5 a-h). For the species L. lanceolata , the IAA/ZT ratio was higher in the endosperm of seeds from most trees, except for trees 2 and 3. The concentration of ABA was higher in the seed tegument of all trees about the endosperm. The concentrations of SA and ACC were higher in the endosperm of all seeds when compared to the tegument. JA was superior in the endosperm of most trees studied, except for trees 1 and 3. For MeJA, the trees with the highest concentrations in the seed endosperm were 1, 2, and 4 and in the tegument were 3, 5, and 6 (Fig. 5 i-p). Phenotyping of seedlings at 160 days after sowing revealed an average length of the aerial part of 42.64 cm and a main root length of 13.12 cm for L. pisonis , and 39.21 and 14.08 cm for L. lanceolata , respectively. Tree 1 of L. pisonis showed the highest SPAD index in its seedlings, although it did not differ statistically from trees 2, 3, 5, and 6. For the species L. lanceolata , trees 3 and 6 attained the highest SPAD indices. In L. pisonis , the seedlings of the 1, 3, 4, 5, and 6 trees did not differ statistically from each other and had a mean number of lateral roots of 25. In L. lanceolata , seedlings from seeds of trees 2 and 3, reached the highest number of lateral roots (mean = 21.58), although these values did not differ statistically from the seedlings from seeds of trees 1 and 4. Number of shoots was 22 times higher in seedlings of the L. lanceolata than in seedlings of the L. pisonis . The low capacity for natural emergence of shoots in L. pisonis seedlings was reflected in the number of leaves value, with an average of 18 leaves per seedling (no statistical difference between the studied trees). In L. lanceolata , the highest number of 127 leaves was observed in seedlings from seeds of tree 3 (Table 3 ). Table 3 Phenotyping of seedlings at 160 days after sowing in L. pisonis and L. lanceolata trees. The following morphological parameters were evaluated: length of the aerial part (LAP, cm), main root length (MRL, cm), collar diameter (CD, mm), number of lateral roots (NLR), main root diameter (MRD, mm), the diameter of the lateral roots (DLR, mm), root volume (RV, cm 3 ), root density (RD, g cm - 3 ), number of leaves (NL), number of shoots (NS), leaf length (LL, cm), leaf width (LW, cm), leaf thickness (LT, mm), number of stems (NST), shoot dry mass (SDM, g), dry root mass (DRM, g), total dry mass (TDM, g), Dickson's quality index (DQI), colorimetry (L*, a*, b*, C*, and H°), SPAD index, as well as LAP/NL, LAP/NLR, LAP/CD, SDM/DRM, NLR/MRL, and NS/MRL ratios Trees LAP MRL CD LAP/CD LAP/NL LAP/NLR L. pisonis 1 44.01ab 1 13.23b 5.87 ns 7.52ab 2.34 ns 1.86b 2 45.55a 12.87bc 5.97 7.67a 2.42 2.39a 3 42.39ab 12.37c 6.47 6.28c 2.70 1.64bc 4 36.14b 13.32b 5.91 6.43bc 1.96 1.45c 5 43.89ab 12.83bc 6.75 6.55abc 2.28 1.66bc 6 43.92ab 14.15a 6.22 7.54ab 2.55 1.88b L. lanceolata 1 36.74cd 14.03ab 4.98ab 7.44ab 0.44abc 2.14bc 2 42.27ab 13.93b 5.07ab 7.74ab 0.51ab 1.96c 3 43.62a 13.85b 5.79a 7.61ab 0.34c 1.96c 4 33.91d 14.47a 4.77b 7.16b 0.39bc 1.93c 5 37.53bcd 14.25ab 5.01ab 7.49ab 0.54a 2.99a 6 41.21abc 14.00ab 4.72b 8.75a 0.47ab 2.79ab Trees NLR NLR/MRL MRD DLR RV RD L. pisonis 1 23.71a 1.80ab 6.13 ns 1.12 ns 3.33ab 0.37 ns 2 19.14b 1.49b 6.13 0.95 2.47c 0.34 3 25.53a 2.09a 6.97 1.05 4.09a 0.38 4 24.10a 2.00ab 5.97 1.04 2.45c 0.35 5 26.76a 2.09a 6.53 1.08 3.03bc 0.37 6 24.96a 1.76ab 6.58 0.95 3.90a 0.32 L. lanceolata 1 18.96ab 1.36abc 4.76 ns 0.77bcd 2.33 ns 0.35 ns 2 22.27a 1.60ab 5.04 0.70d 2.73 0.35 3 20.88a 1.65a 5.41 0.86ab 2.70 0.35 4 17.83ab 1.23bcd 5.19 0.74cd 2.21 0.41 5 12.73c 0.89d 5.09 0.89a 2.92 0.34 6 15.13bc 1.08cd 4.83 0.80abc 2.31 0.34 Trees NL NS LL LW LT NST L. pisonis 1 19.09 ns 0.13c 9.18ab 3.28a 012b 1.17 ns 2 18.32 0.59a 9.43ab 3.21ab 0.11b 1.36 3 16.01 0.29bc 9.59ab 3.06ab 0.14a 1.15 4 19.10 0.38abc 9.01b 2.85b 0.11b 1.24 5 18.34 0.50ab 10.12ab 3.38a 0.11b 1.07 6 17.59 0.23bc 10.46a 3.41a 0.11b 1.25 L. lanceolata 1 91.33b 7.77b 6.39b 1.66abc 0.10ab 1.58ab 2 77.00c 7.64b 7.21a 1.75a 0.09b 2.45a 3 127.67a 11.78a 7.33a 1.71ab 0.10a 1.97ab 4 84.28bc 7.67b 5.89b 1.52c 0.09b 1.54ab 5 72.52c 5.93b 6.27b 1.55bc 0.10ab 1.44b 6 85.83bc 6.50b 7.08a 1.65abc 0.10a 2.44a Trees NS/MRL SDM DRM TDM SDM/DRM DQI L. pisonis 1 0.09 ns 3.04ab 1.22 ns 4.26ab 2.56 ns 3.13 ns 2 0.11 2.81ab 1.07 4.12ab 2.90 3.40 3 0.09 3.77a 1.64 5.41a 2.28 3.02 4 0.09 1.89b 1.08 2.71b 2.43 3.02 5 0.08 3.76a 1.39 5.37a 2.83 3.64 6 0.09 3.26a 1.24 4.50a 2.67 3.27 L. lanceolata 1 0.11ab 2.47bc 0.86 ns 3.29b 3.09b 3.55bc 2 0.18a 2.76bc 0.95 3.70b 2.99b 3.45bc 3 0.16ab 4.12a 0.94 5.06a 4.94a 5.63a 4 0.11b 2.22c 0.92 3.14b 2.45b 2.90bc 5 0.10b 2.21c 0.99 3.16b 2.33b 2.75c 6 0.18a 2.91b 0.76 3.70b 3.71ab 4.14b Trees SPAD L* a* b* C* H° L. pisonis 1 35.88a 33.32 ns -10.92a 20.86b 23.47b 118.41 ns 2 34.89ab 34.03 -11.75ab 21.97ab 24.99ab 119.40 3 34.37ab 33.95 -10.89a 22.18ab 24.61ab 116.18 4 31.42b 35.77 -12.63b 24.27a 27.25a 115.12 5 34.44ab 33.81 -11.50ab 20.58b 23.57b 119.74 6 34.97ab 33.51 -11.08a 20.37b 23.31b 118.77 L. lanceolata 1 30.33b 36.21ab -10.86bc 25.05a 27.30ab 113.68abc 2 30.19b 36.11ab -11.18c 24.11abc 26.69ab 116.10a 3 34.99a 34.77b -10.42ab 21.44c 23.92c 116.02ab 4 29.12b 38.16a -10.57abc 25.64a 27.68a 112.50c 5 29.18b 37.25a -10.21a 24.44ab 26.43abc 113.26bc 6 33.40a 34.63b -10.39ab 22.14bc 24.71bc 115.19abc 1 Means followed by the same letter in the column do not differ by Tukey's test ( p > 0.05 ) for L. pisonis and L. lanceolata . ABA in endosperm in L. pisonis seeds was negatively correlated with seed volume and seed mass. L. pisonis trees showed a positive correlation between the IAA/zeatin ratio in endosperm and ACC in endosperm (Fig. 6 a). In L. pisonis trees, path analysis revealed that emergence and emergence speed index responded to a positive direct effect of ABA in tegument and MeJA in tegument, a negative direct effect of ZT in endosperm, and a negative indirect effect of IAA in tegument. The number of shoots was subjected to a positive indirect effect of ZT in tegument and a negative effect of MeJA in the tegument (Fig. 6 b). In L. lanceolata , a negative correlation was observed between ACC in tegument and seed length. These findings show that ABA and ACC negatively affect seed growth in both species. The emergence of seedlings in L. lanceolata correlated positively with MeJA in endosperm; however, this hormone retarded growth, correlating negatively with number of leaves, number of shoots, shoot dry mass, and total dry mass. In L. lanceolata , a negative correlation was observed between ZT in endosperm and ABA in tegument, while a positive correlation was detected between ZT in tegument and ACC in tegument (Fig. 7 a). In L. lanceolata trees, emergence was influenced in a positive indirect way by MeJA in endosperm; whereas the mean time of emergence was controlled in a positive indirect way by ABA in the tegument and MeJA in endosperm, and in a direct positive way by IAA in tegument. The high budding capacity of L. lanceolata trees was directly negatively affected by the IAA in endosperm/ZT in endosperm ratio and MeJA in tegument (Fig. 7 b). Phenotypic and hormonal characteristics separated L. pisonis trees into two genetically diverse groups: I (trees 1, 2, and 6) and II (trees 3 and 5). The phenotypic characteristics of tree 4 of L. pisonis were closer to trees belonging to the species L. lanceolata trees, which were split into groups I (trees 5, 4, and 1 of L. lanceolata and tree 4 of L. pisonis ) and II (trees 2, 6, and 3) (Fig. 8 a). Molecular markers were more effective in separating the two species into two distinct groups. Cluster analysis revealed strong genetic variability between the two species. L. lanceolata trees were grouped within the same group, whereas L. pisonis trees were clustered into two distinct groups, I (1, 2, 4, and 6) and II (3 and 5), in which tree 1 of L. pisonis was the most divergent (Fig. 8 b). Low genetic variability was observed between trees within the same species, as indicated by 50.98% polymorphic bands for L. lanceolata and 69.56% for L. pisonis . Discussion The size of L. lanceolata trees is smaller when compared to L. pisonis trees, which facilitates fruit harvesting and supports the findings of Tetsumura et al. 32 , who reported that such characteristic was preferred by producers. Trees 1, 2, and 6 of L. pisonis produced numerous fruits, and this feature may be associated with a larger crown circumference, size, and density of the aerial part, as well as higher rates of carbon assimilation and dry mass accumulation 33 . Nevertheless, fruit production remains influenced also by season, location in the canopy, and microclimate (e.g., light, temperature, and rainfall) 34 . Trees of B. excelsa , belonging to the same family as L. pisonis and L. lanceolata , had their fruit yield positively correlated with the largest trunk diameter (100 cm ≤ trunk diameter < 150 cm) and with the exchange capacity of soil cations 35 . It was also observed that the growth of B. excelsa trees is strongly related to the texture of the soil where the plant is located, the topography (elevation) of the place, the chemical variables referring to the nutrients K + and Mn 2+, and the pH KCl of the soil, being evidenced that the greatest growth of trees was observed in places of higher altitude and soil with high contents of clay 36 . Determining the age of the trees was possible by studying their growth rings. L. pisonis is known to have distinct ring boundaries 37 , 38 , a characteristic also observed in L. lanceolata but not found in the literature. When considering the age of the trees, it was evident that L. pisonis demonstrates a higher variability in fruit production than L. lanceolata , which remains stable in its production rate. The observed differences suggest that L. pisonis may have higher genetic variability or experience a wider range of environmental conditions, which could lead to a more significant effect on fruit production compared to L. lanceolata . The weather conditions could influence the relationship between radial growth and fruit production when trees accumulate resources 39 . Consequently, climate could also play a crucial role in improving the availability of resources and photosynthesis capacity, or directly affecting sensitive reproductive stages. The specificities of each matrix can be combined in an allogamous reproduction system 40 and genetic background exerts a significant bearing on annual seed production. In macadamia nuts, pollen origin strongly influences the quantity and quality of fruits and seeds (e.g., the mass of the endosperm), enabling an increased harvest when superior genetic material is selected 41 . Endosperm mass, which was highest in L. pisonis 2 and L. lanceolata 3 trees, is a characteristic of great commercial interest for nuts 42 , serving as a reserve for the growing embryo. L. pisonis and L. lanceolata were propagated exclusively by seeds; however, some trees displayed a low emergence rate (tree 3 of L. pisonis = 3% and tree 3 of L. lanceolata = 60%) and low seedling vigor. These seeds have a hard and thick tegument, constituted by more than 60% lignin in L. pisonis 3 , which can hinder degradation by fungi and protrusion of the primary root 43 . In B . excelsa , genotype 606 has better physiological performance during germination (63.3%; three times higher coefficient of velocity of germination (GSC) and two and a half times higher mean velocity of germination (MVG)), mainly in terms of water imbibition, as it needs to absorb less water and achieve a higher germination percentage than the Santa Fé genotype (26.5%), in addition to a higher stomatal index in seedlings 44 . As observed by Araujo et al. 45 , L. pisonis seeds subjected to physical dormancy and lateral scarification or damage in the region adjacent to the hilum presented much higher seedling emergence rates (71%) than intact seeds (18%). Seed dormancy increases seedling production costs due to slow and uneven seedling emergence over time. In L. pisonis seeds, abnormalities such as empty seeds devoid of embryo and endosperm, cracks in the cotyledons, or desiccation in the endosperm are also common, which could explain the low germination rates in these trees 3 . Seed germination also involves controlling mechanisms by hormonal regulation. This can be seen by the antagonism between the ABA and GA 3 hormones. The ABA hormone acts mainly on the primary dormancy of seeds through the higher ABA/GA 3 concentration ratio. This dormancy is inactivated by the increase in GA 3 synthesis, which induces the release of amylase enzymes by the aleurone layer, causing a breakdown of endosperm reserves and primary root protrusion 46 . In dry corn seeds treated with ABA synthesis inhibitor (fluridone), it led to na increase in the ratio (GA 4 /ABA), which can be partly explaine by the decreased expression of ABA synthesis-related genes GRMZM2G408158 ( NCED9 ), GRMZM2G014392 ( NCED1 ), and GRMZM2G417954 ( NCED5 ) 47 . And the seeds of Benincasa hispida (Thunb.) Cogn., soaked in hydrogen-rich water (AHR, 50%), stimulated GA production by regulating GA biosynthesis genes ( BhiGA3ox , BhiGA2ox , and BhiKAO ), while it had no effect on ABA content and the expression of its biosynthesis ( BhiNCED6 ) and catabolism ( BhiCYP707A2 ) genes, but decreased the expression of ABA receptor gene ( BhiPYL ) 48 . The GA/ABA ratio determines seed dormancy or germination rather than the absolute values ​​of each hormone 49 , 50 . ABA concentrations were 5.01 times ( L. pisonis ) and 8.81 times ( L. lanceolata ) higher in the seed integument than in the endosperm. While ABA can sometimes delay germination, here, it did not retard seedling emergence, which was ≥ 70% in most tree trees. Elevated ABA accumulation in seeds from trees 6 and 4 of L. pisonis and in seeds from trees 4 and 1 can increase seed viability, although it does not prevent deterioration of the endosperm during storage. Because this hormone is a precursor of proteins abundant in late embryogenesis, it is fundamental for acquiring tolerance to embryo desiccation 51 , 52 . During seed formation, the embryo goes through successive developmental steps and hormonal changes until it reaches physiological maturity. These dynamics can be observed in the seeds of Fagopyrum tataricum , whose concentrations of IAA, ZT, and ABA reached approximately 21000, 9080, and 15000 ng g − 1 in young fruits, and 6050 (3.47 times less), 980 (9.26 times less), and 124930 ng g − 1 (83.28 times more) in their mature counterparts, respectively. These results clearly show the association between ABA and maturation or, more specifically, between embryonic phases and seed dormancy 53 . ABA and ACC were negatively correlated with seed growth parameters in both species. High concentrations of these hormones in the seeds may be associated with water deficit, a condition that induces the synthesis of ABA, ACC, and enzymes related to ethylene production (e.g., ACC synthase and ACC oxidase). Ethylene plays a fundamental role in the regulation of water loss by the aerial part, enhances water absorption by the roots, and regulates genes involved in color change, generation of free radicals, autophagy, and cell wall hydrolysis during senescence and maturation 54 . It also positively contributes to seed germination, acting on endosperm breakage and root protrusion in some species, with ACC being its precursor 5 . In the present study, ZT in tegument correlated positively with ACC in tegument in L. lanceolata . Ethylene production can positively influence gene expression of the cytokinin (IPT3) and ABA (NCED3) biosynthetic pathways, and can negatively affect those related to IAA synthesis (YUC5 and YUC6) 55 . Auxins and cytokinins control the development of meristems, with auxins promoting growth in height, and cytokinins controlling the growth of lateral buds and, hence, giving rise to ramifications 56 , 57 . Cytokinins also act by regulating seed germination, root elongation, and seed size 58 , being necessary during symbiotic association in some plants 59 . IAA is an auxin responsible for cell elongation and division, also acting in the formation of vascular tissues 5 . ZT in endosperm correlated negatively with ABA in tegument in L. lanceolata seeds. ABA and ZT exert antagonistic actions in many physiological processes, and compounds that participate in the cytokinin signaling pathway, such as type B ARRs (or ARR5), block the action of ABA-dependent SnRK2s kinase. The opposite effect is induced by ARR5 type A, which negatively affects cytokinin biosynthesis, promoting the activation of ABA-sensitive genes and phosphorylation by SnRK2s. The extent of this effect depends on the conditions the plant finds itself in, whether normal or stressful, which will then reflect on crop productivity 60 . Abiotic stresses, such as salinity and drought, reduce the productivity of some plant species. Some hormones, such as MeJA and SA, act as defense mechanisms in plants, and their exogenous application together (MeJA + SA) in seeds before sowing, reduces lipid peroxidation and the formation of hydrogen peroxide (H 2 O 2 ) 61 . JA is also involved in plant tolerance to saline, drought, cold, and heavy metals stress, increasing the expression of antioxidants and consequently decreasing reactive oxygen species 62 . MeJA is derived from JA, and its synthesis is catalyzed by jasmonic acid carboxyl methyltransferase, an enzyme subjected to ethylene inhibition 63 . JA is also involved in plant defense against pathogens and insects 64 . SA promotes photosynthesis, growth, biochemical reactions, and the synthesis of antioxidant compounds during periods of stress 63 , 65 , 66 . The present study highlights a positive correlation between seedling emergence and the accumulation of MeJA in endosperm in L. pisonis , as well as a direct ( L. pisonis ) and indirect ( L. lanceolata ) positive effect of MeJA in tegument on seedling emergence. Still, the concentration of MeJA in endosperm in L. lanceolata seeds was detrimental to seedling growth and correlated negatively with the number of leaves, number of shoots, shoot dry mass, and total dry mass. Moreover, MeJA in tegument exerted a direct negative effect on several shoots in L. pisonis and L. lanceolata seedlings. MeJA has been documented to block the development of shoots and the selective permeability of membranes in cortical root cells of Arabidopsis, which is associated with the dephosphorylation of aquaporins and consequent impairment of water flow 67 . ISSR analysis allowed the clustering of the studied trees into distinct groups. L. lanceolata trees showed less variability than L. pisonis trees, and such low polymorphism is probably related to the geographic proximity between individuals. This may not be surprising, as one of the factors favoring low genetic variability is pollination among individuals with high kinship, which may cause future problems of inbreeding. In studies with B. excelsa , genetic diversity was greater between populations (95.56%) than among individuals of the same population (2.68%). This finding suggests that it might be worthwhile to harvest seeds from geographically distant trees, to ensure the propagation of highly diverse genetic material 10 . In L. pisonis trees located in different regions of northern Espírito Santo state, the elevated rate of polymorphism (96.7%) based on 13 ISSR primers was likely the result of sampling from geographically distant specimens 3 . Overall, this study brings several contributions related to genetic diversity and phenotypic diversity of the species L. pisonis and L. lanceolata . It also addresses physiological issues of seedling germination and growth, which are fundamental for the propagation and maintenance of these genetic materials. It is an initial study based on a group of trees and can be used as a basis for generating new research for the species L. pisonis and L. lanceolata . Conclusion The greater genetic diversity observed among L. pisonis trees, when compared to L. lanceolata trees, may be related to the greater territorial distance between them. L. pisonis trees showed seedling emergence varying abruptly, between low (3%) and high (93%) values, indicating possible physiological dormancy. Seeds from L. lanceolata trees showed less variation in seedling emergence. Both species showed non-uniform seedling emergence over a long period, a factor that corroborates an increase in the production costs of seedlings in the nursery, indicating that new studies related to the breaking of physical and physiological dormancy should be carried out in order to reduce the seedling time. seedling emergence. In L. lanceolata , the mean emergence time was indirectly positively controlled by abscisic acid in the seed coat, indicating a possible dormancy controlled by ABA accumulation. The hormonal content of the seeds of both species influenced the emergence of seedlings and the growth of seedlings, indicating that new studies related to the exogenous application of growth regulators in seeds can be developed. This is an initial characterization study, which comprises important information about the species L. pisonis and L. lanceolata , mainly related to seed physiology and seedling growth, and can contribute to research related to the production of seedlings for commercial plantings and forest restoration. Future commercial nut plantations, in the long term, could lead to the construction of industries and consequently the creation of jobs. Declarations Authors' contributions RSA, CPA designed the study; CPA, TLMR, TM, IMS and TCCN performed most of the experiments; AF and APS analyzed the data; CPA, SO and MFSF molecular analysis; CPA and CEV; analysis of plant hormones and precursor; CPA, TLMR, TM, IMS, TCCN, SO, AF, JPBO, ERS, JCL, MFSF, ARS, APS, CEV, WCO and RSA scientific article writing. All authors read and approved the manuscript. Acknowledgments The authors would like to thank Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) and Fundação de Amparo à Pesquisa e Inovação do Espírito Santo (FAPES) for research funding. To the Biomolecule Analysis Nucleus (NuBioMol), belonging to the Federal University of Viçosa (UFV) and the Financiadora de Estudos e Projetos (FINEP), CNPq and the Fundação de Amparo à Pesquisa do Estado de Minas Gerais (FAPEMIG) for equipment used to perform hormonal analysis. Competing interests On behalf of all authors, the corresponding author states that there is no conflict of interest. Funding This study was funded by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) (Finance code 001), the Fundação de Amparo à Pesquisa e Inovação do Espírito Santo (FAPES) [EDITAL FAPES/CNPq N° 05/2017 - PRONEM (Programa de Apoio a Núcleos Emergentes), agreement registered in SICONV under N° 794009/2013, Process FAPES N° 72660945; EDITAL FAPES Nº 04/2021 - TAXA DE PESQUISA, Protocol N° 45837.716.19068.15062021], and the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) [Call CNPq 06/2019 - Research Productivity Grants , Process Nº 308365/2019-4, Protocol Nº 3787528332113241]. Data Availability The data that support the findings of this study are available upon reasonable request. References Sfb – Serviço Florestal Brasileiro. Florestas do Brasil em resumo: 2019. MAPA/SFB, Brasília. (2019). Available at: http://www.florestal.gov.br/documentos/publicacoes/4261-florestas-do-brasil-em-resumo-digital/file (Accessed 10 May 2020). 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The role of auxins and cytokinins in the mutualistic interaction between Arabidopsis and Piriformospora indica . Mol. PlantMicrobe Interact. 21 , 1371–1383. https://doi.org/10.1094/MPMI-21-10-1371 (2008). Huang, X. et al. The antagonistic action of abscisic acid and cytokinin signaling mediates drought stress response in Arabidopsis . Mol. Plant. 11 , 970–982. https://doi.org/10.1016/j.molp.2018.05.001 (2018). Tayyab, N. et al. Combined seed and foliar pretreatments with exogenous methyl jasmonate and salicylic acid mitigate droughtinduced stress in maize. PLoS One . 15 , e0232269. https://doi.org/10.1371/journal.pone.0232269 (2020). Kim, H., Seomun, S., Yoon, Y. & Jang, G. Jasmonic acid in plant abiotic stress tolerance and interaction with abscisic acid. Agronomy 11 , 1886. https://doi.org/10.3390/agronomy11091886 (2021). Seo, H. S. et al. Jasmonic acid carboxyl methyltransferase: a key enzyme for jasmonateregulated plant responses. Proc. Natl. Acad. Sci. USA 98, 4788–4793. (2001). https://doi.org/10.1073/pnas.081557298 FarhangiAbriz, S. & GhassemiGolezani, K. Jasmonates: mechanisms and functions in abiotic stress tolerance of plants. Biocatal. Agric. Biotechnol. 20 , 101210. https://doi.org/10.1016/j.bcab.2019.101210 (2019). Shasmita et al. Priming with salicylic acid induces defense against bacterial blight disease by modulating rice plant photosystem II and antioxidant enzymes activity. Physiol. Mol. Plant. Pathol. 108 , 101427. https://doi.org/10.1016/j.pmpp.2019.101427 (2019). Zaid, A. et al. Salicylic acid enhances nickel stress tolerance by upregulating antioxidant defense and glyoxalase systems in mustard plants. Ecotoxicol. Environ. Saf. 180 , 575–587. https://doi.org/10.1016/j.ecoenv.2019.05.042 (2019). Lee, S. H. & Zwiazek, J. J. Regulation of water transport in Arabidopsis by methyl jasmonate. Plant. Physiol. Biochem. 139 , 540–547. https://doi.org/10.1016/j.plaphy.2019.04.023 (2019). Additional Declarations No competing interests reported. Supplementary Files DendrogramSpreadsheet.xlsx ElectrophoresisL.pisonisandL.lanceolata.docx ISSRL.pisonisandL.lanceolata1.pptx ISSRL.pisonisandL.lanceolata2.pptx Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 28 Aug, 2025 Reviewers agreed at journal 19 Aug, 2025 Reviews received at journal 14 Aug, 2025 Reviewers agreed at journal 07 Aug, 2025 Reviews received at journal 03 Aug, 2025 Reviewers agreed at journal 25 Jul, 2025 Reviewers invited by journal 23 Jul, 2025 Editor assigned by journal 23 Jul, 2025 Editor invited by journal 24 Jun, 2025 Submission checks completed at journal 23 Jun, 2025 First submitted to journal 23 Jun, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Alexandre","email":"data:image/png;base64,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","orcid":"","institution":"Federal University of Espírito Santo/UFES","correspondingAuthor":true,"prefix":"","firstName":"Rodrigo","middleName":"Sobreira","lastName":"Alexandre","suffix":""}],"badges":[],"createdAt":"2025-06-11 01:23:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6866798/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6866798/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":87585290,"identity":"d93db9df-c26d-4b9b-8ef2-9ae87a825ba5","added_by":"auto","created_at":"2025-07-25 13:42:29","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1763723,"visible":true,"origin":"","legend":"\u003cp\u003eGeographic coordinates of the trees of \u003cem\u003eL. pisonis\u003c/em\u003e and \u003cem\u003eL. lanceolata\u003c/em\u003e in the different municipalities. Tree 1 Lp (19º 47' 5.49\" S and 41º 9' 16.53\" O) and Ll (20º 54' 14.458\" S and 41º 30' 37.221\" O); tree 2 Lp (19º 47' 1.045\" S and 41º 9' 18.411\" O) and Ll (20º 54' 11.909\" S and 41º 30' 36.662\" O); tree 3 Lp (20º 45' 10.195\" S and 41º 17' 25.782\" O) and Ll (20º 54' 12.151\" S and 41º 30' 36.338\" O); tree 4 Lp (20º 41' 16.82\" S and 41º 20' 28.616\" O) and Ll (20º 54' 10.938\" S and 41º 30' 35.767\" O); tree 5 Lp (20º 41' 29.895\" S and 41º 22' 6.972\" O) and Ll (20º 54' 10.598\" S and 41º 30' 35.306\" O) and tree 6 Lp (20º 47' 27.442\" S and 41º 29' 27.187\" O) and Ll (20º 54' 10.169\" S and 41º 30' 35.199\" O). These figures were prepared by the authors themselves using ArcGIS 10 Software\u003csup\u003e18\u003c/sup\u003e.\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-6866798/v1/eafebcb43781b52be101e41f.png"},{"id":87585558,"identity":"5cb4a391-acc7-4cf5-a2df-59a56e52034b","added_by":"auto","created_at":"2025-07-25 13:50:29","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1579577,"visible":true,"origin":"","legend":"\u003cp\u003eBaguettes were collected from \u003cem\u003eL. pisonis\u003c/em\u003e and \u003cem\u003eL. lanceolata\u003c/em\u003e trees to carry out dendrochronological analysis through the identification of growth rings. These figures were prepared by the authors themselves using FotoFiltre Studio X 10.14.1 Software\u003csup\u003e19 \u003c/sup\u003eand Inkscape 0.92.5 Software\u003csup\u003e20\u003c/sup\u003e.\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-6866798/v1/4a633a05c3a0894b17dd98fa.png"},{"id":87587109,"identity":"45cc42f4-faf6-4305-b48b-a8ac4f977619","added_by":"auto","created_at":"2025-07-25 14:06:29","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":744704,"visible":true,"origin":"","legend":"\u003cp\u003eClimatological variables denoting maximum temperature (Tmax, °C), average temperature (Tmed, °C), and minimum temperature (Tmin, °C) (\u003cstrong\u003ea\u003c/strong\u003e); precipitation (P, mm) and evapotranspiration (PET, mm) (\u003cstrong\u003eb\u003c/strong\u003e); as well as water deficiency (WD) and water surplus (WS) (\u003cstrong\u003ec\u003c/strong\u003e) in the different municipalities. These figures were prepared using Excel Software\u003csup\u003e21\u003c/sup\u003e and Inkscape 0.92.5 Software\u003csup\u003e20\u003c/sup\u003e.\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-6866798/v1/0424c4558cdbabe574c6f2b6.png"},{"id":87585293,"identity":"6fadd49f-e5a8-4262-bf68-3a46e2314a66","added_by":"auto","created_at":"2025-07-25 13:42:29","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1224769,"visible":true,"origin":"","legend":"\u003cp\u003eMorphology of \u003cem\u003eL. lanceolata \u003c/em\u003e(\u003cstrong\u003ea\u003c/strong\u003e) and \u003cem\u003eL. pisonis\u003c/em\u003e (\u003cstrong\u003eb\u003c/strong\u003e) trees; seeds (\u003cstrong\u003ec\u003c/strong\u003e); and seedlings at 45 (\u003cstrong\u003ed\u003c/strong\u003e, \u003cstrong\u003ee\u003c/strong\u003e), 60 (\u003cstrong\u003ef\u003c/strong\u003e, \u003cstrong\u003eg\u003c/strong\u003e), and 160 days after sowing (\u003cstrong\u003eh\u003c/strong\u003e, \u003cstrong\u003ei\u003c/strong\u003e). Morphology of pixie-type fruits (\u003cstrong\u003ej\u003c/strong\u003e-\u003cstrong\u003ek\u003c/strong\u003e) and flower (\u003cstrong\u003el\u003c/strong\u003e-\u003cstrong\u003em\u003c/strong\u003e) isolated from the inflorescence branch. (\u003cstrong\u003en\u003c/strong\u003e) Structural formulae of the hormones zeatin (ZT), 1-aminocyclopropane-1-carboxylic acid (ACC), abscisic acid (ABA), indole-3-acetic acid (IAA), salicylic acid (SA), gibberellic acid (GA\u003csub\u003e3\u003c/sub\u003e), jasmonic acid (JA) and methyl jasmonate (MeJA) present in the seed tegument and endosperm. These figures were prepared by the authors themselves using Inkscape 0.92.5 Software\u003csup\u003e20\u003c/sup\u003e.\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-6866798/v1/94debe44bd0a146ea667e23d.png"},{"id":87585327,"identity":"2a05980c-58ab-4ed1-9f68-783d492a5a8e","added_by":"auto","created_at":"2025-07-25 13:42:30","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":359028,"visible":true,"origin":"","legend":"\u003cp\u003eQuantification of endogenous levels of hormones present in the endosperm (green bars) and tegument (red bars) of mature seeds from \u003cem\u003eL. pisonis\u003c/em\u003e \u003cstrong\u003e(a\u003c/strong\u003e–\u003cstrong\u003eh\u003c/strong\u003e) and \u003cem\u003eL. lanceolata\u003c/em\u003e (\u003cstrong\u003ei\u003c/strong\u003e–\u003cstrong\u003ep\u003c/strong\u003e) trees. Legend: zeatin (ZT), 1-aminocyclopropane-1-carboxylic acid (ACC), abscisic acid (ABA), indole-3-acetic acid (IAA), salicylic acid (SA), jasmonic acid (JA) and methyl jasmonate (MeJA). \u003csup\u003e1\u003c/sup\u003eMeans followed by the same letter, uppercase for endosperm and lowercase for integument, between trees within each species do not differ by Tukey's test (\u003cem\u003ep\u0026gt;0.05\u003c/em\u003e). *\u003cem\u003ep\u0026lt;0.05\u003c/em\u003e, \u003csup\u003ens\u003c/sup\u003enot significant by the F test. These figures were prepared by the authors themselves using Excel Software\u003csup\u003e21\u003c/sup\u003e.\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-6866798/v1/0f30db3472f06761a2659652.png"},{"id":87585322,"identity":"b0327668-761c-40bc-8855-fe598fe7ce5f","added_by":"auto","created_at":"2025-07-25 13:42:30","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":126468,"visible":true,"origin":"","legend":"\u003cp\u003ePearson's correlation between seed emergence, vigor, hormones variables, and seedling growth characteristics for the species \u003cem\u003eL. pisonis\u003c/em\u003e, with the color scale referring to the negative correlation in shades of blue and the positive correlation in shades of red\u003cem\u003e \u003c/em\u003e(\u003cstrong\u003ea\u003c/strong\u003e). Path analysis shows the direct (blue arrow, large circle) and indirect effect (red arrow, small circle) of seed hormonal variables on seedling growth characteristics in \u003cem\u003eL. pisonis\u003c/em\u003e (\u003cstrong\u003eb\u003c/strong\u003e). Legend: seed length (SL, mm), smallest seed width (\u0026lt; SW, mm), largest seed width (\u0026gt; SW, mm), seed mass (SM, g), seed volume (SV, cm\u003csup\u003e3\u003c/sup\u003e), seed density (SD, g cm\u003csup\u003e-3\u003c/sup\u003e), integument thickness in the aerial part region (ITAPR, mm), integument thickness in the hilum region (ITHR, mm), emergence (E, %), emergence speed index (ESI), mean time of emergence (MTE, days), endosperm mass (EM, g), tegument mass (TM, g), length of the aerial part (LAP, cm), main root length (MRL, cm), number of lateral roots (NLR), main root diameter (MRD, mm), diameter of the lateral roots (DLR, mm), root volume (RV, cm\u003csup\u003e3\u003c/sup\u003e), root density (RD, g cm\u003csup\u003e-3\u003c/sup\u003e), number of leaves (NL), number of shoots (NS), leaf width (LW, cm), leaf thickness (LT, mm), number of stems (NST), shoot dry mass (SDM, g), dry root mass (DRM, g), Dickson's quality index (DQI), colorimetry parameters in leaf\u0026nbsp; (L*, a*, b*, C*, and H°) and Spad index. These figures were prepared by the authors themselves using R\u003csup\u003e29 \u003c/sup\u003eSoftware, using the package biotools\u003csup\u003e30, 31\u003c/sup\u003e.\u003c/p\u003e","description":"","filename":"image6.png","url":"https://assets-eu.researchsquare.com/files/rs-6866798/v1/97885106d7adf044abab46ef.png"},{"id":87585302,"identity":"e43fe141-8339-4385-8c01-69cfcb6de887","added_by":"auto","created_at":"2025-07-25 13:42:29","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":110509,"visible":true,"origin":"","legend":"\u003cp\u003ePearson's correlation between seed emergence, vigor, hormones variables, and seedling growth characteristics for the species \u003cem\u003eL. lanceolata\u003c/em\u003e, with the color scale referring to the negative correlation in shades of blue and the positive correlation in shades of red (\u003cstrong\u003ea\u003c/strong\u003e). Path analysis shows the direct (blue arrow, large circle) and indirect effect (red arrow, small circle) of seed hormonal variables on seedling growth characteristics in \u003cem\u003eL. lanceolata\u003c/em\u003e (\u003cstrong\u003eb\u003c/strong\u003e). Legend: seed length (SL, mm), smallest seed width (\u0026lt; SW, mm), largest seed width (\u0026gt; SW, mm), seed mass (SM, g), seed volume (SV, cm\u003csup\u003e3\u003c/sup\u003e), seed density (SD, g cm\u003csup\u003e-3\u003c/sup\u003e), integument thickness in the aerial part region (ITAPR, mm), integument thickness in the hilum region (ITHR, mm), emergence (E, %), emergence speed index (ESI), mean time of emergence (MTE, days), endosperm mass (EM, g), tegument mass (TM, g), length of the aerial part (LAP, cm), main root length (MRL, cm), number of lateral roots (NLR), main root diameter (MRD, mm), diameter of the lateral roots (DLR, mm), root volume (RV, cm\u003csup\u003e3\u003c/sup\u003e), root density (RD, g cm\u003csup\u003e-3\u003c/sup\u003e), number of leaves (NL), number of shoots (NS), leaf width (LW, cm), leaf thickness (LT, mm), number of stems (NST), shoot dry mass (SDM, g), dry root mass (DRM, g), Dickson's quality index (DQI), colorimetry parameters in leaf\u0026nbsp; (L*, a*, b*, C*, and H°) and Spad index. These figures were prepared by the authors themselves using R\u003csup\u003e29 \u003c/sup\u003eSoftware, using the package biotools\u003csup\u003e30, 31\u003c/sup\u003e.\u003c/p\u003e","description":"","filename":"image7.png","url":"https://assets-eu.researchsquare.com/files/rs-6866798/v1/7f6c26b8d1b53c87a6d704ed.png"},{"id":87585321,"identity":"89b8a1cc-4882-4a3b-a9f4-4a4aceb017f4","added_by":"auto","created_at":"2025-07-25 13:42:30","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":128854,"visible":true,"origin":"","legend":"\u003cp\u003eGenetic diversity determined by the Mahalanobis distance with the UPGMA method (\u003cstrong\u003ea\u003c/strong\u003e) and dendrogram obtained by the UPGMA method with the Jaccard similarity coefficient on polymorphisms for 11 ISSR primers (\u003cstrong\u003eb\u003c/strong\u003e) in trees of \u003cem\u003eL. pisonis\u003c/em\u003e (Lp1, Lp2, Lp3, Lp4, Lp5, and Lp6) and \u003cem\u003eL. lanceolata \u003c/em\u003e(Ll1, Ll2, Ll3, Ll4, Ll5, and Ll6). Legend: seed length (SL, mm), smallest seed width (\u0026lt; SW, mm), largest seed width (\u0026gt; SW, mm), seed mass (SM, g), seed volume (SV, cm\u003csup\u003e3\u003c/sup\u003e), seed density (SD, g cm\u003csup\u003e-3\u003c/sup\u003e), integument thickness in the aerial part region (ITAPR, mm), integument thickness in the hilum region (ITHR, mm), emergence (E, %), emergence speed index (ESI), mean time of emergence (MTE, days), endosperm mass (EM, g), tegument mass (TM, g), length of the aerial part (LAP, cm), main root length (MRL, cm), number of lateral roots (NLR), main root diameter (MRD, mm), diameter of the lateral roots (DLR, mm), root volume (RV, cm\u003csup\u003e3\u003c/sup\u003e), root density (RD, g cm\u003csup\u003e-3\u003c/sup\u003e), number of leaves (NL), number of shoots (NS), leaf width (LW, cm), leaf thickness (LT, mm), number of stems (NST), shoot dry mass (SDM, g), dry root mass (DRM, g), Dickson's quality index (DQI), SPAD index, indole-3-acetic acid in tegument (IAAt) and endosperm (IAAe), zeatin in tegument (ZTt) and endosperm (ZTe), abscisic acid in tegument (ABAt) in endosperm (ABAe), jasmonic acid in tegument (JAt) and endosperm (JAe), methyl jasmonate in tegument (MeJAt) and endosperm (MeJAe), salicylic acid in tegument (SAt) and endosperm (SAe), and 1-aminocyclopropane-1-carboxylic acid in tegument (ACCt) and endosperm (ACCe). These figures were prepared by the authors themselves using R\u003csup\u003e29 \u003c/sup\u003eSoftware, using the package biotools\u003csup\u003e30, 31\u003c/sup\u003e.\u003c/p\u003e","description":"","filename":"image8.png","url":"https://assets-eu.researchsquare.com/files/rs-6866798/v1/259b6a1d67d2c8745a0d22b6.png"},{"id":87588191,"identity":"f83a9de2-5452-4956-ba96-4fe4659aa0bb","added_by":"auto","created_at":"2025-07-25 14:14:34","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":7765568,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6866798/v1/eeb4ae68-272c-41b3-a2bd-b629311109cb.pdf"},{"id":87585292,"identity":"8d5bbc69-f28a-48e8-8f61-58485cd21f27","added_by":"auto","created_at":"2025-07-25 13:42:29","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":15457,"visible":true,"origin":"","legend":"","description":"","filename":"DendrogramSpreadsheet.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6866798/v1/416a1d42320cafed7c4c1b40.xlsx"},{"id":87586727,"identity":"eb60511f-de4b-40a5-a831-192cf103fd8c","added_by":"auto","created_at":"2025-07-25 13:58:29","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":10787391,"visible":true,"origin":"","legend":"","description":"","filename":"ElectrophoresisL.pisonisandL.lanceolata.docx","url":"https://assets-eu.researchsquare.com/files/rs-6866798/v1/1aa770eaa0563c848a694a73.docx"},{"id":87585299,"identity":"7c8538ee-97a8-4e4e-b5d8-c0b577427d4a","added_by":"auto","created_at":"2025-07-25 13:42:29","extension":"pptx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":1361736,"visible":true,"origin":"","legend":"","description":"","filename":"ISSRL.pisonisandL.lanceolata1.pptx","url":"https://assets-eu.researchsquare.com/files/rs-6866798/v1/3996da40c4d5c6b46ad5d122.pptx"},{"id":87585562,"identity":"83ceb7f2-1fd2-4287-a85e-d7b115d824cb","added_by":"auto","created_at":"2025-07-25 13:50:29","extension":"pptx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":2162007,"visible":true,"origin":"","legend":"","description":"","filename":"ISSRL.pisonisandL.lanceolata2.pptx","url":"https://assets-eu.researchsquare.com/files/rs-6866798/v1/74d0c9b488f0902c895966ca.pptx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Prospecting elite donor plants and characterization of endogenous hormonal status in seeds of Brazilian chestnuts (Lecythidaceae)","fulltext":[{"header":"Introduction","content":"\u003cp\u003eGlobally, Brazil is the country with the highest biodiversity and the second-largest area covered by natural forests\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. The Amazon Forest and the Atlantic Forest biodiversity hotspot harbor species of chestnuts called \u003cem\u003eLecythis pisonis\u003c/em\u003e Cambess. and \u003cem\u003eLecythis lanceolata\u003c/em\u003e Poir., whose nuts are rich in nutrients and antioxidant compounds\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. The high nutritional potential of these nuts makes them novel unconventional foods to be introduced into human consumption, mainly as a source of selenium\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. This can be observed in the trees of \u003cem\u003eBertholletia excelsa\u003c/em\u003e Humn. \u0026amp; Bonpl., which belongs to the same family (Lecythidaceae) as the species studied, whose nuts are appreciated worldwide and considered one of the main products of Amazonian extractivism\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThe lack of information related to the germination behavior and growth of seedlings of both species is the main problem of this study. This information is essential for the production of seedlings in forest nurseries, whether for reforestation purposes or for commercial purposes of non-timber resources aimed at selling nuts. Germination behavior varies depending on the species, and it is necessary to understand whether there is any type of physical or physiological impediment that hinders this process and the formation of normal seedlings, being the seed germination is related to a rigorous endogenous hormonal balance established through signaling pathways and specific genes\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThe breaking of physiological seed dormancy is mainly associated with the loss of sensitivity of abscisic acid, which acts by inactivating the transcription of genes involved in germination processes and promotes the transcription of genes responsible for the catabolism of gibberellic acid. The gibberellic acid produced in the embryo and released in the aleurone layer induces the synthesis of α-amylases and proteases that are released in the endosperm to start the synthesis of starch degradation, and its catabolism interrupts this process that allows the nutrition of the embryo\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThe hormones present in seeds also induce the growth of seedlings, through an antagonistic relationship between auxin/cytokinin. Auxins are responsible for apical dominance, height growth, and root formation, while cytokinins induce the formation of lateral shoots and participate in cell division processes\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. After the seedlings have grown, the highest quality ones should be selected for planting in the field. This selection is carried out through phenotypic characteristics of rusticity, such as the collar diameter, which usually indicates a greater ability to adapt to adverse conditions, contributing to the reduction of project costs caused by low survival\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eDuring seed harvesting, another important factor that must be analyzed is the genetic diversity of the mother trees. It is known that approximately 50% of Lecythidaceae are found in forest fragments of the Amazon rainforest, sites of auto-endemism, and extreme deforestation\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. Forest fragmentation and isolation of tree populations lead to a decrease in the genetic diversity of their descendants\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. To ensure the selection of sufficiently diverse populations, genotypic diversity of molecular markers must be considered together with phenotypic diversity\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Parent trees can be selected based on desirable phenotypes, allowing the identification of new individuals for genetic improvement programs\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. The analyses of phenotypic characteristics are efficient for a better understanding of the genotype/environment interaction, aiming at efficient use of genetic resources and, in the future, the production of young forests with improved genetic structures\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003e\u003cem\u003eL. pisonis\u003c/em\u003e trees with greater crown circumference tend to produce fruits with large seeds\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e, which is an important characteristic for the food industry, since consumers already prefer larger nuts\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. Observations in \u003cem\u003eL. pisonis\u003c/em\u003e show that extra-large fruits produce large seeds in smaller numbers\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. Mother trees spend less energy in producing small seeds when compared to large seeds. However, large seeds are more resistant to adverse environmental conditions but are often attacked by rodents\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. Large seeds can also positively influence seedling germination, vigor, and growth\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eGiven this information, the aim of this study was (1) to demarcate and phenotypically and genotypically characterize a group of trees belonging to the species \u003cem\u003eL. pisonis\u003c/em\u003e and \u003cem\u003eL. lanceolata\u003c/em\u003e; (2) biometrically and physiologically characterize its seeds; (3) understand the hormonal composition of its seeds and the effect of these hormones on germination and (4) phenotypically characterize seedlings at an initial stage of growth.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eGeographic coordinates and matrix characterization\u003c/h2\u003e\u003cp\u003eSeeds from six trees of \u003cem\u003eL. pisonis\u003c/em\u003e (Lp) and six trees of \u003cem\u003eL. lanceolata\u003c/em\u003e (Ll) were collected in the municipalities of Laranja da Terra (trees 1 and 2 of \u003cem\u003eL. pisonis\u003c/em\u003e ), Cachoeiro de Itapemirim (trees 3, 4 and 5 of \u003cem\u003eL. pisonis\u003c/em\u003e), Alegre (tree 6 of \u003cem\u003eL. pisonis\u003c/em\u003e), and Mimoso do Sul (trees 1, 2, 3, 4, 5 and 6 of \u003cem\u003eL. lanceolata\u003c/em\u003e), Esp\u0026iacute;rito Santo, Brazil (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe trees of \u003cem\u003eL. pisonis\u003c/em\u003e and \u003cem\u003eL. lanceolata\u003c/em\u003e were observed from flowering (oct/2017) until the beginning of the opening of the first fruits (oct/2018), with the opening of the pixidio indicating the ideal point of harvest. The trees were climbed with the aid of a seat belt and aluminum ladder, and all the fruits produced in 2018 were harvested with the aid of an adjustable aluminum pruner and later the total number of fruits was counted. The trees were characterized in terms of height (m) using a Suunto\u003csup\u003e\u0026reg;\u003c/sup\u003e PM-5/360PC clinometer, diameter at breast height (cm), larger canopy diameter (m), smaller crown diameter (m), and crown circumference (m) using measuring tape.\u003c/p\u003e\u003cp\u003eThe age of all trees collected was also identified through dendrochronological analyses. At least two wood samples were taken from each tree using an increment borer. The samples were obtained perpendicular to each other, measuring 0.5 mm in diameter, at a height of 1.30 m above the ground in the bark-pith direction. The collected samples were carefully polished using a variety of sandpaper, ranging from 80 to 1200 grains per square millimeter, to highlight the transverse plane. The annual rings were counted and analyzed by scanning the samples at 1200 dpi (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe temperature (\u0026deg;C), precipitation (mm), and water balance (mm) of the locations of each tree studied were analyzed, aiming to characterize the environment and explain possible results related to fruit production and endogenous concentration of hormones in the seeds. Between October 2017 and August 2018, the average annual temperatures in the harvest regions ranged from 20.08\u0026deg;C (Mimoso do Sul) to 24.21\u0026deg;C (Cachoeiro de Itapemirim) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea). Generally, temperatures were higher between September and April (rainy season). Potential evapotranspiration increased in summer (December to March) and decreased in winter (June to September) in all municipalities (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb). Rainfall increased in October (spring) and was high until the end of summer (March), resulting in a water surplus. Water deficiency was almost always positive or close to zero. The most significant increase in water deficiency was observed from May to August 2018, when evapotranspiration surpassed rainfall (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eSeed biometrics\u003c/h3\u003e\n\u003cp\u003eFor the biometric analysis of seeds from \u003cem\u003eL. pisonis\u003c/em\u003e and \u003cem\u003eL. lanceolata\u003c/em\u003e trees, four replicates with 25 seeds, i.e. a total of 100 seeds per tree, were studied, which were arranged in a completely randomized design. Seed length, seed largest width, and seed smallest width, as well as the thickness of the integument in the hilum region and aerial part, were measured with a digital caliper (Snauzer\u003csup\u003e\u0026reg;\u003c/sup\u003e, precision 0.01 mm). Seed mass, endosperm mass, and integument mass were determined using an analytical balance (Mars\u003csup\u003e\u0026reg;\u003c/sup\u003e AY220, precision 0.0001 g). Seed volume was measured by immersion in water according to Archimedes' principle (density\u003csub\u003eH2O\u003c/sub\u003e = 1 g cm\u003csup\u003e-\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e), and the seed density (g cm\u003csup\u003e-\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e) was calculated by the ratio: seed mass/seed volume.\u003c/p\u003e\n\u003ch3\u003eSeedling emergence, vigor, and phenotyping\u003c/h3\u003e\n\u003cp\u003eThe seeds of \u003cem\u003eL. pisonis\u003c/em\u003e and \u003cem\u003eL. lanceolata\u003c/em\u003e were collected from pixid type fruits, originating from inflorescences. The seeds were arranged in a randomized block design, with four replicates of 25 seeds per matrix tree, and sown in polypropylene tubes with a capacity of 280 cm\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e containing Vivato\u003csup\u003e\u0026reg;\u003c/sup\u003e substrate. The tubes were kept in a shade house covered with polyethylene mesh, which reduced the ligh t intensity by 50%. Emergence (%) was evaluated according to Brasil\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. The emergence speed index (ESI) was calculated using the formula ESI\u0026thinsp;=\u0026thinsp;E\u003csub\u003e1\u003c/sub\u003e/N\u003csub\u003e1\u003c/sub\u003e +...+ E\u003csub\u003en\u003c/sub\u003e/N\u003csub\u003en\u003c/sub\u003e, where E\u003csub\u003e1\u003c/sub\u003e and E\u003csub\u003en\u003c/sub\u003e represent the number of emerged seedlings in each count, and N\u003csub\u003e1\u003c/sub\u003e to N\u003csub\u003en\u003c/sub\u003e represents the number of days elapsed between sowing and each count\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. The mean time of emergence (MTE, days) was evaluated using the formula MTE\u0026thinsp;=\u0026thinsp;Σn\u003csub\u003ei\u003c/sub\u003et\u003csub\u003ei\u003c/sub\u003e/Σn\u003csub\u003ei\u003c/sub\u003e, where n\u003csub\u003ei\u003c/sub\u003e represents the number of germinated seeds at each count and it is the time elapsed between emergence and the last count\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. At 160 days after sowing, seedling samples were randomly selected within each repetition, the seedlings were organized in a randomized block design, consisting of four replicates with 12 seedlings each, totaling 48 seedlings (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea-n).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe characteristics evaluated in the seedlings were: the length of the aerial part (cm), main root length (cm), leaf length (cm), and leaf width (cm) were evaluated using a ruler graduated in millimeters. The collar diameter (mm) and main root diameter (mm) were measured using a digital caliper (Snauzer\u003csup\u003e\u0026reg;\u003c/sup\u003e, precision 0.01 mm). The diameter of the lateral root (mm) and leaf thickness (mm) were measured using a digital micrometer (Digimess\u003csup\u003e\u0026reg;\u003c/sup\u003e). Root volume (cm\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e) was measured by immersion in water according to Archimedes' principle (density H\u003csub\u003e2\u003c/sub\u003eO\u0026thinsp;=\u0026thinsp;1 g cm\u003csup\u003e-\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e). The number of lateral roots, number of leaves, number of shoots, and number of stems were counted. Shoot dry mass (g), dry root mass (g), and total dry mass (g) were measured in a hot-air oven (Adamo\u003csup\u003e\u0026reg;\u003c/sup\u003e) until constant weight was attained. Root density (g cm\u003csup\u003e-\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e) was calculated using the formula dry root mass/root volume. Dickson's quality index was calculated using the formula: total dry mass/(length of the aerial part/collar diameter)\u0026thinsp;+\u0026thinsp;shoot dry mass/dry root mass\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. The length of the aerial part/number of leaves, length of the aerial part/number of lateral roots, length of the aerial part/collar diameter, shoot dry mass/dry root mass, number of lateral roots/main root length, and number of shoots/main root length ratios were calculated. Colorimetry parameters in leaf (L*, a*, b*, C*, and H\u0026deg;) were measured using a CR-10 digital colorimeter (Konica Minolta\u003csup\u003e\u0026reg;\u003c/sup\u003e); whereas the SPAD index was assessed using a SPAD-502 Plus chlorophyll meter (Konica Minolta\u003csup\u003e\u0026reg;\u003c/sup\u003e).\u003c/p\u003e\n\u003ch3\u003eAnalysis of hormones/precursors in seeds\u003c/h3\u003e\n\u003cp\u003eHormonal extraction from the seed integument and endosperm was performed according to Forcat et al.\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e, with some modifications\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. Six \u003cem\u003eL. pisonis\u003c/em\u003e and six \u003cem\u003eL. lanceolata\u003c/em\u003e trees, laid out in a completely randomized design with four replicates of 0.110 g each, were used. The tegument and endosperm samples were macerated separately in methanol:isopropanol:acetic acid extraction solution (20:79:1 v:v:v) and 400 \u0026micro;L of the extract was placed in pre-cooled microtubes. The microtubes were vortexed four times for 20 s, sonicated for 10 min, placed on ice for 30 min, sonicated for another 10 min, and finally centrifuged at 13000 rpm for 10 min at 4\u0026deg;C.\u003c/p\u003e\u003cp\u003eAfter repeating the post-maceration steps, the supernatant was filtered into microtubes using syringe filters (PVDF 13 mm \u0026times; 0.22 \u0026micro;m). Samples (5 \u0026micro;L) were injected in an ultra-high-performance liquid chromatography system coupled to a triple quadrupole mass spectrometer (Agilent Technologies; model 6430). Chromatographic separation was performed using a Zorbax Eclipse Plus C18 column in series with a Zorbax SB-C18 guard column (Agilent Technologies). The solvents used were acetic acid (0.02%) in water and acetic acid (0.02%) in acetonitrile, with a flow rate of 0.3 mL min\u003csup\u003e-\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e and a temperature of 30\u0026deg;C. Electrospray ionization mass spectrometry was applied by adjusting the gas temperature to 300\u0026deg;C, nitrogen to 10 L min\u003csup\u003e-\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e, nebulizer to 35 psi, and capillary voltage to 4000 V.\u003c/p\u003e\u003cp\u003eThe peaks of gibberellic acid (GA\u003csub\u003e3\u003c/sub\u003e), indole-3-acetic acid (IAA), zeatin (ZT), abscisic acid (ABA), jasmonic acid (JA), methyl jasmonate (MeJA), salicylic acid (SA), and the ethylene precursor 1-aminocyclopropane-1-carboxylic acid (ACC) were obtained. Multiple reaction monitoring allowed for the individual mass to be monitored via molecular fragmentation tests: ZT (220/136), ACC (102.1/56.2), ABA (263/153), IAA (176/130), SA (137/93), GA\u003csub\u003e3\u003c/sub\u003e (345/142.9), and JA (209/59). Scanning was carried out in positive (ZT, IAA, and ACC) and negative (ABA, SA, GA\u003csub\u003e3\u003c/sub\u003e, and JA) modes; absolute quantification was based on a calibration curve (0.1 to 200 ng) constructed with the standard of each hormone. The area of each peak was derived using Skyline\u003csup\u003e\u0026reg;\u003c/sup\u003e Software, and the masses were subsequently calculated in ng g\u003csup\u003e-\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e of fresh mass, using the equation Y\u0026thinsp;=\u0026thinsp;X, where Y is the peak area.\u003c/p\u003e\n\u003ch3\u003eGenotyping of inter simple sequence repeat (ISSR) markers\u003c/h3\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eGenomic DNA extraction\u003c/h2\u003e\u003cp\u003eDNA was extracted from the leaves of \u003cem\u003eL. pisonis\u003c/em\u003e and \u003cem\u003eL. lanceolata\u003c/em\u003e trees, following maceration in liquid nitrogen according to Doyle and Doyle\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. Macerated tissue (50 mg) was transferred to microtubes containing 700 \u0026micro;L of 200 mM Tris-HCl (pH 7.5), 288 mM NaCl, 25 mM cetyltrimethylammonium bromide, 0.5% sodium dodecyl sulfate, 0.2% beta-mercaptoethanol, and 1% polyvinylpyrrolidone.\u003c/p\u003e\u003cp\u003eThe samples were placed in a dry bath for 30 min at 65\u0026deg;C and homogenized every 10 min. Next, 650 \u0026micro;L of chloroform:isoamyl alcohol 24:1 (v:v) was added, the samples were homogenized for 5 min, and centrifuged at 12000 rpm for 10 min. The supernatant was decanted, and the extraction plus centrifugation steps were repeated twice.\u003c/p\u003e\u003cp\u003eDNA was precipitated with ice-cold isopropanol and 230 \u0026micro;L of ammonium acetate and then centrifuged at 12000 rpm for 10 min. The DNA precipitate was washed three times with 250 \u0026micro;L of 70% alcohol and centrifuged at 12000 rpm for 3 min. The samples were then placed in a dry bath and resuspended in 40 \u0026micro;L TE buffer with RNase (40 \u0026micro;g mL\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), followed by incubation at 37\u0026deg;C for 30 min.\u003c/p\u003e\u003cp\u003eA Nanodrop 2000 Spectrophotometer (Thermo Scientific\u0026reg;) was used to analyze the quality and quantity of DNA. DNA integrity was analyzed on 1.2% agarose gels using a Bio-Rad GelDoc\u0026trade; XR photo-documenter.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eDNA amplification and electrophoresis\u003c/h3\u003e\n\u003cp\u003eAfter extraction of genomic DNA, amplification and electrophoresis were performed as described by Rosa et al.\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e, with some modifications. The following 11 ISSR primers (with their respective ringing temperatures indicated in parenthesis) were used: UBC 841, UBC 852, UBC 853, UBC 868, UBC 873, UBC 880, UBC 812, and UBC 818 (50\u0026deg;C); UBC 808, UBC 826, and UBC 811 (56\u0026deg;C).\u003c/p\u003e\u003cp\u003eAmplification conditions were as follows: 1\u0026times; buffer; 1 U Taq DNA polymerase in 0.2 \u0026micro;L; 0.8 \u0026micro;M primer, 0.8 mM dNTPs, 2 mM MgCl\u003csub\u003e2\u003c/sub\u003e; 7 ng genomic DNA, and 7.8 \u0026micro;L H\u003csub\u003e2\u003c/sub\u003eO for a final volume of 15 \u0026micro;L. Amplification was carried out in a Veriti 96-Well Thermal Cycler (Applied Biosystems\u0026reg;) with the following program: 4 min denaturation at 94\u0026deg;C, followed by 40 cycles of 1 min at 94\u0026deg;C for denaturation, 1 min at T \u0026deg;C for specific annealing of each primer, 1 min at 72\u0026deg;C for extension, and 5 min at 72\u0026deg;C for the final extension step.\u003c/p\u003e\u003cp\u003eThe amplification products were separated on a 1.2% agarose gel run at 80 V for 2 h, stained with GelRed\u0026reg; dye, and documented on a GelDoc\u0026trade; XR.\u003c/p\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eAnalysis of variance and Tukey\u0026rsquo;s test (\u003cem\u003ep\u0026thinsp;\u0026gt;\u0026thinsp;0.05\u003c/em\u003e) were performed for the completely randomized design and randomized block design experiments, the F test (\u003cem\u003ep\u0026thinsp;\u0026gt;\u0026thinsp;0.05\u003c/em\u003e) for the hormonal characterization of the integument and endosperm, and Pearson correlation for comparison of all parameters. ISSR data were fed into a Jaccard dissimilarity matrix and grouped by the unweighted pair group method with arithmetic mean (UPGMA) to obtain genetic similarity estimates. Phenotypic and hormonal diversity was estimated using phenotypic and hormonal characteristics analyzed by the Mahalanobis dissimilarity matrix and the UPGMA.\u003c/p\u003e\u003cp\u003ePath analysis based on the estimated Pearson correlation coefficients (rxy) was performed in R\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e, using the package biotools\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e, to examine the direct and indirect effects of a group of independent variables over dependent variables. In the first group, the independent variables indole-3-acetic acid, zeatin, abscisic acid, and methyl jasmonate in tegument and endosperm were coupled to the dependent variables emergence, emergence speed index, and mean time of emergence. In another group of independent variables, indole-3-acetic acid in tegument and endosperm, zeatin in tegument and endosperm, indole-3-acetic acid in tegument/zeatin in tegument ratio, indole-3-acetic acid in endosperm/zeatin in endosperm ratio, methyl jasmonate in tegument and endosperm were coupled to number of shoots as dependent variable. The following variation was found: R_squared: 0.851 to 0.998 and residual effect: 0.046 to 0.385.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eThe height of \u003cem\u003eL. pisonis\u003c/em\u003e trees varied between 13.68 (tree 5) and 36.68 m (tree 4), with the highest diameter at breast height and crown circumference values observed in trees 1 (91.99 cm and 62.83 m) and 2 (70.35 cm and 56.55 m, respectively). Compared to other \u003cem\u003eL. pisonis\u003c/em\u003e trees, which produced between 23 and 51 fruits, trees 1 and 2 yielded 300 and 200 fruits, respectively. \u003cem\u003eL. lanceolata\u003c/em\u003e trees were smaller in size, ranging from 8 (tree 5) to 14 m (tree 6), with tree 6 displaying the largest diameter at breast height (56.50 cm), crown circumference (43.35 m), and number of fruits produced (126 fruits) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The age of \u003cem\u003eL. pisonis\u003c/em\u003e trees ranged from 16 to 28 years while \u003cem\u003eL. lanceolata\u003c/em\u003e trees ranged from 18 to 52 years old. \u003cem\u003eL. pisonis\u003c/em\u003e, despite having younger trees, shows a wider range of fruit production, varying from 23 to 300 fruits as the trees age. In contrast, \u003cem\u003eL. lanceolata\u003c/em\u003e, with older trees, maintains a more consistent production over time, with fruit numbers ranging from 20 to 126.\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\u003eCharacterization of growth of trees from \u003cem\u003eL. pisonis\u003c/em\u003e and \u003cem\u003eL. lanceolata\u003c/em\u003e in terms of height (H, m), diameter at breast height (DBH, cm), larger crown diameter (CD \u0026gt;, m), smaller crown diameter (CD \u0026lt;, m), crown circumference (CC, m), and number of fruits produced per tree (NFT)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"9\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"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=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTrees\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eH\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eDBH\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eCD \u0026gt;\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eCD \u0026lt;\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eCC\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eNFT\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003e\u003cem\u003eL. pisonis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e32.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e91.99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e19.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e21.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e62.83\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e300\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e28\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e23.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e70.35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e19.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e17.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e56.55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e200\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e25\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e18.68\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e33.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e12.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e8.30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e31.89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e51\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e21\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e36.68\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e51.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e19.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e12.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e49.95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e16\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e13.68\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e27.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e10.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e7.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e27.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e16\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e18.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e91.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e17.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e15.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e50.26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e23\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMean\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e23.75\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e60.85\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e16.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e13.55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e46.54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e104.66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e21.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003e\u003cem\u003eL. lanceolata\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e10.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e28.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e8.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e8.30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e26.39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e10.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e19.60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e6.60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e6.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e20.58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e18\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e10.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e21.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e9.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e8.90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e28.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e10.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e20.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e8.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e7.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e24.97\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e24\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e8.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e20.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e7.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e7.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e23.56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e23\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e14.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e56.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e14.30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e13.30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e43.35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e126\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e52\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMean\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e10.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e27.77\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e9.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e8.55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e27.82\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e53.66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e26.17\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eAs shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, the highest seedling emergence (93%) and emergence speed index of seedlings were observed in the 1 tree of \u003cem\u003eL. pisonis\u003c/em\u003e after 53 days. Emergence was similar in the 2 trees of \u003cem\u003eL. pisonis\u003c/em\u003e (88%), but the emergence speed index was lower, causing the mean time of emergence to be delayed to 68 days. Additionally, \u003cem\u003eL. pisonis\u003c/em\u003e 2 trees showed elevated seed mass (7.70 g), seed volume (7.90 cm\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e), and endosperm mass (4.62 g). Endosperm mass was also high in the 3 (4.17 g) and 5 (4.34 g) trees of \u003cem\u003eL. pisonis\u003c/em\u003e.\u003c/p\u003e\u003cp\u003eAmong \u003cem\u003eL. lanceolata\u003c/em\u003e trees, seedling emergence was greatest in 1, 2, 4, 5, and 6 (Emergence\u003csub\u003eMean\u003c/sub\u003e = 81.4%). Notably, tree 5 showed the highest seed vigor, with a mean time of emergence of only 51.58 days. The 3 trees exhibited the lowest seedling emergence (60%); however, the seeds of this tree displayed the highest seed mass (9.16 g) and endosperm mass (4.51 g) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), which are important characteristics for the chestnut market.\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\u003eEmergence (E, %), emergence speed index (ESI), mean time of emergence (MTE, days), seed mass (SM, g), endosperm mass (EM, g), tegument mass (TM, g), seed volume (SV, cm\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e), seed density (SD, g cm\u003csup\u003e-\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e), seed length (SL, mm), smaller seed width (\u0026lt;\u0026thinsp;SW, mm), larger seed width (\u0026gt;\u0026thinsp;SW, mm), tegument thickness in the aerial part region (ITAPR, mm) and tegument thickness in the hilum region (ITHR, mm) of seeds from different trees of \u003cem\u003eL. pisonis\u003c/em\u003e and \u003cem\u003eL. lanceolata\u003c/em\u003e\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"9\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTrees\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eE\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eESI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eMTE\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eSM\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eEM\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eTM\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003eSV\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003e\u003cem\u003eL. pisonis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e93.00a\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.45a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e53.75ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e5.87c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e3.58cd\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e2.06c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e6.08c\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e88.00ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.38b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e62.25a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e7.70a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e4.62a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e2.90ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e7.90a\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.00e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.01e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e28.50b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e6.86b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e4.17abc\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e2.42bc\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e7.22b\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e62.67c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.30c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e54.67ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e4.03d\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e3.20d\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e2.29c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e4.13d\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e46.67d\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.21d\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e59.00ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e5.47c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e4.34ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e3.29a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e6.58bc\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e81.33b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.44a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e48.65ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e5.96c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e3.69bcd\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e2.51bc\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e6.02c\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003e\u003cem\u003eL. lanceolata\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e80.00a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.34b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e63.80bc\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e6.05c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e3.32b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e3.08bc\u003c/p\u003e\u003c/td\u003e\u003ctd 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rowspan=\"6\"\u003e\u003cp\u003e\u003cem\u003eL. pisonis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.97ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e36.67d\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e17.92bc\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e21.97ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.95ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e2.25\u003csup\u003ens\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.98ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e38.66c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e18.67ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e22.72a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.80b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e2.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.95ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e43.98a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e17.83c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e21.22b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.77b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e2.24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.13a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e31.37e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e15.24d\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e19.87c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2.15ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e2.48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.83b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e42.11b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e18.99a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e22.50a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2.60a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e2.68\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.99ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e36.52d\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e17.32c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e21.04b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2.00ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e2.60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003e\u003cem\u003eL. lanceolata\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.92ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e35.88c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e18.22b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e22.99ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2.59ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e3.22ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.77c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e42.75b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e21.23a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e23.55ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2.39abc\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e2.87bc\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.92ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e43.32b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e20.98a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e22.65b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2.29bc\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e2.64c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.95a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e33.57d\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e15.84c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e19.11c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2.06c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e2.51c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.94a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e35.75c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e16.93bc\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e19.16c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2.12c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e2.49c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.89b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e45.54a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e20.90a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e24.52a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2.72a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e3.29a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003eMeans followed by the same letter in the column do not differ by Tukey's test (\u003cem\u003ep\u0026thinsp;\u0026gt;\u0026thinsp;0.05\u003c/em\u003e) between \u003cem\u003eL. pisonis\u003c/em\u003e and \u003cem\u003eL. lanceolata\u003c/em\u003e.\u003c/p\u003e\u003cp\u003eFor all \u003cem\u003eL. pisonis\u003c/em\u003e trees, there is a higher IAA/ZT ratio and a higher concentration of ACC in the endosperm of the seeds when compared to the tegument. ABA concentrations are higher in the tegument of all seeds when compared to the endosperm. JA concentrations were higher in the tegument, except for seeds from tree 1. MeJA concentrations were also higher in the seed tegument, except for seeds from 2 and 3 trees. The SA also obtained higher concentrations in the seeds tegument, except for the 4 and 6 trees (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea-h).\u003c/p\u003e\u003cp\u003eFor the species \u003cem\u003eL. lanceolata\u003c/em\u003e, the IAA/ZT ratio was higher in the endosperm of seeds from most trees, except for trees 2 and 3. The concentration of ABA was higher in the seed tegument of all trees about the endosperm. The concentrations of SA and ACC were higher in the endosperm of all seeds when compared to the tegument. JA was superior in the endosperm of most trees studied, except for trees 1 and 3. For MeJA, the trees with the highest concentrations in the seed endosperm were 1, 2, and 4 and in the tegument were 3, 5, and 6 (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ei-p).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003ePhenotyping of seedlings at 160 days after sowing revealed an average length of the aerial part of 42.64 cm and a main root length of 13.12 cm for \u003cem\u003eL. pisonis\u003c/em\u003e, and 39.21 and 14.08 cm for \u003cem\u003eL. lanceolata\u003c/em\u003e, respectively. Tree 1 of \u003cem\u003eL. pisonis\u003c/em\u003e showed the highest SPAD index in its seedlings, although it did not differ statistically from trees 2, 3, 5, and 6. For the species \u003cem\u003eL. lanceolata\u003c/em\u003e, trees 3 and 6 attained the highest SPAD indices.\u003c/p\u003e\u003cp\u003eIn \u003cem\u003eL. pisonis\u003c/em\u003e, the seedlings of the 1, 3, 4, 5, and 6 trees did not differ statistically from each other and had a mean number of lateral roots of 25. In \u003cem\u003eL. lanceolata\u003c/em\u003e, seedlings from seeds of trees 2 and 3, reached the highest number of lateral roots (mean\u0026thinsp;=\u0026thinsp;21.58), although these values did not differ statistically from the seedlings from seeds of trees 1 and 4. Number of shoots was 22 times higher in seedlings of the \u003cem\u003eL. lanceolata\u003c/em\u003e than in seedlings of the \u003cem\u003eL. pisonis\u003c/em\u003e. The low capacity for natural emergence of shoots in \u003cem\u003eL. pisonis\u003c/em\u003e seedlings was reflected in the number of leaves value, with an average of 18 leaves per seedling (no statistical difference between the studied trees). In \u003cem\u003eL. lanceolata\u003c/em\u003e, the highest number of 127 leaves was observed in seedlings from seeds of tree 3 (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\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\u003ePhenotyping of seedlings at 160 days after sowing in \u003cem\u003eL. pisonis\u003c/em\u003e and \u003cem\u003eL. lanceolata\u003c/em\u003e trees. The following morphological parameters were evaluated: length of the aerial part (LAP, cm), main root length (MRL, cm), collar diameter (CD, mm), number of lateral roots (NLR), main root diameter (MRD, mm), the diameter of the lateral roots (DLR, mm), root volume (RV, cm\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e), root density (RD, g cm\u003csup\u003e-\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e), number of leaves (NL), number of shoots (NS), leaf length (LL, cm), leaf width (LW, cm), leaf thickness (LT, mm), number of stems (NST), shoot dry mass (SDM, g), dry root mass (DRM, g), total dry mass (TDM, g), Dickson's quality index (DQI), colorimetry (L*, a*, b*, C*, and H\u0026deg;), SPAD index, as well as LAP/NL, LAP/NLR, LAP/CD, SDM/DRM, NLR/MRL, and NS/MRL ratios\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=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTrees\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eLAP\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMRL\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eCD\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eLAP/CD\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eLAP/NL\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eLAP/NLR\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003e\u003cem\u003eL. pisonis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e44.01ab\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" 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colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTrees\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSPAD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eL*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ea*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eb*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eC*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eH\u0026deg;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003e\u003cem\u003eL. pisonis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e35.88a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e33.32\u003csup\u003ens\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-10.92a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e20.86b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e23.47b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e118.41\u003csup\u003ens\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e34.89ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e34.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-11.75ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e21.97ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e24.99ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e119.40\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e34.37ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e33.95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-10.89a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e22.18ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e24.61ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e116.18\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e31.42b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e35.77\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-12.63b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e24.27a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e27.25a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e115.12\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e34.44ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e33.81\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-11.50ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e20.58b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e23.57b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e119.74\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e34.97ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e33.51\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-11.08a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e20.37b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e23.31b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e118.77\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003e\u003cem\u003eL. lanceolata\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e30.33b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e36.21ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-10.86bc\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e25.05a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e27.30ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e113.68abc\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e30.19b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e36.11ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-11.18c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e24.11abc\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e26.69ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e116.10a\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e34.99a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e34.77b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-10.42ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e21.44c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e23.92c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e116.02ab\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e29.12b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e38.16a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-10.57abc\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e25.64a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e27.68a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e112.50c\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e29.18b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e37.25a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-10.21a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e24.44ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e26.43abc\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e113.26bc\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e33.40a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e34.63b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-10.39ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e22.14bc\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e24.71bc\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e115.19abc\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003eMeans followed by the same letter in the column do not differ by Tukey's test (\u003cem\u003ep\u0026thinsp;\u0026gt;\u0026thinsp;0.05\u003c/em\u003e) for \u003cem\u003eL. pisonis\u003c/em\u003e and \u003cem\u003eL. lanceolata\u003c/em\u003e.\u003c/p\u003e\u003cp\u003eABA in endosperm in \u003cem\u003eL. pisonis\u003c/em\u003e seeds was negatively correlated with seed volume and seed mass. \u003cem\u003eL. pisonis\u003c/em\u003e trees showed a positive correlation between the IAA/zeatin ratio in endosperm and ACC in endosperm (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ea). In \u003cem\u003eL. pisonis\u003c/em\u003e trees, path analysis revealed that emergence and emergence speed index responded to a positive direct effect of ABA in tegument and MeJA in tegument, a negative direct effect of ZT in endosperm, and a negative indirect effect of IAA in tegument. The number of shoots was subjected to a positive indirect effect of ZT in tegument and a negative effect of MeJA in the tegument (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eb).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eIn \u003cem\u003eL. lanceolata\u003c/em\u003e, a negative correlation was observed between ACC in tegument and seed length. These findings show that ABA and ACC negatively affect seed growth in both species. The emergence of seedlings in \u003cem\u003eL. lanceolata\u003c/em\u003e correlated positively with MeJA in endosperm; however, this hormone retarded growth, correlating negatively with number of leaves, number of shoots, shoot dry mass, and total dry mass. In \u003cem\u003eL. lanceolata\u003c/em\u003e, a negative correlation was observed between ZT in endosperm and ABA in tegument, while a positive correlation was detected between ZT in tegument and ACC in tegument (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003ea).\u003c/p\u003e\u003cp\u003eIn \u003cem\u003eL. lanceolata\u003c/em\u003e trees, emergence was influenced in a positive indirect way by MeJA in endosperm; whereas the mean time of emergence was controlled in a positive indirect way by ABA in the tegument and MeJA in endosperm, and in a direct positive way by IAA in tegument. The high budding capacity of \u003cem\u003eL. lanceolata\u003c/em\u003e trees was directly negatively affected by the IAA in endosperm/ZT in endosperm ratio and MeJA in tegument (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eb).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003ePhenotypic and hormonal characteristics separated \u003cem\u003eL. pisonis\u003c/em\u003e trees into two genetically diverse groups: I (trees 1, 2, and 6) and II (trees 3 and 5). The phenotypic characteristics of tree 4 of \u003cem\u003eL. pisonis\u003c/em\u003e were closer to trees belonging to the species \u003cem\u003eL. lanceolata\u003c/em\u003e trees, which were split into groups I (trees 5, 4, and 1 of \u003cem\u003eL. lanceolata\u003c/em\u003e and tree 4 of \u003cem\u003eL. pisonis\u003c/em\u003e) and II (trees 2, 6, and 3) (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003ea). Molecular markers were more effective in separating the two species into two distinct groups. Cluster analysis revealed strong genetic variability between the two species. \u003cem\u003eL. lanceolata\u003c/em\u003e trees were grouped within the same group, whereas \u003cem\u003eL. pisonis\u003c/em\u003e trees were clustered into two distinct groups, I (1, 2, 4, and 6) and II (3 and 5), in which tree 1 of \u003cem\u003eL. pisonis\u003c/em\u003e was the most divergent (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eb). Low genetic variability was observed between trees within the same species, as indicated by 50.98% polymorphic bands for \u003cem\u003eL. lanceolata\u003c/em\u003e and 69.56% for \u003cem\u003eL. pisonis\u003c/em\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe size of \u003cem\u003eL. lanceolata\u003c/em\u003e trees is smaller when compared to \u003cem\u003eL. pisonis\u003c/em\u003e trees, which facilitates fruit harvesting and supports the findings of Tetsumura et al.\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e, who reported that such characteristic was preferred by producers. Trees 1, 2, and 6 of \u003cem\u003eL. pisonis\u003c/em\u003e produced numerous fruits, and this feature may be associated with a larger crown circumference, size, and density of the aerial part, as well as higher rates of carbon assimilation and dry mass accumulation\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. Nevertheless, fruit production remains influenced also by season, location in the canopy, and microclimate (e.g., light, temperature, and rainfall)\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. Trees of \u003cem\u003eB. excelsa\u003c/em\u003e, belonging to the same family as \u003cem\u003eL. pisonis\u003c/em\u003e and \u003cem\u003eL. lanceolata\u003c/em\u003e, had their fruit yield positively correlated with the largest trunk diameter (100 cm\u0026thinsp;\u0026le;\u0026thinsp;trunk diameter\u0026thinsp;\u0026lt;\u0026thinsp;150 cm) and with the exchange capacity of soil cations\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. It was also observed that the growth of \u003cem\u003eB. excelsa\u003c/em\u003e trees is strongly related to the texture of the soil where the plant is located, the topography (elevation) of the place, the chemical variables referring to the nutrients K\u003csup\u003e+\u003c/sup\u003e and Mn\u003csup\u003e2+,\u003c/sup\u003e and the pH\u003csub\u003eKCl\u003c/sub\u003e of the soil, being evidenced that the greatest growth of trees was observed in places of higher altitude and soil with high contents of clay\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eDetermining the age of the trees was possible by studying their growth rings. \u003cem\u003eL. pisonis\u003c/em\u003e is known to have distinct ring boundaries\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e, a characteristic also observed in \u003cem\u003eL. lanceolata\u003c/em\u003e but not found in the literature. When considering the age of the trees, it was evident that \u003cem\u003eL. pisonis\u003c/em\u003e demonstrates a higher variability in fruit production than \u003cem\u003eL. lanceolata\u003c/em\u003e, which remains stable in its production rate. The observed differences suggest that \u003cem\u003eL. pisonis\u003c/em\u003e may have higher genetic variability or experience a wider range of environmental conditions, which could lead to a more significant effect on fruit production compared to \u003cem\u003eL. lanceolata\u003c/em\u003e. The weather conditions could influence the relationship between radial growth and fruit production when trees accumulate resources\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e. Consequently, climate could also play a crucial role in improving the availability of resources and photosynthesis capacity, or directly affecting sensitive reproductive stages.\u003c/p\u003e\u003cp\u003eThe specificities of each matrix can be combined in an allogamous reproduction system\u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e and genetic background exerts a significant bearing on annual seed production. In macadamia nuts, pollen origin strongly influences the quantity and quality of fruits and seeds (e.g., the mass of the endosperm), enabling an increased harvest when superior genetic material is selected\u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e. Endosperm mass, which was highest in \u003cem\u003eL. pisonis\u003c/em\u003e 2 and \u003cem\u003eL. lanceolata\u003c/em\u003e 3 trees, is a characteristic of great commercial interest for nuts\u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e, serving as a reserve for the growing embryo.\u003c/p\u003e\u003cp\u003e\u003cem\u003eL. pisonis\u003c/em\u003e and \u003cem\u003eL. lanceolata\u003c/em\u003e were propagated exclusively by seeds; however, some trees displayed a low emergence rate (tree 3 of \u003cem\u003eL. pisonis\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3% and tree 3 of \u003cem\u003eL. lanceolata\u003c/em\u003e\u0026thinsp;=\u0026thinsp;60%) and low seedling vigor. These seeds have a hard and thick tegument, constituted by more than 60% lignin in \u003cem\u003eL. pisonis\u003c/em\u003e\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e, which can hinder degradation by fungi and protrusion of the primary root\u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e. In \u003cem\u003eB\u003c/em\u003e. \u003cem\u003eexcelsa\u003c/em\u003e, genotype 606 has better physiological performance during germination (63.3%; three times higher coefficient of velocity of germination (GSC) and two and a half times higher mean velocity of germination (MVG)), mainly in terms of water imbibition, as it needs to absorb less water and achieve a higher germination percentage than the Santa F\u0026eacute; genotype (26.5%), in addition to a higher stomatal index in seedlings\u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e. As observed by Araujo et al.\u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e, \u003cem\u003eL. pisonis\u003c/em\u003e seeds subjected to physical dormancy and lateral scarification or damage in the region adjacent to the hilum presented much higher seedling emergence rates (71%) than intact seeds (18%). Seed dormancy increases seedling production costs due to slow and uneven seedling emergence over time. In \u003cem\u003eL. pisonis\u003c/em\u003e seeds, abnormalities such as empty seeds devoid of embryo and endosperm, cracks in the cotyledons, or desiccation in the endosperm are also common, which could explain the low germination rates in these trees\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eSeed germination also involves controlling mechanisms by hormonal regulation. This can be seen by the antagonism between the ABA and GA\u003csub\u003e3\u003c/sub\u003e hormones. The ABA hormone acts mainly on the primary dormancy of seeds through the higher ABA/GA\u003csub\u003e3\u003c/sub\u003e concentration ratio. This dormancy is inactivated by the increase in GA\u003csub\u003e3\u003c/sub\u003e synthesis, which induces the release of amylase enzymes by the aleurone layer, causing a breakdown of endosperm reserves and primary root protrusion\u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e. In dry corn seeds treated with ABA synthesis inhibitor (fluridone), it led to na increase in the ratio (GA\u003csub\u003e4\u003c/sub\u003e/ABA), which can be partly explaine by the decreased expression of ABA synthesis-related genes \u003cem\u003eGRMZM2G408158\u003c/em\u003e (\u003cem\u003eNCED9\u003c/em\u003e), \u003cem\u003eGRMZM2G014392\u003c/em\u003e (\u003cem\u003eNCED1\u003c/em\u003e), and \u003cem\u003eGRMZM2G417954\u003c/em\u003e (\u003cem\u003eNCED5\u003c/em\u003e)\u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e. And the seeds of \u003cem\u003eBenincasa hispida\u003c/em\u003e (Thunb.) Cogn., soaked in hydrogen-rich water (AHR, 50%), stimulated GA production by regulating GA biosynthesis genes (\u003cem\u003eBhiGA3ox\u003c/em\u003e, \u003cem\u003eBhiGA2ox\u003c/em\u003e, and \u003cem\u003eBhiKAO\u003c/em\u003e), while it had no effect on ABA content and the expression of its biosynthesis (\u003cem\u003eBhiNCED6\u003c/em\u003e) and catabolism (\u003cem\u003eBhiCYP707A2\u003c/em\u003e) genes, but decreased the expression of ABA receptor gene (\u003cem\u003eBhiPYL\u003c/em\u003e)\u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e. The GA/ABA ratio determines seed dormancy or germination rather than the absolute values ​​of each hormone\u003csup\u003e\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e,\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eABA concentrations were 5.01 times (\u003cem\u003eL. pisonis\u003c/em\u003e) and 8.81 times (\u003cem\u003eL. lanceolata\u003c/em\u003e) higher in the seed integument than in the endosperm. While ABA can sometimes delay germination, here, it did not retard seedling emergence, which was \u0026ge;\u0026thinsp;70% in most tree trees. Elevated ABA accumulation in seeds from trees 6 and 4 of \u003cem\u003eL. pisonis\u003c/em\u003e and in seeds from trees 4 and 1 can increase seed viability, although it does not prevent deterioration of the endosperm during storage. Because this hormone is a precursor of proteins abundant in late embryogenesis, it is fundamental for acquiring tolerance to embryo desiccation\u003csup\u003e\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e,\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eDuring seed formation, the embryo goes through successive developmental steps and hormonal changes until it reaches physiological maturity. These dynamics can be observed in the seeds of \u003cem\u003eFagopyrum tataricum\u003c/em\u003e, whose concentrations of IAA, ZT, and ABA reached approximately 21000, 9080, and 15000 ng g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e in young fruits, and 6050 (3.47 times less), 980 (9.26 times less), and 124930 ng g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e (83.28 times more) in their mature counterparts, respectively. These results clearly show the association between ABA and maturation or, more specifically, between embryonic phases and seed dormancy\u003csup\u003e\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eABA and ACC were negatively correlated with seed growth parameters in both species. High concentrations of these hormones in the seeds may be associated with water deficit, a condition that induces the synthesis of ABA, ACC, and enzymes related to ethylene production (e.g., ACC synthase and ACC oxidase). Ethylene plays a fundamental role in the regulation of water loss by the aerial part, enhances water absorption by the roots, and regulates genes involved in color change, generation of free radicals, autophagy, and cell wall hydrolysis during senescence and maturation\u003csup\u003e\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e. It also positively contributes to seed germination, acting on endosperm breakage and root protrusion in some species, with ACC being its precursor\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eIn the present study, ZT in tegument correlated positively with ACC in tegument in \u003cem\u003eL. lanceolata\u003c/em\u003e. Ethylene production can positively influence gene expression of the cytokinin (IPT3) and ABA (NCED3) biosynthetic pathways, and can negatively affect those related to IAA synthesis (YUC5 and YUC6)\u003csup\u003e\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u003c/sup\u003e. Auxins and cytokinins control the development of meristems, with auxins promoting growth in height, and cytokinins controlling the growth of lateral buds and, hence, giving rise to ramifications\u003csup\u003e\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u003c/sup\u003e. Cytokinins also act by regulating seed germination, root elongation, and seed size\u003csup\u003e\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u003c/sup\u003e, being necessary during symbiotic association in some plants\u003csup\u003e\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e\u003c/sup\u003e. IAA is an auxin responsible for cell elongation and division, also acting in the formation of vascular tissues\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eZT in endosperm correlated negatively with ABA in tegument in \u003cem\u003eL. lanceolata\u003c/em\u003e seeds. ABA and ZT exert antagonistic actions in many physiological processes, and compounds that participate in the cytokinin signaling pathway, such as type B ARRs (or ARR5), block the action of ABA-dependent SnRK2s kinase. The opposite effect is induced by ARR5 type A, which negatively affects cytokinin biosynthesis, promoting the activation of ABA-sensitive genes and phosphorylation by SnRK2s. The extent of this effect depends on the conditions the plant finds itself in, whether normal or stressful, which will then reflect on crop productivity\u003csup\u003e\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eAbiotic stresses, such as salinity and drought, reduce the productivity of some plant species. Some hormones, such as MeJA and SA, act as defense mechanisms in plants, and their exogenous application together (MeJA\u0026thinsp;+\u0026thinsp;SA) in seeds before sowing, reduces lipid peroxidation and the formation of hydrogen peroxide (H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e)\u003csup\u003e\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e\u003c/sup\u003e. JA is also involved in plant tolerance to saline, drought, cold, and heavy metals stress, increasing the expression of antioxidants and consequently decreasing reactive oxygen species\u003csup\u003e\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u003c/sup\u003e. MeJA is derived from JA, and its synthesis is catalyzed by jasmonic acid carboxyl methyltransferase, an enzyme subjected to ethylene inhibition\u003csup\u003e\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e\u003c/sup\u003e. JA is also involved in plant defense against pathogens and insects\u003csup\u003e\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e\u003c/sup\u003e. SA promotes photosynthesis, growth, biochemical reactions, and the synthesis of antioxidant compounds during periods of stress\u003csup\u003e\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e, \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThe present study highlights a positive correlation between seedling emergence and the accumulation of MeJA in endosperm in \u003cem\u003eL. pisonis\u003c/em\u003e, as well as a direct (\u003cem\u003eL. pisonis\u003c/em\u003e) and indirect (\u003cem\u003eL. lanceolata\u003c/em\u003e) positive effect of MeJA in tegument on seedling emergence. Still, the concentration of MeJA in endosperm in \u003cem\u003eL. lanceolata\u003c/em\u003e seeds was detrimental to seedling growth and correlated negatively with the number of leaves, number of shoots, shoot dry mass, and total dry mass. Moreover, MeJA in tegument exerted a direct negative effect on several shoots in \u003cem\u003eL. pisonis\u003c/em\u003e and \u003cem\u003eL. lanceolata\u003c/em\u003e seedlings. MeJA has been documented to block the development of shoots and the selective permeability of membranes in cortical root cells of Arabidopsis, which is associated with the dephosphorylation of aquaporins and consequent impairment of water flow\u003csup\u003e\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eISSR analysis allowed the clustering of the studied trees into distinct groups. \u003cem\u003eL. lanceolata\u003c/em\u003e trees showed less variability than \u003cem\u003eL. pisonis\u003c/em\u003e trees, and such low polymorphism is probably related to the geographic proximity between individuals. This may not be surprising, as one of the factors favoring low genetic variability is pollination among individuals with high kinship, which may cause future problems of inbreeding. In studies with \u003cem\u003eB. excelsa\u003c/em\u003e, genetic diversity was greater between populations (95.56%) than among individuals of the same population (2.68%). This finding suggests that it might be worthwhile to harvest seeds from geographically distant trees, to ensure the propagation of highly diverse genetic material\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. In \u003cem\u003eL. pisonis\u003c/em\u003e trees located in different regions of northern Esp\u0026iacute;rito Santo state, the elevated rate of polymorphism (96.7%) based on 13 ISSR primers was likely the result of sampling from geographically distant specimens\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eOverall, this study brings several contributions related to genetic diversity and phenotypic diversity of the species \u003cem\u003eL. pisonis\u003c/em\u003e and \u003cem\u003eL. lanceolata\u003c/em\u003e. It also addresses physiological issues of seedling germination and growth, which are fundamental for the propagation and maintenance of these genetic materials. It is an initial study based on a group of trees and can be used as a basis for generating new research for the species \u003cem\u003eL. pisonis\u003c/em\u003e and \u003cem\u003eL. lanceolata\u003c/em\u003e.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe greater genetic diversity observed among \u003cem\u003eL. pisonis\u003c/em\u003e trees, when compared to \u003cem\u003eL. lanceolata\u003c/em\u003e trees, may be related to the greater territorial distance between them. \u003cem\u003eL. pisonis\u003c/em\u003e trees showed seedling emergence varying abruptly, between low (3%) and high (93%) values, indicating possible physiological dormancy. Seeds from \u003cem\u003eL. lanceolata\u003c/em\u003e trees showed less variation in seedling emergence. Both species showed non-uniform seedling emergence over a long period, a factor that corroborates an increase in the production costs of seedlings in the nursery, indicating that new studies related to the breaking of physical and physiological dormancy should be carried out in order to reduce the seedling time. seedling emergence. In \u003cem\u003eL. lanceolata\u003c/em\u003e, the mean emergence time was indirectly positively controlled by abscisic acid in the seed coat, indicating a possible dormancy controlled by ABA accumulation. The hormonal content of the seeds of both species influenced the emergence of seedlings and the growth of seedlings, indicating that new studies related to the exogenous application of growth regulators in seeds can be developed. This is an initial characterization study, which comprises important information about the species \u003cem\u003eL. pisonis\u003c/em\u003e and \u003cem\u003eL. lanceolata\u003c/em\u003e, mainly related to seed physiology and seedling growth, and can contribute to research related to the production of seedlings for commercial plantings and forest restoration. Future commercial nut plantations, in the long term, could lead to the construction of industries and consequently the creation of jobs.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u0026nbsp;\u003c/strong\u003eRSA, CPA designed the study; CPA, TLMR, TM, IMS and TCCN performed most of the experiments; AF and APS analyzed the data; CPA, SO and MFSF molecular analysis;\u0026nbsp;CPA and CEV; analysis of plant hormones and precursor; CPA, TLMR, TM, IMS, TCCN, SO, AF, JPBO, ERS, JCL, MFSF, ARS, APS, CEV, WCO and RSA scientific article writing. All authors read and approved the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u0026nbsp;\u003c/strong\u003eThe authors would like to thank Conselho Nacional de Desenvolvimento Cient\u0026iacute;fico e Tecnol\u0026oacute;gico (CNPq), Coordena\u0026ccedil;\u0026atilde;o de Aperfei\u0026ccedil;oamento de Pessoal de N\u0026iacute;vel Superior (CAPES) and Funda\u0026ccedil;\u0026atilde;o de Amparo \u0026agrave; Pesquisa e Inova\u0026ccedil;\u0026atilde;o do Esp\u0026iacute;rito Santo (FAPES) for research funding. To the Biomolecule Analysis Nucleus (NuBioMol), belonging to the Federal University of Vi\u0026ccedil;osa (UFV) and the Financiadora de Estudos e Projetos (FINEP), CNPq and the Funda\u0026ccedil;\u0026atilde;o de Amparo \u0026agrave; Pesquisa do Estado de Minas Gerais (FAPEMIG) for equipment used to perform hormonal analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e On behalf of all authors, the corresponding author states that there is no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003eThis study was funded by the Coordena\u0026ccedil;\u0026atilde;o de Aperfei\u0026ccedil;oamento de Pessoal de N\u0026iacute;vel Superior (CAPES) (Finance code 001), the Funda\u0026ccedil;\u0026atilde;o de Amparo \u0026agrave; Pesquisa e Inova\u0026ccedil;\u0026atilde;o do Esp\u0026iacute;rito Santo (FAPES) [EDITAL FAPES/CNPq N\u0026deg; 05/2017 - PRONEM (Programa de Apoio a N\u0026uacute;cleos Emergentes), agreement registered in SICONV under N\u0026deg; 794009/2013, Process FAPES N\u0026deg; 72660945; EDITAL FAPES N\u0026ordm; 04/2021 - TAXA DE PESQUISA,\u0026nbsp;Protocol\u0026nbsp;N\u0026deg; 45837.716.19068.15062021], and the Conselho Nacional de Desenvolvimento Cient\u0026iacute;fico e Tecnol\u0026oacute;gico (CNPq) [Call\u0026nbsp;CNPq 06/2019 -\u0026nbsp;Research Productivity Grants\u003cem\u003e,\u003c/em\u003e Process\u0026nbsp;N\u0026ordm; 308365/2019-4,\u0026nbsp;Protocol\u0026nbsp;N\u0026ordm; 3787528332113241].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u0026nbsp;\u003c/strong\u003eThe data that support the findings of this study are available upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSfb \u0026ndash; Servi\u0026ccedil;o Florestal Brasileiro. Florestas do Brasil em resumo: 2019. MAPA/SFB, Bras\u0026iacute;lia. (2019). Available at: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.florestal.gov.br/documentos/publicacoes/4261-florestas-do-brasil-em-resumo-digital/file\u003c/span\u003e\u003cspan address=\"http://www.florestal.gov.br/documentos/publicacoes/4261-florestas-do-brasil-em-resumo-digital/file\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (Accessed 10 May 2020).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePolmann, G., Badia, V., Danielski, R., Ferreira, S. R. S. \u0026amp; Block, J. M. Nonconventional nuts: an overview of reported composition and bioactivity and new approaches for its consumption and valorization of coproducts. \u003cem\u003eFuture Foods\u003c/em\u003e. \u003cb\u003e4\u003c/b\u003e, 100099. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.fufo.2021.100099\u003c/span\u003e\u003cspan address=\"10.1016/j.fufo.2021.100099\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2021).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRosa, T. L. M. et al. Sapucaia nut: Morphophysiology, minerals content, methodological validation in image analysis, phenotypic and molecular diversity in \u003cem\u003eLecythis pisonis\u003c/em\u003e Cambess. \u003cem\u003eFood Res. 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Biochem.\u003c/em\u003e \u003cb\u003e139\u003c/b\u003e, 540\u0026ndash;547. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.plaphy.2019.04.023\u003c/span\u003e\u003cspan address=\"10.1016/j.plaphy.2019.04.023\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2019).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Genetic divergence, Seedling emergence, Seedling phenotyping, Seed vigor","lastPublishedDoi":"10.21203/rs.3.rs-6866798/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6866798/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe Brazilian rainforests host the species \u003cem\u003eLecythis pisonis\u003c/em\u003e and \u003cem\u003eLecythis lanceolata\u003c/em\u003e, potential producers of functional nuts. This study aimed to: (1) demarcate and characterize phenotypically and genotypically both species; (2) analyze seed biometric and physiological traits; (3) investigate seed hormonal composition and its influence on germination; and (4) assess early seedling phenotypes. \u003cem\u003eL. pisonis\u003c/em\u003e showed higher genetic diversity than \u003cem\u003eL. lanceolata\u003c/em\u003e. Seedling emergence was highest in seeds from specific trees: 1 and 2 (\u003cem\u003eL. pisonis\u003c/em\u003e) and 1, 2, 4, 5, and 6 (\u003cem\u003eL. lanceolata\u003c/em\u003e). Abscisic acid (ABA) and 1-aminocyclopropane-1-carboxylic acid (ACC) were negatively correlated with seed growth in both species. In \u003cem\u003eL. pisonis\u003c/em\u003e, methyl jasmonate (MeJA) in the endosperm correlated positively with seedling emergence, while MeJA in the tegument negatively affected shoot formation in both species. In \u003cem\u003eL. lanceolata\u003c/em\u003e, ABA in the seed coat positively influenced mean emergence time, suggesting a dormancy mechanism. These findings enhance the understanding of seed physiology and early development in \u003cem\u003eL. pisonis\u003c/em\u003e and \u003cem\u003eL. lanceolata\u003c/em\u003e, offering key insights for future propagation and commercial cultivation efforts.\u003c/p\u003e","manuscriptTitle":"Prospecting elite donor plants and characterization of endogenous hormonal status in seeds of Brazilian chestnuts (Lecythidaceae)","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-25 13:42:24","doi":"10.21203/rs.3.rs-6866798/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2025-08-28T16:37:43+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"60653650486626540424012178481396431311","date":"2025-08-19T14:18:46+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-14T21:03:06+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"28210639080949914234896063510042480407","date":"2025-08-07T05:17:29+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-03T20:55:46+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"210324158709073214945114486239358345707","date":"2025-07-25T16:44:54+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-07-23T11:00:22+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-07-23T10:58:41+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-06-24T10:53:12+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-06-23T17:36:44+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-06-23T17:30:50+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"7b5a4a25-5984-4f19-bf2c-8a809a6b5991","owner":[],"postedDate":"July 25th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":51991412,"name":"Biological sciences/Developmental biology"},{"id":51991413,"name":"Biological sciences/Ecology"},{"id":51991414,"name":"Biological sciences/Physiology"},{"id":51991415,"name":"Biological sciences/Plant sciences"},{"id":51991416,"name":"Earth and environmental sciences/Ecology"}],"tags":[],"updatedAt":"2025-07-25T13:42:24+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-25 13:42:24","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6866798","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6866798","identity":"rs-6866798","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}