|
|
|
|
|
|
Study on the Effects of Planting Years of Vegetable Greenhouse on the
Cucumber Qualties Using Mid-IR Spectroscopoy |
ZHANG Yan-ru1, 2, SHAO Peng-shuai1* |
1. Shandong Key Laboratory of Eco-Environmental Science for the Yellow River Delta, Binzhou University, Binzhou 256603, China
2. College of Life Science, Shandong Agricultural University, Taian 271018, China
|
|
|
Abstract Greenhouse vegetable cultivation plays a crucial role in global vegetable supply. The planting year of vegetable greenhouses greatly affects vegetable yield and quality, whereas the study on vegetable quality using infrared spectroscopy is still unclear. Therefore, the mid-IR spectroscopy was used to detect how planting year of vegetable greenhouses (i.e., 1 year, 10 years, and 18 years) influenced cucumber quality by analyzing the specific peaks of cucumber fruits and leaves. In our study, the polysaccharides and protein components in cucumber fruits initially increased (the highest in 10 years) and subsequently decreased during the progression of the planting year. Raising planting years (i.e., 10 years and 18 years) increased lignin components of cucumber fruits (mainly in cucumber peel), which reduced the cucumber’s taste. In addition, the ratio of organic components in cucumber can reflect cucumber quality under different greenhouse planting years. Polysaccharide/protein components and polysaccharide/lignin components in 18 years were significantly lower than those in 1 year and 10 years, implying that cucumbers of 1 year and 10 years had well-balanced carbohydrates and nutrients. Our finding suggests that short-term planting years (e.g., within 10 years) can improve cucumber quality, but long-term planting years inhibit cucumber quality. Therefore, comprehensively considering cucumber quality, we suggested that the planting year of the cucumber greenhouse should not be too long. Additionally, the organic components of cucumber leaves showed a similar trend to organic cucumber components across greenhouse planting years. Linear regression analysis demonstrated that cucumber fruits’ protein and lignin components were positively associated with the protein and lignin components of cucumber leaves, which indicated that cucumber leaves might represent the nutrient and taste cucumber fruit. Overall, this study revealed the changes in organic cucumber components by mid-IR spectroscopy paralleled changed cucumber quality, providing scientific evidence for vegetable greenhouses management and improving vegetable quality.
|
Received: 2021-11-03
Accepted: 2022-01-21
|
|
Corresponding Authors:
SHAO Peng-shuai
E-mail: pshshao@163.com
|
|
[1] MA Jun-li(马俊礼). The Farmers Consultant(农家参谋),2021,5: 67.
[2] ZENG Xi-bai,BAI Ling-yu,SU Shi-ming,et al(曾希柏,白玲玉,苏世鸣,等). Acta Ecologica Sinica(生态学报),2010,30(7): 1853.
[3] Hu W,Zhang Y,Huang B,et al. Chemosphere,2017,170: 183.
[4] ZHU Yu-qing,WANG Jun(朱余清,王 军). Jiangsu Agricultural Sciences(江苏农业科学),2012,40(9): 152.
[5] YUE Huan-fang,WANG Ke-wu,MENG Fan-yu,et al(岳焕芳,王克武,孟范玉,等). Vegetables(蔬菜),2020,(9): 45.
[6] LI Zheng-pu,TONG Jing,WANG Li-ping,et al(李政璞,佟 静,王丽萍,等). China Vegetables(中国蔬菜),2020,(12): 56.
[7] Aykas D P,Borba K R,Rodriguez-Saona L E. Foods,2020,9(9):1300.
[8] WANG Dong,WU Jing-zhu,HAN Ping,et al(王 冬,吴静珠,韩 平,等). Spectroscopy and Spectral Analysis(光谱学与光谱分析),2021,41(5): 1593.
[9] LI Tian-hua, CHEN Gong-fei, LIU Guang-wei, et al(李天华,陈龚飞,刘光伟,等). Computers and Applied Chemistry(计算机与应用化学),2014,31(4):494.
[10] ZHANG Peng,LI Jiang-kuo,CHEN Shao-hui(张 鹏,李江阔,陈绍慧). Storage and Process(保鲜与加工),2013,13(3): 1.
[11] GAO Meng-chao,MI Chun-li,SHI Yi(高孟朝,米春利,施 怡). China Food Safety Magazine(食品安全导刊),2018,(33): 67.
[12] Calderón F,Haddix M,Conant R,et al. Soil Science Society of America Journal,2013,77: 1591.
[13] ZHU Yi(朱 熠). China Food Safety Magazine(食品安全导刊),2021,(9): 180.
[14] Suseela V,Tharayil N,Xing B,et al. New Phytologist,2013,200: 122.
[15] HE Xiao-qin,ZHANG Yong-qing,YAN Jiao,et al(贺小琴,张永清,闫 姣,等). Journal of Agriculture(农学学报),2014,4(8): 43.
[16] DU Qing-jie, YANG Ya-yong, ZHANG Jia-xin, et al(杜清洁,杨亚勇,张嘉欣,等). Journal of China Agricultural University(中国农业大学学报),2021,26(7):45.
[17] YU Li-mei,LIU Xiao-jing,NONG Zhong-wen,et al(于立梅,刘晓静,农仲文,等). Modern Food Science and Technology(现代食品科技),2017,33(11): 70.
[18] XUE Shu-dan,XIE Da-sen,WAN Xiao-tong,et al(薛舒丹,谢大森,万小童,等). Guangdong Agricultural Sciences(广东农业科学),2021,48(9): 142.
[19] Figueroa N E,Gatica-Meléndez C,Figueroa C R. Food Chemistry,2021,358: 129913.
[20] YAN Geng-wu,FAN Bing-quan(闫庚戌,范丙全). Soil and Fertilizer Sciences in China(中国土壤与肥料),2019,(4): 187.
[21] ZHU Hai-yan,LI Ting-ting(祝海燕,李婷婷). China Cucurbits and Vegetables(中国瓜菜),2019,32(5): 45.
[22] CAO Jian-ting,YANG Hong,PENG Yan,et al(曹舰艇,杨 红,彭 艳,等). Journal of Northwest A&F University·Natural Science Edition(西北农林科技大学学报·自然科学版),2019,47(8): 117.
[23] NING De-fu,KONG Li-qiong,TANG Na,et al(宁德富,孔丽琼,汤 娜,等). Journal of Sichuan Agricultural University(四川农业大学学报),2016,34(1): 67.
[24] DUAN Hui-min,LU Xiao,ZHOU Xiao-jie,et al(段惠敏,卢 潇,周晓洁,等). Crops(作物杂志),2021,(1): 160.
[25] WU Yang,YAO Xiao-hua,HE Zheng-sheng,et al(吴 杨,姚小华,何正盛,等). Journal of Zhejiang University·Agriculture and Life Sciences(浙江大学学报·农业与生命科学版),2021,47(2): 147.
|
[1] |
YANG Cheng-en1, 2, LI Meng3, LU Qiu-yu2, WANG Jin-ling4, LI Yu-ting2*, SU Ling1*. Fast Prediction of Flavone and Polysaccharide Contents in
Aronia Melanocarpa by FTIR and ELM[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 62-68. |
[2] |
DUAN Ming-xuan1, LI Shi-chun1, 2*, LIU Jia-hui1, WANG Yi1, XIN Wen-hui1, 2, HUA Deng-xin1, 2*, GAO Fei1, 2. Detection of Benzene Concentration by Mid-Infrared Differential
Absorption Lidar[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3351-3359. |
[3] |
LIU Bo-yang1, GAO An-ping1*, YANG Jian1, GAO Yong-liang1, BAI Peng1, Teri-gele1, MA Li-jun1, ZHAO San-jun1, LI Xue-jing1, ZHANG Hui-ping1, KANG Jun-wei1, LI Hui1, WANG Hui1, YANG Si2, LI Chen-xi2, LIU Rong2. Research on Non-Targeted Abnormal Milk Identification Method Based on Mid-Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 3009-3014. |
[4] |
LIU Si-qi1, FENG Guo-hong1*, TANG Jie2, REN Jia-qi1. Research on Identification of Wood Species by Mid-Infrared Spectroscopy Based on CA-SDP-DenseNet[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(03): 814-822. |
[5] |
YANG Cheng-en1, SU Ling2, FENG Wei-zhi1, ZHOU Jian-yu1, WU Hai-wei1*, YUAN Yue-ming1, WANG Qi2*. Identification of Pleurotus Ostreatus From Different Producing Areas Based on Mid-Infrared Spectroscopy and Machine Learning[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(02): 577-582. |
[6] |
LI Xiao1, CHEN Yong2, MEI Wu-jun3*, WU Xiao-hong2*, FENG Ya-jie1, WU Bin4. Classification of Tea Varieties Using Fuzzy Covariance Learning
Vector Quantization[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(02): 638-643. |
[7] |
FENG Hai-zhi1, LI Long1*, WANG Dong2, ZHANG Kai1, FENG Miao1, SONG Hai-jiang1, LI Rong1, HAN Ping2. Progress of the Application of MIR and NIR Spectroscopies in Quality
Testing of Minor Coarse Cereals[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(01): 16-24. |
[8] |
BAI Zi-jin1, PENG Jie1*, LUO De-fang1, CAI Hai-hui1, JI Wen-jun2, SHI Zhou3, LIU Wei-yang1, YIN Cai-yun1. A Mid-Infrared Spectral Inversion Model for Total Nitrogen Content of Farmland Soil in Southern Xinjiang[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(09): 2768-2773. |
[9] |
YANG Cheng-en1, WU Hai-wei1*, YANG Yu2, SU Ling2, YUAN Yue-ming1, LIU Hao1, ZHANG Ai-wu3, SONG Zi-yang3. A Model for the Identification of Counterfeited and Adulterated Sika Deer Antler Cap Powder Based on Mid-Infrared Spectroscopy and Support
Vector Machines[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(08): 2359-2365. |
[10] |
XIAO Shi-jie1, WANG Qiao-hua1, 2*, LI Chun-fang3, 4, DU Chao3, ZHOU Zeng-po4, LIANG Sheng-chao4, ZHANG Shu-jun3*. Nondestructive Testing and Grading of Milk Quality Based on Fourier Transform Mid-Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(04): 1243-1249. |
[11] |
ZHOU Jun1, 2, YANG Yang2, YAO Yao2, LI Zi-wen3, WANG Jian3, HOU Chang-jun1*. Application of Mid-Infrared Spectroscopy in the Analysis of Key Indexes of Strong Flavour Chinese Spirits Base Liquor[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(03): 764-768. |
[12] |
CHEN Feng-xia1, YANG Tian-wei2, LI Jie-qing1, LIU Hong-gao3, FAN Mao-pan1*, WANG Yuan-zhong4*. Identification of Boletus Species Based on Discriminant Analysis of Partial Least Squares and Random Forest Algorithm[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(02): 549-554. |
[13] |
XIAO Shi-jie1, WANG Qiao-hua1, 2*, FAN Yi-kai3, LIU Rui3, RUAN Jian3, WEN Wan4, LI Ji-qi4, SHAO Huai-feng4, LIU Wei-hua5, ZHANG Shu-jun3*. Rapid Determination of αs1-Casein and κ-Casein in Milk Based on Fourier Transform Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2021, 41(12): 3688-3694. |
[14] |
LIN Yan1, XIA Bo-hou1, LI Chun2, LIN Li-mei1, LI Ya-mei1*. Rapid Identification of Crude and Processed Polygonui Multiflori Radix With Mid-IR and Pattern Recognition[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2021, 41(12): 3708-3711. |
[15] |
SUN Di1, 2, LI Meng-ting1, MU Mei-rui1, ZHAO Run1*, ZHANG Ke-qiang1*. Rapid Determination of Nitrogen and Phosphorus in Dairy Farm Slurry Via Near-Mid Infrared Fusion Spectroscopy Technology[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2021, 41(10): 3092-3098. |
|
|
|
|