Study on Ebb-and-flow Mode Parameters of Smart Tobacco Seedling Cultivation

doi:10.11924/j.issn.1000-6850.casb2025-0096

Abstract

Abstract:

Seedling cultivation based on ebb-and-flow irrigation mode is a new type technology with water-saving, fertilizer-reducing and efficient-improving characteristics, in which ebb-and-flow parameters play a key role. To clarify the appropriate ebb-and-flow parameters in tobacco seedling cultivation, this study conducted a uniform design experiment on irrigation interval frequency, nutrient concentration, and liquid supply height. Both main effect analysis and comprehensive contribution rate analysis showed that irrigation interval frequency had the greatest impact, followed by nutrient concentration and liquid supply height. The interaction effects were significantly greater than the single factor main effect. The ridge regression model was optimized with irrigation interval frequency of 30.50 h/time, nutrient concentration of 153.94 mg/L, and liquid supply height of 3.84 cm, which could stably obtain the best seedling. Furthermore, the ebb-and-flow parameter for optimization management plan were irrigation interval frequency of 28.8-30.5 h/time, nutrient concentration of 153-154 mg/L, and liquid supply height of 3.8-3.9 cm, respectively.

Key words: tobacco, seedling cultivation based on ebb-and-flow irrigation mode, ebb-and-flow parameters, strong seedling evaluation, single factor effect analysis, contribution rate, model optimization

GAO Siman, LIU Guangliang, DUAN Wuli, YANG Na, DONG Xingmei, CHEN Aiguo. Study on Ebb-and-flow Mode Parameters of Smart Tobacco Seedling Cultivation[J]. Chinese Agricultural Science Bulletin, 2025, 41(23): 38-44.

Figures/Tables 8

References 32

[1]	赵书坤, 刘光亮, 尹海静, 等. 分段施肥对烤烟漂浮育苗幼苗生长发育的影响[J]. 江西农业大学学报, 2024, 46(1):25-41.
[2]	潘可可, 王克磊, 苏世闻, 等. 潮汐灌溉对番茄苗期生长及基质水分耗散的影响[J]. 福建农业学报, 2023, 38(7):817-823.
[3]	GIACOMELLI G A, van WEEL P A, BLOK C. Ebb and flood nutrient delivery system for sustainable automated crop production[J]. Acta horticulturae, 2020, 1296:1129-1136.
[4]	AVELLAR G S, CAMPOS W G, CARVALHO L M, et al. Life table of Rhodobium porosum on rose cultivars in subsurface ‘ebb and flow’ irrigation system[J]. International journal of plant & soil science, 2021, 33(17):60-69.
[5]	CAROTTI L, PISTILLO A, ZAULI I, et al. Improving water use efficiency in vertical farming: Effects of growing systems, far-red radiation and planting density on lettuce cultivation[J]. Agricultural water management, 2023, 285:108365.
[6]	赵春江. 智慧农业的发展现状与未来展望[J]. 华南农业大学学报, 2021, 42(6):1-7.
[7]	王研. 不同育苗方式与灌溉量对西葫芦幼苗生长的影响[D]. 太谷: 山西农业大学, 2022.
[8]	李倩, 董春娟, 田雅楠, 等. 潮汐灌溉供液高度对黄瓜穴盘苗生长发育与水肥利用的影响[J]. 中国蔬菜, 2020(1):56-62.
[9]	黄国栋, 刘光亮, 陈天才, 等. 烟苗壮苗指数构建与生长过程素质评估[J]. 安徽农业大学学报, 2024, 51(1):28-35.
[10]	中国烟草总公司青州烟草研究所. YC/T 142—2010,烟草农艺性状调查测量方法[S]. 北京: 中国标准出版社, 2010.
[11]	陶靖轩. 析因试验与因子贡献率[J]. 数学的实践与认识, 2006, 36(11):105-109.
[12]	MÉNDEZ-CIFUENTES A, VALDEZ-AGUILAR L A, CADENA-ZAPATA M, et al. Water and fertilizer use efficiency in subirrigated containerized tomato[J]. Water, 2020, 12:1313.
[13]	董春娟, 张晓蕊, 尚庆茂. 蔬菜潮汐式育苗技术应用概况与研究进展[J]. 贵州农业科学, 2018(3):16-26.
[14]	王克磊, 朱隆静, 苏世闻, 等. 潮汐灌溉频率对花椰菜幼苗生长的影响[J]. 江西农业学报, 2020, 32(9):45-48.
[15]	MÉNDEZ-CIFUENTES A, VALDEZ-AGUILAR L A, CADENA-ZAPATA M, et al. Nutrient solution electrical conductivity affects yield and growth of sub-irrigated tomatoes[J]. Horticulturae, 2023, 9(7):826.
[16]	FAYEZIZADEH M R, ANSARI N A Z, ALBAJI M, et al. Effects of hydroponic systems on yield, water productivity and stomatal gas exchange of greenhouse tomato cultivars[J]. Agricultural water management, 2021, 258:107171.
[17]	FERRANTE A, TOSCANO S, ROMANO D. Light quality and intensity modulation on yield and quality on crops grown in vertical farms[J]. European journal of horticultural science, 2024, 89(5):1-8.
[18]	赵书坤. 烤烟漂浮育苗一次施肥技术研究[D]. 北京: 中国农业科学院, 2024.
[19]	ZAMBON F T, MEADOWS T D, ECKMAN M A, et al. Automated ebb-and-flow subirrigation accelerates citrus liner production in treepots[J]. Agricultural water management, 2022, 262:107387.
[20]	ANLAUF R, MUHAMMED H H A, REINEKE T. Water retention properties of wood fiber based growing media and their impact on irrigation strategy[J]. Acta horticulturae, 2024, 1389:227-235.
[21]	RANJIT P S, RAJU V, MAHESH G S, et al. IoT-based smart irrigation systems for smart agriculture. In Internet of things for agriculture 4.0[M]. New York: Apple academic press,2022:35-90.
[22]	SOHELI S J, JAHAN N, HOSSAIN M B, et al. Smart greenhouse monitoring system using internet of things and artificial intelligence[J]. Wireless personal communications, 2022, 124:3603-3634.
[23]	SUMARUDIN A, ISMANTOHADI E, PUSPANINGRUM A, et al. Implementation irrigation system using Support Vector Machine for precision agriculture based on IoT[J]. IOP Conference Series: materials science and engineering, 2021, 1098(3):32098.
[24]	NAGHEDIFAR S M, ZIAEI A N. EBMAN-HP: A parallel model for simulation of sensor-based ebb-and-flow subirrigation systems[J]. Agricultural water management, 2023, 275:108007.
[25]	MARAVEAS C, PIROMALIS D, ARVANITIS K G, et al. Applications of IoT for optimized greenhouse environment and resources management[J]. Computers and electronics in agriculture, 2022, 198:106993.
[26]	郭威, 吴华瑞, 郭旺, 等. 特色农产品设施环境下品质智能管控技术研究现状与展望[J]. 智慧农业(中英文), 2024, 6(6):44-62.
[27]	LIN Y S, FANG S L, KANG L, et al. Combining recurrent neural network and sigmoid growth models for short-term temperature forecasting and tomato growth prediction in a plastic greenhouse[J]. Horticulturae, 2024, 10(3):230.
[28]	MUHAMMED D, AHVAR E, AHVAR S, et al. Artificial Intelligence of Things (AIoT) for smart agriculture: A review of architectures, technologies and solutions[J]. Journal of network and computer applications, 2024, 228:103905.
[29]	OUBEHAR H, SELMANI A, ED-DAHHAK A, et al. ANFIS-based climate controller for computerized greenhouse system[J]. Advances in science, technology and engineering systems, 2020, 5(1):8-12.
[30]	胡瑾, 杨永霞, 李远方, 等. 温室环境控制方法研究现状分析与展望[J]. 农业工程学报, 2024, 40(1):112-128.
[31]	HOU H, JAWADDI S, ISMAIL A, et al. Energy efficient task scheduling based on deep reinforcement learning in cloud environment: A specialized review[J]. Future generation computer systems, 2024, 151:214-231.
[32]	XIA Y, CHEN X, SUN S, et al. Data-knowledge co-driven innovations in engineering and management[J]. Patterns, 2024, 5(12):1-4.

处理	灌溉间歇频次(x₁)	养分浓度(x₂)	供液高度(x₃)
T₁	-1（1天2次）	0(150 mg/L)	1(5 cm)
T₂	0（1天1次）	0(150 mg/L)	0(4 cm)
T₃	1（2天1次）	0(150 mg/L)	-1(3 cm)
T₄	0（1天1次）	-1(130 mg/L)	-1(3 cm)
T₅	-1（1天2次）	-1(130 mg/L)	0(4 cm)
T₆	0（1天1次）	1(170 mg/L)	1(5 cm)
T₇	-1（1天2次）	1(170 mg/L)	-1(3 cm)
T₈	1（2天1次）	-1(130 mg/L)	1(5 cm)
T₉	1（2天1次）	1(170 mg/L)	0(4 cm)

处理	灌溉间歇频次(x₁)	养分浓度(x₂)	供液高度(x₃)
T₁	-1（1天2次）	0(150 mg/L)	1(5 cm)
T₂	0（1天1次）	0(150 mg/L)	0(4 cm)
T₃	1（2天1次）	0(150 mg/L)	-1(3 cm)
T₄	0（1天1次）	-1(130 mg/L)	-1(3 cm)
T₅	-1（1天2次）	-1(130 mg/L)	0(4 cm)
T₆	0（1天1次）	1(170 mg/L)	1(5 cm)
T₇	-1（1天2次）	1(170 mg/L)	-1(3 cm)
T₈	1（2天1次）	-1(130 mg/L)	1(5 cm)
T₉	1（2天1次）	1(170 mg/L)	0(4 cm)

处理	株高/cm	SPAD	全株鲜重/g	地上干重/g	壮苗评估值
T₁	2.533	32.817	2.069	0.125	35.607
T₂	5.767	28.250	3.671	0.225	40.264
T₃	1.867	34.767	1.051	0.075	14.950
T₄	4.867	26.033	2.708	0.200	29.371
T₅	3.467	34.633	2.093	0.154	32.178
T₆	4.667	28.517	4.164	0.400	111.409
T₇	5.567	35.000	2.903	0.160	34.061
T₈	5.533	24.000	2.162	0.123	11.522
T₉	2.167	31.083	1.710	0.110	26.957
Pearson相关系数	0.2052	-0.096	0.7729^*	0.9371^**

处理	株高/cm	SPAD	全株鲜重/g	地上干重/g	壮苗评估值
T₁	2.533	32.817	2.069	0.125	35.607
T₂	5.767	28.250	3.671	0.225	40.264
T₃	1.867	34.767	1.051	0.075	14.950
T₄	4.867	26.033	2.708	0.200	29.371
T₅	3.467	34.633	2.093	0.154	32.178
T₆	4.667	28.517	4.164	0.400	111.409
T₇	5.567	35.000	2.903	0.160	34.061
T₈	5.533	24.000	2.162	0.123	11.522
T₉	2.167	31.083	1.710	0.110	26.957
Pearson相关系数	0.2052	-0.096	0.7729^*	0.9371^**

指标	SS_变因	SS_总	贡献率/%	排序
灌溉间歇频次	0.4603	1.0000	43.03	1
养分浓度	0.3836	1.0000	38.36	2
供液高度	0.0848	1.0000	8.48	3