Application of Xanthoceras sorbifolia leaf traits in predicting its oil quality

Abstract

The application discloses application of Xanthoceras sorbifolia leaf traits in predicting oil quality, and belongs to the technical field of oil quality. 206 Xanthoceras sorbifolia germplasms are counted, and mature leaves and mature seeds in east, south, west and north directions are collected. Leaf trait data of the samples are measured and counted by using professional instruments and methods, and the fatty acid content of the mature seeds of Xanthoceras sorbifolia is accurately detected by using gas chromatography-mass spectrometry (GC-MS) technology. Coordination of plant traits shows physiological response of the plant to environmental conditions. Leaf characteristics of the plant are usually relatively easy to measure. By establishing correlation between the leaf traits and the proportion of fatty acid components and the oil content of Xanthoceras sorbifolia, the proportion of fatty acid components and the oil content of the mature seeds of Xanthoceras sorbifolia are predicted, so that breeding work is promoted. The purpose of predicting complex indexes by using simple phenotype data is achieved.

Description

Technical Field

[0001] This invention relates to the field of oil quality technology, and more specifically to the application of leaf traits of *Sapindus mukorossi* in predicting its oil quality. Background Technology

[0002] *Xanthoceras sorbifolia* Bunge is a multi-functional tree species unique to my country, integrating woody oil production, ecological afforestation, ornamental landscaping, and medicinal uses. The mature seeds of *Xanthoceras sorbifolia* contain 17.72%–37.18% oil, while the kernels contain 45.05%–65.78% oil. Unsaturated fatty acids account for up to 92% of the total fatty acids, with oleic acid (C18:1) (26.44%–34.18%) and linoleic acid (C18:2) (36.95%–44.18%) being the main components. Notably, the oil from *Xanthoceras sorbifolia* contains nervonic acid (C24:1) (3%–7%), which is rare in plants and plays a crucial role in maintaining brain nerve fibers and improving the nerve cell environment, making it a high-quality material for producing premium woody edible oils.

[0003] Currently, *Xanthoceras sorbifolium* oil is typically extracted from mature seeds (or kernels) using methods such as pressing (cold pressing and hot pressing), solvent extraction, aqueous enzymatic extraction, and supercritical carbon dioxide extraction. Before actually testing the oil content of *Xanthoceras sorbifolium* seeds, we cannot know in advance whether a particular *Xanthoceras sorbifolium* germplasm has a higher oil content or a higher content of a specific fatty acid component.

[0004] Plant leaf functional traits are characterized by rapid quantification and ease of measurement, reflecting a plant's ecological adaptability to various environmental factors. The frequency of trait variation is a quantitative measure of genetic diversity, while the degree of variation represents the inherent characteristics of germplasm resources and the range of individual differences. Research on leaf functional trait variation can provide valuable insights for assessing intraspecific genetic diversity and understanding the relationship between leaf traits and oil quality. Strengthening research on the correlation between leaf phenotypic traits and breeding objectives can effectively accelerate the breeding process and the protection of genetic resources. Currently, there are no methods to predict the oil quality of *Xanthoceras sorbifolium* using leaf phenotypic indicators.

[0005] In summary, how to provide a method for predicting the oil quality of *Sapindus mukorossi* through leaf traits is a problem that urgently needs to be solved by those skilled in the art. Summary of the Invention

[0006] In view of this, the present invention provides the application of leaf traits of *Sapindus mukorossi* in predicting its oil quality.

[0007] This invention requires detailed and accurate leaf trait data and fatty acid composition data for *Xanthoceras sorbifolium* seeds. Randomness, uniformity, and representativeness must be ensured during sample collection. This invention provides valuable information for predicting complex oil quality traits using simple leaf characteristics.

[0008] To achieve the above objectives, the present invention adopts the following technical solution:

[0009] Application of leaf traits of *Sapindus mukorossi* in predicting its oil quality, said leaf traits include: δ 15 N, δ 13 C. Relative moisture content, chlorophyll content, and number of compound leaves;

[0010] The quality of the oil includes: the proportion of oleic acid, the proportion of linoleic acid, the proportion of nervonic acid, and the oil content.

[0011] Furthermore, when δ 15 N ranges from -1.13 to 1.71‰;

[0012] δ 13 C ranges from -29.96 to -27.19‰;

[0013] The relative moisture content is 0.38–0.51.

[0014] The chlorophyll content ranges from 36.01% to 50.04%.

[0015] When the number of compound leaves is 13.17–17.83,

[0016] The oleic acid component accounts for more than 29.4%.

[0017] Furthermore, when δ 15 N ranges from -1.19 to 2.69‰;

[0018] δ 13 C ranges from -29.53 to -27.36‰;

[0019] The relative moisture content is 0.36–0.49.

[0020] The chlorophyll content ranges from 37.82% to 51.26%.

[0021] When the number of compound leaves is 13.17–18.33,

[0022] The proportion of linoleic acid is greater than 40.2%.

[0023] Furthermore, when δ 15 N ranges from -1.02 to 2.78‰;

[0024] δ 13 C ranges from -29.96 to -27.41‰;

[0025] The relative moisture content is 0.35–0.49.

[0026] The chlorophyll content ranges from 36.93% to 48.66%.

[0027] When the number of compound leaves is 12.67–17.83,

[0028] The proportion of nervonic acid component is greater than 3.39%.

[0029] Furthermore, when δ 15 N is -1.50 to 1.71‰;

[0030] δ 13 C ranges from -30.08 to -27.63‰;

[0031] The relative moisture content is 0.37–0.49.

[0032] The chlorophyll content ranges from 33.85% to 49.92%.

[0033] When the number of compound leaves is 13.25–17.83,

[0034] The oil content is greater than 36.27%.

[0035] Furthermore, when δ 15 N ranges from -1.02 to 1.71‰;

[0036] δ 13 C ranges from -29.53 to -27.63‰;

[0037] The relative moisture content is 0.38–0.49.

[0038] The chlorophyll content ranges from 37.82% to 48.66%.

[0039] When the number of compound leaves is 13.25–17.83,

[0040] The proportion of oleic acid is greater than 29.4%, the proportion of linoleic acid is greater than 40.2%, the proportion of nervonic acid is greater than 3.39%, and the oil content is greater than 36.27%.

[0041] As can be seen from the above technical solution, compared with the prior art, the beneficial effects achieved by the present invention are as follows:

[0042] The coordination of plant traits reflects the physiological response of plants to environmental conditions. Leaf characteristics are relatively easy to measure. By establishing the correlation between leaf traits and the fatty acid composition ratio and oil content of *Xanthoceras sorbifolium*, the fatty acid composition ratio and oil content of *Xanthoceras sorbifolium* can be predicted, thereby promoting breeding work. This achieves the goal of predicting complex indicators using simple phenotypic data.

[0043] Plant leaf functional traits are relatively stable, rapidly quantifiable, and easily measured, reflecting a plant's ecological adaptability to various environmental factors. Strengthening research on the correlation between phenotypic traits, especially leaf traits, and breeding objectives can effectively accelerate the breeding process. Understanding the relationship between leaf traits and oil quality enables producers to use these simple leaf traits to select *Xanthoceras sorbifolium* germplasm with good oil quality, contributing to the development of breeding and improvement programs, as well as the protection of genetic resources. Attached Figure Description

[0044] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0045] Figure 1 The attached figure is a prediction diagram of the C18:1 component ratio in Example 1 of the present invention;

[0046] Figure 2 The attached figure is a predicted ratio diagram of C18:2 components in Embodiment 1 of the present invention;

[0047] Figure 3 The attached figure is a prediction diagram of the C24:1 component ratio in Example 1 of the present invention;

[0048] Figure 4 The attached figure is a prediction chart of oil content in Example 1 of the present invention. Detailed Implementation

[0049] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0050] The reagents required for this invention are conventional experimental reagents, purchased from commercially available channels; the experimental methods not mentioned are conventional experimental methods, and will not be described in detail here.

[0051] Example 1

[0052] Samples were collected from Tongliao City, Inner Mongolia Autonomous Region (121.34°~121.37°E, 43.40°~43.42°N). Three months after the leaves of *Xanthoceras sorbifolium* unfolded (late July), 10 mature leaves were collected from each of the four cardinal directions (east, south, west, and north) of 206 perennial *Xanthoceras sorbifolium* trees (the average value was used). Five leaf traits were statistically analyzed, including δ... 15 N, δ 13 C. Relative moisture content (LRWC), chlorophyll content (SPAD), and number of compound leaves (FN).

[0053] Seeds were collected at the fruit ripening stage. Using heptadecanoic acid (C17:0) as an internal standard, 13 fatty acid components were identified by gas chromatography-mass spectrometry (GC-MS), including palmitic acid (C16:0), palmitoleic acid (C16:1), stearic acid (C18:0), oleic acid (C18:1), linoleic acid (C18:2), linolenic acid (C18:3), arachidic acid (C20:0), cis-11-eicosenoic acid (C20:1), cis-11,14-eicosadienoic acid (C20:2), benzolic acid (C22:0), erucic acid (C22:1), teicosicoic acid (C24:0), and nervonic acid (C24:1). The oil content was then calculated.

[0054] Formulas for calculating the content (mg / g) of each fatty acid component:

[0055] m C16:0 =((300*S) C16:0 ) / S C17:0 ) / m 样品 ;

[0056] Where 300 (μg) is the mass of the internal standard (C17:0). S represents the peak area of ​​GC-MS. C16:0 This represents the peak area of ​​C16:0 as determined by GC-MS. 样品 (mg) represents the amount of sample used in the determination. The same principle applies to the following.

[0057] m C16:1 =((300×S) C16:1 ) / S C17:0 ) / m 样品 ;

[0058] m C18:0 =((300×S) C18:0 ) / S C17:0 ) / m 样品 ;

[0059] m C18:1 =((300×S) C18:1 ) / S C17:0 ) / m 样品 ;

[0060] m C18:2 =((300×S) C18:2 ) / S C17:0 ) / m 样品 ;

[0061] m C18:3 =((300×S) C18:3 ) / S C17:0 ) / m 样品 ;

[0062] m C20:0 =((300×S) C20:0 ) / S C17:0 ) / m 样品 ;

[0063] m C20:1 =((300×S) C20:1 ) / S C17:0 ) / m 样品 ;

[0064] m C20:2 =((300×S) C20:2 ) / S C17:0 ) / m 样品 ;

[0065] m C22:0 =((300×S) C22:0 ) / S C17:0 ) / m 样品 ;

[0066] m C22:1 =((300×S) C22:1 ) / S C17:0 ) / m 样品 ;

[0067] m C24:0 =((300×S) C24:0 ) / S C17:0 ) / m 样品 ;

[0068] m C24:1 =((300×S) C24:1 ) / S C17:0 ) / m 样品 .

[0069] Formula for calculating the percentage (%) of each fatty acid component:

[0070] C16:0=m C16:0 / (m C16:0+ ···m C24:1 )×100%;

[0071] C16:1=m C16:1 / (m C16:0 +···m C24:1 )×100%;

[0072] C18:0=m C18:0 / (m C16:0 +···m C24:1 )×100%;

[0073] C18:1=m C18:1 / (m C16:0 +···m C24:1 )×100%;

[0074] C18:2=m C18:2 / (m C16:0 +···m C24:1 )×100%;

[0075] C18:3=m C18:3 / (m C16:0 +···m C24:1 )×100%;

[0076] C20:0=m C20:0 / (m C16:0 +···m C24:1 )×100%;

[0077] C20:1=m C20:1 / (m C16:0 +···m C24:1 )×100%;

[0078] C20:2=m C20:2 / (m C16:0 +···m C24:1 )×100%;

[0079] C22:0=m C22:0 / (m C16:0 +···m C24:1 )×100%;

[0080] C22:1=m C22:1 / (m C16:0 +···m C24:1 )×100%;

[0081] C24:0=m C24:0 / (m C16:0 +···m C24:1 )×100%;

[0082] C24:1=m C24:1 / (m C16:0 +···mC24:1 )×100%;

[0083] Oil content (%) = (m C16:0 +···m C24:1 ) / 10.

[0084] Oleic acid and linoleic acid are the main components of *Xanthoceras sorbifolium* oil, while nervonic acid is a unique substance in *Xanthoceras sorbifolium* oil. Using Origin software, SPAD, FN, LRWC, and δ... 15 N and δ 13 Using five leaf indicators as vertices, a prediction map for the quality of *Xanthoceras sorbifolium* oil was constructed based on key indicators of *Xanthoceras sorbifolium* oil quality (the main components of *Xanthoceras sorbifolium* oil, the proportion of components of unique substances, and oil content).

[0085] in:

[0086] δ 13 C、δ 15 N was determined by a stable isotope mass spectrometer (Pee-Dee-Belemnite standard).

[0087] Relative moisture content (LRWC): The fresh leaf weight (FLW) and dry leaf weight (LDW) of the sample leaves were collected using an electronic balance (0.01g) and calculated according to formula (1):

[0088] Formula (1): Leaf water content (LRWC) = (FLW-LDW) / LDW.

[0089] Chlorophyll content (SPAD) was measured using a SPAD-520 chlorophyll meter (Konica Minolta, Japan).

[0090] The number of compound leaves (FN) was determined by scanning the collected sample leaves with an EPSONperfection V30 portable scanner and counting the results using Digimizer software (V5.4.4).

[0091] Thirteen fatty acid components were determined using gas chromatography-mass spectrometry (GC-MS).

[0092] Based on fatty acid composition data from 206 mature seeds of *Xanthoceras sorbifolium*, principal component analysis was used to screen germplasms with high proportions of target fatty acid components and high oil content (oleic acid ≥ 29.4%, linoleic acid ≥ 40.2%, nervonic acid ≥ 3.39%, oil content ≥ 36.27%). Germplasm was then selected based on the corresponding SPAD, FN, LRWC, and δ-carboxylic acid components. 15 N and δ 13 C. Prediction charts were drawn based on the data of five leaf indicators (Table 2). Figures 1-4 The gray area is defined to predict the oil quality of *Sapindus mukorossi*. When SPAD, FN, LRWC, and δ...15 N and δ 13 When all five leaf index data meet the following data range (Table 1 data), the proportions of oleic acid (C18:1), linoleic acid (C18:2), and nervonic acid (C24:1) components and the oil content of this *Sapindus mukorossi* cultivar are higher than those of the samples in this batch.

[0093] Table 1 Forecasting Standards

[0094] C18:1 component ratio -1.13～1.71 -29.96～-27.19 0.38～0.51 36.01～50.04 13.17～17.83 C18:2 component ratio -1.19～2.69 -29.53～-27.36 0.36～0.49 37.82～51.26 13.17～18.33 C24:1 component ratio -1.02～2.78 -29.96～-27.41 0.35～0.49 36.93～48.66 12.67～17.83 Fat content -1.50～1.71 -30.08～-27.63 0.37～0.49 33.85～49.92 13.25～17.83

[0095] Table 2. Standardized prediction results

[0096] C18:1 component ratio 0.12～0.54 0.23～0.81 0.07～0.42 0.23～0.80 0.24～0.82 C18:2 component ratio 0.11～0.68 0.32～0.77 0.02～0.39 0.30～0.85 0.24～0.88 C24:1 component ratio 0.14～0.69 0.23～0.71 0.00～0.39 0.27～0.74 0.18～0.82 Fat content 0.07～0.54 0.21～0.72 0.05～0.36 0.14～0.80 0.26～0.82

[0097] Example 2

[0098] We conducted δ-ray analysis on the leaves of 42 *Xanthoceras sorbifolium* seedlings from this region (Tongliao City, Inner Mongolia Autonomous Region, a different location from Example 1). 15 N, δ 13 C. Statistical analysis of relative moisture content (LRWC), chlorophyll content (SPAD), and compound leaf number (FN), as well as determination of fatty acid composition in mature seeds. Sampling and measurement methods were the same as in Example 1. Results are as follows:

[0099] Table 3 Detection Data

[0100]

[0101]

[0102] According to the prediction criteria in Table 1,

[0103] High-quality oleic acid includes: 1, 2, 3, 4, 5, 10, 11, 14, 15, 16, 17, 18, 19, 20, 21, 23, 24, 27, 29, 30, 36, 37, 38, 39, and 42.

[0104] The following are high-quality linoleic acid grades: 1, 2, 3, 5, 6, 7, 8, 10, 11, 14, 16, 18, 21, 22, 23, 24, 27, 29, 36, 37, 39, 40, 41, and 42.

[0105] The following are high-quality nervonic acid: 1, 2, 6, 10, 11, 12, 14, 16, 17, 18, 19, 20, 21, 22, 23, 24, 29, 30, 36, and 39.

[0106] The following have high-quality fat content: 1, 2, 10, 11, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 27, 29, 30, 32, 34, 35, 36, 37, 38, 39, and 42.

[0107] Based on the actual test results of the oils in Table 2, and according to the screening criteria (oleic acid ≥ 29.4%, linoleic acid ≥ 40.2%, nervonic acid ≥ 3.39%, oil content ≥ 36.27%),

[0108] The following are high-quality oleic acid grades: 1, 2, 3, 4, 5, 7, 8, 10, 11, 14, 15, 16, 17, 18, 20, 21, 22, 23, 24, 26, 27, 29, 30, 32, 34, 35, 37, 38, 39, 41, and 42.

[0109] The following are high-quality linoleic acid grades: 1, 2, 3, 4, 5, 6, 7, 8, 10, 11, 14, 16, 18, 22, 23, 25, 27, 29, 31, 33, 36, 37, 40, 41, and 42.

[0110] The following are high-quality nervonic acid products: 1, 2, 5, 6, 10, 11, 12, 14, 15, 16, 18, 19, 20, 22, 23, 24, 29, 30, 36, 39, and 40.

[0111] The following have high-quality fat content: 1, 8, 9, 10, 11, 14, 15, 16, 17, 19, 20, 21, 22, 24, 27, 29, 30, 32, 34, 35, 36, 37, 38, 39, and 42.

[0112] In summary, according to the prediction diagram of the present invention, the coverage rate of high-quality C18:1 mature seeds with high quality is 23 / 31, and the accuracy is 23 / 25.

[0113] C18:2 has a high-quality coverage of 21 / 25 and an accuracy of 22 / 24.

[0114] C24:1 has a high-quality coverage of 18 / 21 and an accuracy of 18 / 20.

[0115] The coverage rate for high-quality oil content is 23 / 25, and the accuracy rate is 23 / 26.

[0116] (Coverage is calculated as the number of germplasm selected by both screening methods / the number of germplasm selected based on measured oil content; accuracy is calculated as the number of germplasm selected by both screening methods / the number of germplasm selected based on leaf traits.)

[0117] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The same or similar parts between the various embodiments can be referred to each other.

[0118] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. The application of leaf traits of *Sapindus mukorossi* in predicting its oil quality, characterized in that... The leaf characteristics include: δ 15 N, δ 13 C. Relative moisture content, chlorophyll content, and number of compound leaves; The quality of the oil includes: the proportion of oleic acid, the proportion of linoleic acid, the proportion of nervonic acid, and the oil content. When δ 15 N is -1.13 to 1.71‰; δ 13 C ranges from -29.96 to -27.19‰; The relative moisture content is 0.38~0.51; The chlorophyll content is 36.01~50.04; When the number of compound leaves is 13.17~17.83, The oleic acid component accounts for more than 29.4%; When δ 15 N is -1.19 to 2.69‰; δ 13 C ranges from -29.53 to -27.36‰; The relative moisture content is 0.36~0.49; The chlorophyll content is 37.82~51.26; When the number of compound leaves is 13.17~18.33, The proportion of linoleic acid is greater than 40.2%; When δ 15 N ranges from -1.02 to 2.78‰; δ 13 C ranges from -29.96 to -27.41‰; The relative moisture content is 0.35~0.49; The chlorophyll content is 36.93~48.66; When the number of compound leaves is 12.67~17.83, The proportion of nervonic acid component is greater than 3.39%; When δ 15 N is -1.50 to 1.71‰; δ 13 C ranges from -30.08 to -27.63‰; The relative moisture content is 0.37~0.49; The chlorophyll content is 33.85~49.92; When the number of compound leaves is 13.25~17.83, The oil content is greater than 36.27%.

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