基于产量反应和农学效率的番茄智能化推荐施肥方法研究  

Construction of intelligent fertilizer recommendation method for tomato based on yield response and agronomic efficiency

作　　者：杨秉庚 刘梦娇 丁文成[1] 徐新朋[1] 李明悦[2] 何萍[1] 周卫[1] YANG Bing-geng;LIU Meng-jiao;DING Wen-cheng;XU Xin-peng;Li Ming-yue;HE Ping;ZHOU Wei(Institute of Agricultural Resources and Regional Planning,Chinese Academy of Agricultural Sciences/State Key Laboratory of Efficient Utilization of Arid and Semi-arid Arable Land in Northern China/Key Laboratory of Plant Nutrition and Fertilizer,Ministry of Agriculture and Rural Affairs,Beijing 100081,China;Tianjin Institute of Agriculture Resource and Environment Sciences,Tianjin 300384,China)

机构地区：[1]中国农业科学院农业资源与农业区划研究所/北方干旱半干旱耕地高效利用全国重点实验室/农业农村部植物营养与肥料重点实验室,北京100081 [2]天津市农业资源与环境研究所,天津300384

出　　处：《植物营养与肥料学报》2024年第12期2296-2306,共11页Journal of Plant Nutrition and Fertilizers

基　　金：国家自然科学基金重点项目(32230093);农田智慧施肥项目(20221805)。

摘　　要：【目的】蔬菜种类多,养分需求特性各异。本研究构建基于产量反应和农学效率的番茄养分专家系统,并进行施肥推荐,为我国番茄生产提供科学轻简高效的推荐施肥方法。【方法】收集整理2000—2023年314个番茄田间试验数据,计算产量反应、相对产量、农学效率、养分内在效率等参数,利用QUEFTS模型估测不同目标产量下番茄的最佳养分需求参数,建立基于产量反应和农学效率的番茄养分专家系统。于2023年,在天津市和江苏徐州市共7个地点开展田间验证试验,设置农民习惯施肥(FP)、测土推荐施肥(ST)、番茄养分专家系统推荐施肥(NE)处理,以及基于NE的不施氮、不施磷和不施钾处理,共6个处理。调查了番茄产量、经济效益、植株氮磷钾养分吸收量、养分表观平衡和养分利用率。【结果】我国已有试验的平均结果为:番茄产量73.34 t/hm^(2),收获指数0.54 kg/kg,番茄地上部氮、磷和钾养分吸收量分别为218.60、52.66、370.14 kg/hm^(2),氮、磷和钾养分收获指数分别为0.51、0.52、0.52 kg/kg,氮、磷和钾养分内在效率分别为352.75、1445.45和209.64 kg/kg。QUEFTS模型结果表明,在达到潜在产量70%范围内,1 t番茄果实产量所需要的氮、磷和钾养分量分别为2.6、0.7和4.6 kg,氮、磷和钾养分需求比例约为3.8∶1.0∶6.8。番茄氮、磷、钾肥产量反应与相对产量呈极显著负线性相关关系(P<0.01);产量反应与农学效率呈极显著的二次曲线关系(P<0.01)。田间验证结果表明,与FP处理相比,NE处理氮、磷和钾肥施用量分别降低31.3%、59.2%和22.7%,而番茄产量和经济净效益分别提高2.0%和4.2%;与ST处理相比,NE处理减少了氮和磷肥施用量,增加了钾肥施用量。养分表观平衡结果显示,FP处理存在大量的氮磷钾养分盈余;ST处理氮和磷素盈余较高,钾素呈现亏缺状态;NE处理氮磷钾养分盈余量最接近于平衡。NE处理氮、磷和钾肥回【Objectives】The diverse types of vegetables have varying nutrient demand characteristics.We constructed a tomato Nutrient Expert system based on yield response and agronomic efficiency for fertilizer recommendation,aiming to provide a scientific,simplified,and efficient fertilizer recommendation method for tomato production in China.【Methods】We collected data from 314 tomato field experiments conducted between 2000 and 2023,calculated parameters such as yield response,relative yield,agronomic efficiency,and internal nutrient efficiency,and used the QUEFTS model to estimate the optimal nutrient demand parameters for tomatoes at different target yields.Based on this,we established a tomato Nutrient Expert system(NE)that incorporates yield response and agronomic efficiency.In 2023,field validation experiments were conducted at seven locations in Tianjin and Xuzhou of Jiangsu Province,with six treatments:farmer practice(FP),soil testing-based recommendation(ST),tomato Nutrient Expert system recommendation(NE),and three additional treatments based on NE but without N,P,or K application,respectively.Tomato yield,economic benefits,nutrient uptake by plants(N,P,K),apparent nutrient balance,and nutrient use efficiency were investigated.【Results】The average results from our existing experiments in China were:tomato yields 73.34 t/hm^(2),harvest index 0.54 kg/kg,the aboveground of plant uptake 218.60 kg/hm^(2)for N,52.66 kg/hm^(2)for P,and 370.14 kg/hm^(2)for K,with respective nutrient harvest indices of 0.51,0.52,and 0.52 kg/kg,and internal nutrient efficiencies of 352.75,1445.45,and 209.64 kg/kg for N,P,and K.The QUEFTS model results indicated that within the range of achieving 70%of potential yield,the amounts of N,P,and K required for 1 t of tomato fruit yield were constant,at 2.6,0.7,and 4.6 kg,respectively,with a nutrient demand ratio of approximately 3.8:1.0:6.8 for N:P:K.There was a highly significant negative linear correlation between tomato yield response to N,P,and K fertilizers and relative yield(P<

关 键 词：番茄 养分专家系统 产量反应 肥料利用率 推荐施肥 

分 类 号：S641.2[农业科学—蔬菜学]