[
Barker M, Rayens W (2003) Partial least squares for discrimination. Journal of Chemometrics 17(3): 166-173. https://dx.doi.org/10.1002/cem.785
]Search in Google Scholar
[
Bonner FT (1987) Seed biology and technology of Quercus. Louisiana, U.S.: US Department of Agriculture, Forest Service, Southern Forest Experiment Station, 5-6, 11-12 p
]Search in Google Scholar
[
Cen H, He Y(2007) Theory and application of near infrared reflectance spectroscopy in determination of food quality. Trends in Food Science and Technology 18(2): 72-83. https://dx.doi.org/10.1016/j.tifs.2006.09.003
]Search in Google Scholar
[
Chung DH, Yu TJ, Choi BK (1975) Studies on the utilization of acorn starch -part I. properties of acorn starch-. Applied Biological Chemistry 18(2): 102-108
]Search in Google Scholar
[
Chung HI, Kim HJ (2000) Near-infrared spectroscopy: principles. Analytical science & technology 13(1): 138-151
]Search in Google Scholar
[
Connor K (2004) Storing acorns. Native Plants Journal 5(2): 160-166
]Search in Google Scholar
[
Csóka G, Hirka AC (2006) Direct effects of carpophagous insects on the germination ability and early abscission of oak acorns. Acta Silvatica et Lignaria Hungarica 2: 57-67
]Search in Google Scholar
[
Daneshvar A, Tigabu M, Karimidoost A, Oden PC (2015) Single seed near infrared spectroscopy discriminates viable and non-viable seeds of Juniperus polycarpos. Silva Fennica 49(5). https://dx.doi.org/10.14214/sf.1334
]Search in Google Scholar
[
Dorsey CK, Tryon EH, Carvell KL (1962) Insect damage to acorns in West Virginia and control studies using granular systemic insecticides. Journal of Economic Entomology 55(6): 885-888. https://dx.doi.org/10.1093/jee/55.6.885
]Search in Google Scholar
[
FAO (2010) Seeds in emergencies : a technical handbook. Rome: FAO, ISBN 9789251066768
]Search in Google Scholar
[
Farhadi M, Tigabu M, Stener L-G, Odén PC (2016) Feasibility of visible+ near infrared spectroscopy for non-destructive verification of European× Japanese larch hybrid seeds. New Forests 47(2): 271-285
]Search in Google Scholar
[
Feng L, Zhu S, Liu F, He Y, Bao Y, Zhang C (2019) Hyperspectral imaging for seed quality and safety inspection: a review. Plant Methods 15(1): 91-91. https://dx.doi.org/10.1186/s13007-019-0476-y
]Search in Google Scholar
[
Government of Korea (2021) 2050 Carbon neutrality scenarios. Available from https://www.2050cnc.go.kr/eng/board/read?boardManagement-No=28&boardNo=608&searchCategory=&page=1&searchType=&-searchWord=&menuLevel=2&menuNo=65
]Search in Google Scholar
[
Gribko LS (1995) The effect of acorn insects on the establishment and vigor of northern red oak seedlings in north-central West Virginia. Proceedings of the 10th Central Hardwood Forest Conference, West Virginia, U. S.: 430-441
]Search in Google Scholar
[
Gribko LS, Jones WE (1995) Test of the float method of assessing northern red oak acorn condition. Tree Planters’ Notes 46(4): 143-147
]Search in Google Scholar
[
Guo W, Zhao F, Dong J (2016) Nondestructive measurement of soluble solids content of kiwifruits using near-infrared hyperspectral imaging. Food Analytical Methods 9(1): 38-47
]Search in Google Scholar
[
He X, Yan C, Jiang X, Shen F, You J, Fang Y (2021) Classification of aflatoxin B1 naturally contaminated peanut using visible and near-infrared hyperspectral imaging by integrating spectral and texture features. Infrared physics & technology 114: 103652. https://dx.doi.org/10.1016/j.infrared.2021.103652
]Search in Google Scholar
[
Hirayama D, Fujii T, Nanami S, Itoh A, Yamakura T (2012) Two-year cycles of synchronous acorn and leaf production in biennial-fruiting evergreen oaks of subgenus Cyclobalanopsis (Quercus, Fagaceae). Ecological Research 27(6): 1059-1068. https://dx.doi.org/10.1007/s11284-012-0986-9
]Search in Google Scholar
[
Hwang JS, Kang JT, Son YM, Jeon HS (2015) Prediction of the optimal growth site and estimation of carbon stocks for Quercus acuta in Wando Area. Journal of Climate Change Research 6(4): 319. https://dx.doi.org/10.15531/ksccr.2015.6.4.319
]Search in Google Scholar
[
Jamshidi B (2020) Ability of near-infrared spectroscopy for non-destructive detection of internal insect infestation in fruits: Meta-analysis of spectral ranges and optical measurement modes. Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy 225: 117479. https://dx.doi.org/10.1016/j.saa.2019.117479
]Search in Google Scholar
[
Jamshidi B, Mohajerani E, Farazmand H, Mahmoudi A, Hemmati A (2019) Pattern recognition-based optical technique for non-destructive detection of Ectomyelois ceratoniae infestation in pomegranates during hidden activity of the larvae. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy 206: 552-557
]Search in Google Scholar
[
Khan S, Habib A (2015) Effect of pre-sowing treatments on seed germination in Quercus glauca Thunb., collected from different sampling sites of the Himalayan region of Pakistan. International Journal of Biosciences 6(11): 42-48
]Search in Google Scholar
[
Kim C, Kim W, Song W, Cho J, Choi J (2023) Prediction of native seed habitat distribution according to ssp scenario and seed transfer zones: a focus on Acer pictum subsp. mono and Quercus acuta. Forests 14(1): 87
]Search in Google Scholar
[
Kim HJ, Lee SH (2017) Estimating carbon storage and CO2 absorption by developing allometric equations for Quercus acuta in South Korea. Forest science and technology 13(2): 55-60
]Search in Google Scholar
[
Kim S, Park I-H (2021) Acorn production and characteristics of Quercus acuta thunb-Focused on Wando, Jindo and Haenam in Jeollanam-do, Korea. Korean Journal of Environment and Ecology 35(6): 621-631
]Search in Google Scholar
[
Lee JH, Choi BH (2010) Distribution and northernmost limit on the Korean Peninsula of three evergreen trees. Korean Journal of Plant Taxonomy 40(4): 267
]Search in Google Scholar
[
Lowe A, Harrison N, French AP (2017) Hyperspectral image analysis techniques for the detection and classification of the early onset of plant disease and stress. Plant Methods 13(1): 80-80. https://dx.doi.org/10.1186/s13007-017-0233-z
]Search in Google Scholar
[
Moscetti R, Haff RP, Saranwong S, Monarca D, Cecchini M, Massantini R (2014) Nondestructive detection of insect infested chestnuts based on NIR spectroscopy. Postharvest biology and technology 87: 88-94. https://dx.doi.org/10.1016/j.postharvbio.2013.08.010
]Search in Google Scholar
[
Munera S, Rodríguez-Ortega A, Aleixos N, Cubero S, Gómez-Sanchis J, Blasco J (2021) Detection of invisible damages in ‘rojo brillante’ persimmon fruit at different stages using hyperspectral imaging and chemometrics. Foods 10(9): 2170. https://dx.doi.org/10.3390/foods10092170
]Search in Google Scholar
[
Næs T, Isaksson T, Fearn T, Davies T (2002) A user-friendly guide to multivariate calibration and classification. Chichester, UK: NIR Publications, ISBN 978-1-906715-25-0
]Search in Google Scholar
[
NFSV (The National Forest Seed and Variety Center) (2021) The 2nd plan for the management and establishment of the seed orchard (2022~2026).
]Search in Google Scholar
[
Novikov AI (2019) Visible wave spectrometric features of scots pine seeds: the basis for designing a rapid analyzer. In: 2020 IOP Conference Series: Earth and Environmental Science.: Earth Environmental Science. Bristol, UK: IOP Publishing, p 12064
]Search in Google Scholar
[
Novikov AI, Ersson BT, Malyshev VV, Petrishchev EP, Ilunina AA (2020) Mechanization of coniferous seeds grading in Russia: a selected literature analysis. In: 2020 IOP Conference Series: Earth and Environmental Science.: Earth Environmental Science. Bristol: IOP Publishing, p 12060
]Search in Google Scholar
[
Novikov AI, Novikova TP (2018) Non-destructive quality control of forest seeds in globalization: Problems and prospects of output innovative products. Globalization and Its Socio-Economic Consequences: 1260-1267
]Search in Google Scholar
[
Rahman A, Wang S, Yan J, Xu H (2021) Intact macadamia nut quality assessment using near-infrared spectroscopy and multivariate analysis. Journal of food composition and analysis 102: 104033. https://dx.doi.org/10.1016/j.jfca.2021.104033
]Search in Google Scholar
[
Rinnan Å, Van Den Berg F, Engelsen SB (2009) Review of the most common pre-processing techniques for near-infrared spectra. TrAC Trends in Analytical Chemistry 28(10): 1201-1222
]Search in Google Scholar
[
Shenk JS, Westerhaus MO (1993) Near infrared reflectance analysis with single and multiproduct calibrations. Crop Science 33(3): 582-584
]Search in Google Scholar
[
Son YM, Kim RH, Kang JT, Lee KS, Kim SW (2014) A practical application and development of carbon emission factors for 4 major species of warm temperate forest in Korea. Journal of Korean Forest Society 103(4): 593-598. https://dx.doi.org/10.14578/jkfs.2014.103.4.593
]Search in Google Scholar
[
Takahashi A, Shimada T, Kawano S (2011) Nondestructive determination of tannin content in intact individual acorns by near-infrared spectroscopy. Ecological Research 26(3): 679-685. https://dx.doi.org/10.1007/s11284-011-0823-6
]Search in Google Scholar
[
Tigabu M, Daneshvar A, Wu R, Ma X, Christer Odén P (2019) Rapid and non-destructive evaluation of seed quality of Chinese fir by near infrared spectroscopy and multivariate discriminant analysis. New Forests 51(3): 395-408. https://dx.doi.org/10.1007/s11056-019-09735-8
]Search in Google Scholar
[
Tigabu M, Fjellström J, Odén PC, Teketay D (2007) Germination of Juniperus procera seeds in response to stratification and smoke treatments, and detection of insect-damaged seeds with VIS + NIR spectroscopy. New Forests 33(2): 155-169. https://dx.doi.org/10.1007/s11056-006-9020-9
]Search in Google Scholar
[
Tigabu M, Odén PC (2002) Multivariate classification of sound and insect-infested seeds of a tropical multipurpose tree, Cordia africana, with near infrared reflectance spectroscopy. Journal of Near Infrared Spectroscopy 10(1): 45-51
]Search in Google Scholar
[
Wang J, Nakano K, Ohashi S, Takizawa K, He J (2010) Comparison of different modes of visible and near-infrared spectroscopy for detecting internal insect infestation in jujubes. Journal of Food Engineering 101(1): 78-84
]Search in Google Scholar
[
Wang Z, Künnemeyer R, McGlone A, Burdon J (2020) Potential of Vis-NIR spectroscopy for detection of chilling injury in kiwifruit. Postharvest biology and technology 164: 111160. https://dx.doi.org/10.1016/j.postharvbio.2020.111160
]Search in Google Scholar
[
Wati RK, Pahlawan MFR, Masithoh RE (2021) Development of calibration model for pH content of intact tomatoes using a low-cost Vis/NIR spectroscopy. In: 2021 IOP Conference Series: Earth and Environmental Science.: Earth Environmental Science. Bristol: IOP Publishing, p 12049
]Search in Google Scholar
[
Xia K, Daws MI, Stuppy W, Zhou Z-K, Pritchard HW (2012) Rates of water loss and uptake in recalcitrant fruits of Quercus species are determined by pericarp anatomy. PLoS One 7(10): e47368-e47368. https://dx.doi.org/10.1371/journal.pone.0047368
]Search in Google Scholar
[
Zhang Z, Liu H, Chen D, Zhang J, Li H, Shen M, Pu Y, Zhang Z, Zhao J, Hu J (2022) SMOTE-based method for balanced spectral nondestructive detection of moldy apple core. Food control 141: 109100. https://dx.doi.org/10.1016/j.foodcont.2022.109100
]Search in Google Scholar