基于物联网技术的简易大棚智慧管理技术应用研究

doi:10.16178/j.issn.0528-9017.20230987

摘要/Abstract

摘要：

当前我国90%以上的设施结构为简易型塑料大棚,人工经验管理效果较差,缺乏即时科学的种植管理技术指导。为探索简易大棚中的智慧种植管理技术,以简易大棚草莓为研究对象,基于物联网技术构建了简易大棚智慧种植平台,该平台包括专家种植标准、执行评价、专家答疑解惑、环境感知及健康诊断等功能,通过用户微信和计算机平台进行互动,可针对单品草莓实行全生育阶段24 h监测-分析-决策-管控。本平台物联网系统与高端智能温室相比,监测-分析-决策过程无明显差别,均由物联网系统智能运行,特色优势在于无需花费高额投入部署自动作业端,智能决策信息可由手机端微信传达到种植户,以人力代替自动作业设备实现管控,可极大降低部署成本。该平台应用后,试验项目实施区单个大棚:产量水分利用效率(WUE_y)、产值水分利用效率(WUE_p)分别提高了128.55%、226.42%;化肥用量降低了40%;农药投入成本降低了32.48%。平台根据草莓不同生育阶段以工艺单形式自动给种植户下达常规种植管理标准要求,并基于环境感知给每个种植户下达临时处置策略,可克服以往草莓种植户系统知识不足、体系化管理薄弱的问题。

关键词: 智慧种植, 物联网, 人工智能, 水分利用效率

Abstract:

At present, more than 90% of the facilities in China are basic plastic greenhouses, the effect of artificial experience management is poor, and there is a lack of immediate scientific planting management technical guidance. In order to explore the intelligent planting management technology in the basic greenhouse,the intelligent planting platform for the strawberry basic greenhouse was constructed based on the internet of things technology (IoT). The platform includes expert planting standard, executive evaluation, expert Q&A, environmental perception and health diagnosis functions. It interacts with the computer platform through the user's WeChat. 24 hours monitoring-analysis-decision-control during the whole growth stage can be carried out for single strawberry. Compared with high-end intelligent greenhouses, the IoT system of this platform has no obvious difference between the monitoring-analysis-decision process, which is intelligently operated by the IoT system. Its characteristic advantage is that there is no need to spend high investment to deploy the automatic operation terminal. The management and control can be realized by replacing the automatic operation equipment with manpower, which can greatly reduce the deployment cost. After the application of the platform, the single basic greenhouse in the implementation area of the test project: the water use efficiency (WUE_y) of yield and (WUE_p) of output value increased by 128.55% and 226.42%, respectively; fertilizer consumption has decreased by 40%; the input cost of pesticide was reduced by 32.48%. According to the different growth stages of strawberries, the platform automatically issued the requirements of normal planting management standards to growers in the form of process sheets, and issued temporary disposal strategies to each grower based on environmental perception, so as to overcome the problems of insufficient knowledge and weak systematic management among strawberry growers in the past.

Key words: intelligent planting, internet of things, artificial intelligence, water use efficiency

中图分类号:

王维宝, 李群. 基于物联网技术的简易大棚智慧管理技术应用研究[J]. 浙江农业科学, 2025, 66(1): 251-260.

WANG Weibao, LI Qun. Research on application of intelligent management technology in basic greenhouse based on internet of things technology[J]. Journal of Zhejiang Agricultural Sciences, 2025, 66(1): 251-260.

图/表 11

参考文献 29

[1]	ZORBAS D, ABDELFADEEL K, KOTZANIKOLAOU P, et al. TS-LoRa: time-slotted LoRaWAN for the Industrial Internet of Things[J]. Computer Communications, 2020, 153: 1-10.
[2]	彭焘. 互联互通理念下跨境电商物流发展策略研究[J]. 商业经济, 2020(2): 50-51, 88.
[3]	LUSIKKA T, KINNUNEN T K, KOSTIAINEN J. Public transport innovation platform boosting intelligent transport system value chains[J]. Utilities Policy, 2020, 62: 100998.
[4]	成福伟. 发达国家现代农业园区的发展模式及借鉴[J]. 世界农业, 2017(1): 13-17.
[5]	姚於康. 国外设施农业智能化发展现状、基本经验及其借鉴[J]. 江苏农业科学, 2011, 39(1): 3-5.
[6]	唐珂. 国外农业物联网技术发展及对我国的启示[J]. 中国科学院院刊, 2013, 28(6): 700-707.
[7]	PAWLOWSKI A, GUZMAN J L, RODRÍGUEZ F, et al. Simulation of greenhouse climate monitoring and control with wireless sensor network and event-based control[J]. Sensors, 2009, 9(1): 232-252.
[8]	PAHUJA R, VERMA H K, UDDIN M. A wireless sensor network for greenhouse climate control[J]. IEEE Pervasive Computing, 2013, 12(2): 49-58.
[9]	SRBINOVSKA M, GAVROVSKI C, DIMCEV V, et al. Environmental parameters monitoring in precision agriculture using wireless sensor networks[J]. Journal of Cleaner Production, 2015, 88: 297-307.
[10]	AIELLO G, GIOVINO I, VALLONE M, et al. A decision support system based on multisensor data fusion for sustainable greenhouse management[J]. Journal of Cleaner Production, 2018, 172: 4057-4065.
[11]	FERENTINOS K P, KATSOULAS N, TZOUNIS A, et al. Wireless sensor networks for greenhouse climate and plant condition assessment[J]. Biosystems Engineering, 2017, 153: 70-81.
[12]	PARK D H, KANG B J, CHO K R, et al. A study on greenhouse automatic control system based on wireless sensor network[J]. Wireless Personal Communications, 2011, 56(1): 117-130.
[13]	PARK D H, PARK J W. Wireless sensor network-based greenhouse environment monitoring and automatic control system for dew condensation prevention[J]. Sensors, 2011, 11(4): 3640-3651.
[14]	KATSOULAS N, FERENTINOS K P, TZOUNIS A, et al. Spatially distributed greenhouse climate control based on wireless sensor network measurements[J]. Acta Horticulturae, 2017(1154): 111-120.
[15]	ROWSHON M K, DLAMINI N S, MOJID M A, et al. Modeling climate-smart decision support system (CSDSS) for analyzing water demand of a large-scale rice irrigation scheme[J]. Agricultural Water Management, 2019, 216: 138-152.
[16]	BIABI H, ABDANAN MEHDIZADEH S, SALEHI SALMI M. Design and implementation of a smart system for water management of lilium flower using image processing[J]. Computers and Electronics in Agriculture, 2019, 160: 131-143.
[17]	李莉莉. 华东型连栋塑料温室环境智能控制系统的研究[D]. 上海: 上海交通大学, 2013.
[18]	赵立安, 李修华, 周永华, 等. 基于农业物联网的火龙果生长环境大数据分析[J]. 节水灌溉, 2018(3): 58-62.
[19]	廖建尚. 基于物联网的温室大棚环境监控系统设计方法[J]. 农业工程学报, 2016, 32(11): 233-243.
[20]	包志炎, 王学斌, 张海波, 等. 基于物联网和云架构的渠灌闸门智能控制系统[J]. 农业机械学报, 2017, 48(11): 222-228.
[21]	葛文杰, 赵春江. 农业物联网研究与应用现状及发展对策研究[J]. 农业机械学报, 2014, 45(7): 222-230, 277.
[22]	李道亮, 杨昊. 农业物联网技术研究进展与发展趋势分析[J]. 农业机械学报, 2018, 49(1): 1-20.
[23]	余欣荣. 关于发展农业物联网的几点认识[J]. 中国科学院院刊, 2013, 28(6): 679-685.
[24]	徐增祥, 金涛, 田洪暄. 农业物联网设备在日光温室中的应用及推广模式[J]. 天津农业科学, 2018, 24(11): 38-41, 61.
[25]	齐飞, 李恺, 李邵, 等. 世界设施园艺智能化装备发展对中国的启示研究[J]. 农业工程学报, 2019, 35(2): 183-195.
[26]	GUSTA L V, TRISCHUK R, WEISER C J. Plant cold acclimation: the role of abscisic acid[J]. Journal of Plant Growth Regulation, 2005, 24(4): 308-318.
[27]	LI S X, WANG Z H, LI S Q, et al. Effect of plastic sheet mulch, wheat straw mulch, and maize growth on water loss by evaporation in dryland areas of China[J]. Agricultural Water Management, 2013, 116: 39-49.
[28]	VIAL L K, LEFROY R D B, FUKAI S. Application of mulch under reduced water input to increase yield and water productivity of sweet corn in a lowland rice system[J]. Field Crops Research, 2015, 171: 120-129.
[29]	JIN S S, WANG Y K, SHI L G, et al. Effects of pruning and mulching measures on annual soil moisture, yield, and water use efficiency in jujube (Ziziphus jujube Mill.) plantations[J]. Global Ecology and Conservation, 2018, 15: e00406.

处理	试验大棚个数	策略与技术支持	说明
T1	9	物联网专家灌溉策略+物联网体系化管理策略	试验大棚应用全套系统指导服务
T2	3	种植户经验灌溉策略+物联网体系化管理策略	试验大棚仅提供除灌溉外的管理指导服务
T3	9	物联网专家灌溉策略+种植户经验管理策略	试验大棚仅提供灌溉指导服务
CK	12	种植户经验灌溉策略+种植户经验管理策略	试验大棚全部由种植户按照习惯作业

处理	试验大棚个数	策略与技术支持	说明
T1	9	物联网专家灌溉策略+物联网体系化管理策略	试验大棚应用全套系统指导服务
T2	3	种植户经验灌溉策略+物联网体系化管理策略	试验大棚仅提供除灌溉外的管理指导服务
T3	9	物联网专家灌溉策略+种植户经验管理策略	试验大棚仅提供灌溉指导服务
CK	12	种植户经验灌溉策略+种植户经验管理策略	试验大棚全部由种植户按照习惯作业

年份	试验处理	上市日期 (月-日)	单价/ (元·kg^-1)	667 m²产量/ kg	WUE_y/ (kg·m^-3)	WUE_p/ (元·m^-3)
2018	T1	12-16	60	1 776.97±71.69 a	17.85±0.72 a	1 070.78±43.20 a
	T2	12-16	60	1 565.12±96.12 b	14.98±1.05 b	856.21±66.34 b
	T3	12-28	42	1 093.77±137.96 c	10.98±1.39 c	659.10±83.13 c
	CK	12-28	42	898.22±213.91 d	7.81±1.86 d	328.04±78.12 d
2019	T1	12-16	60	1 896.97±62.13 a	17.94±0.7 a	1 148.01±40.98 a
	T2	12-16	60	1 681.12±81.24 b	15.12±1.03 b	885.29±65.22 b
	T3	12-28	42	1 216.27±118.67 c	11.21±1.37 c	701.43±78.38 c
	CK	12-28	42	724.36±251.39 d	7.38±1.89 d	301.63±84.19 d

年份	试验处理	上市日期 (月-日)	单价/ (元·kg^-1)	667 m²产量/ kg	WUE_y/ (kg·m^-3)	WUE_p/ (元·m^-3)
2018	T1	12-16	60	1 776.97±71.69 a	17.85±0.72 a	1 070.78±43.20 a
	T2	12-16	60	1 565.12±96.12 b	14.98±1.05 b	856.21±66.34 b
	T3	12-28	42	1 093.77±137.96 c	10.98±1.39 c	659.10±83.13 c
	CK	12-28	42	898.22±213.91 d	7.81±1.86 d	328.04±78.12 d
2019	T1	12-16	60	1 896.97±62.13 a	17.94±0.7 a	1 148.01±40.98 a
	T2	12-16	60	1 681.12±81.24 b	15.12±1.03 b	885.29±65.22 b
	T3	12-28	42	1 216.27±118.67 c	11.21±1.37 c	701.43±78.38 c
	CK	12-28	42	724.36±251.39 d	7.38±1.89 d	301.63±84.19 d

时间节点	T1和T2			T3和 CK
时间节点	肥料配方	用量/kg	费用/元	肥料配方	用量/kg	费用/元
定植前14 d	腐熟有机肥、硫酸钾复合肥、硫酸亚铁、硫酸锌、硼砂	腐熟有机肥:3 000 化肥:72 新型肥料:28	1 440	农家肥、氮磷钾复合肥	农家肥:4 000 化肥:120	1 114
铺设地膜前	草莓1号微生物菌肥			氮磷钾复合肥
果实膨大初期	种霸3号叶面肥			氮磷钾复合肥
顶果采收初期	种霸5号腐殖酸水溶肥			氮磷钾复合肥
收获高峰	氮磷钾复合肥			氮磷钾复合肥
早春腋花序开花	草莓1号微生物菌肥			氮磷钾复合肥
早春腋花序结果	种霸3号叶面肥			氮磷钾复合肥