Evaluation of nitrogen requirement and efficiency of rice in the region of Yangtze River Valley based on large-scale field experiments

Overestimation of nitrogen(N) uptake requirement is one of the driving forces of the overuse of N fertilization and the low efficiency of N use in China. In this study, we collected data from 1 844 site-years of rice(Oryza sativa L.) under various rotation cropping systems across the Yangtze River Valley. Selected treatments included without(N0 treatment) and with N application(N treatment) which were recommended by local technicians, with a wide grain range of 1.5–11.9 t ha–1. Across the 1 844 site-years, over 96% of the sites showed yield increase(relative yield105%) with N fertilization, and the increase rates decreased from 78.9 to 16.2% within the lowest range 4.0 to the highest 6.5 t ha–1. To produce one ton of grain, the rice absorbed approximately 17.8 kg N in the N0 treatment and 20.4 kg N in the N treatment. The value of partial factor productivity by N(PFP N) reached a range of 35.2–51.4 kg grain kg–1 with N application under the current recommended N rate. Averaged recovery rate of N(RE N) was above 36.0% in yields below 6.0 t ha–1 and lower than 31.7% in those above 6.0 t ha–1. Soil properties only affected yield increments within low rice yield levels(5.5 t ha–1). There is a poor relationship between N application rates and indigenous nitrogen supply(INS). From these observations and considering the local INS, we concluded there was a great potential for improvement in regional grain yield and N efficiency.     

Evaluation of mid-season sensor based nitrogen fertilizer recommendations for winter wheat using different estimates of yield potential

Optical sensors, coupled with mathematical algorithms, have proven effective at determining more accurate mid-season nitrogen (N) fertilizer recommendations in winter wheat. One parameter required in making these recommendations is in-season grain yield potential at the time of sensing. Four algorithms, with different methods for determining grain yield potential, were evaluated for effectiveness to predict final grain yield and the agronomic optimum N rate (AONR) at 34 site-years. The current N fertilizer optimization algorithm (CNFOA) outperformed the other three algorithms at predicting yield potential with no added N and yield potential with added N (R² = 0.46 and 0.25, respectively). However, no differences were observed in the amount of variability accounted for among all four algorithms in regards to predicting the AONR. Differences were observed in that the CNFOA and proposed N fertilizer optimization algorithm (PNFOA), under predicted the AONR at approximately 75 % of the site-years; whereas, the generalized algorithm (GA) and modified generalized algorithm (MGA) recommended N rates under the AONR at about 50 % of the site-years. The PNFOA was able to determine N rate recommendations within 20 kg N ha^?1 of the AONR for half of the site-years; whereas, the other three algorithms were only able recommend within 20 kg N ha^?1 of the AONR for about 40 % of the site-years. Lastly, all four algorithms reported more accurate N rate recommendations compared to non-sensor based methodologies and can more precisely account for the year to year variability in grain yields due to environment.     

Management zone delineation using a modified watershed algorithm

Site-specific management (SSM) is a common way to manage within-field variability. This concept divides fields into site-specific management zones (SSMZ) according to one or several soil or crop characteristics. This paper proposes an original methodology for SSMZ delineation which is able to manage different kinds of crop and/or soil images using a powerful segmentation tool: the watershed algorithm. This image analysis algorithm was adapted to the specific constraints of precision agriculture. The algorithm was tested on high-resolution bio-physical images of a set of fields in France.     

Maximizing the relationship of yield to site-specific management zones with object-oriented segmentation of hyperspectral images

Quick and low cost delineation of site-specific management zones (SSMZ) would improve applications of precision agriculture. In this study, a new method for delineating SSMZ using object-oriented segmentation of airborne imagery was demonstrated. Three remote sensing domains—spectral, spatial, and temporal- are exploited to improve the SSMZ relationship to yield. Common vegetation indices (VI), and first and second derivatives (\(\rho^{\prime}\), \(\rho^{\prime\prime}\)) from twelve airborne hyperspectral images of a cotton field for one season \(\rho^{\prime}\) were used as input layers for object-oriented segmentation. The optimal combination of VI, SSMZ size and crop phenological stage were used as input variables for SSMZ delineation, determined by maximizing the correlation to segmented yield monitor maps. Combining narrow band vegetation indices and object-oriented segmentation provided higher correlation between VI and yield at SSMZ scale than that at pixel scale by reducing multi-resource data noise. VI performance varied during the cotton growing season, providing better SSMZ delineation at the beginning and middle of the season (days after planting (DAP) 66–143).The optimal scale determined for SSMZ delineation was approximately 240 polygons for the study field, but the method also provided flexibility enabling the setting of practical scales for a given field. For a defined scale, the optimal single phenological stage for the study field was near July 11 (DAP 87) early in the growing season. SSMZs determined from multispectral VIs at a single stage were also satisfactory; compared to hyperspectral indices, temporal resolution of multi-spectral data seems more important for SSMZ delineation.     

Developing a new Crop Circle active canopy sensor-based precision nitrogen management strategy for winter wheat in North China Plain

Active canopy sensor (ACS)—based precision nitrogen (N) management (PNM) is a promising strategy to improve crop N use efficiency (NUE). The GreenSeeker (GS) sensor with two fixed bands has been applied to improve winter wheat (Triticum aestivum L.) N management in North China Plain (NCP). The Crop Circle (CC) ACS-470 active sensor is user configurable with three wavebands. The objective of this study was to develop a CC ACS-470 sensor-based PNM strategy for winter wheat in NCP and compare it with GS sensor-based N management strategy, soil N_min test-based in-season N management strategy and conventional farmer’s practice. Four site-years of field N rate experiments were conducted from 2009 to 2013 to identify optimum CC vegetation indices for estimating early season winter wheat plant N uptake (PNU) and grain yield in Quzhou Experiment Station of China Agricultural University located in Hebei province of NCP. Another nine on-farm experiments were conducted at three different villages in Quzhou County in 2012/2013 to evaluate the performance of the developed N management strategy. The results indicated that the CC ACS-470 sensor could significantly improve estimation of early season PNU (R² = 0.78) and grain yield (R² = 0.62) of winter wheat over GS sensor (R² = 0.60 and 0.33, respectively). All three in-season N management strategies achieved similar grain yield as compared with farmer’s practice. The three PNM strategies all significantly reduced N application rates and increased N partial factor productivity (PFP) by an average of 61–67 %. It is concluded that the CC sensor can improve estimation of early season winter wheat PNU and grain yield as compared to the GS sensor, but the PNM strategies based on these two sensors perform equally well for improving winter wheat NUE in NCP. More studies are needed to further develop and evaluate these active sensor-based PNM strategies under more diverse on-farm conditions.     

Active remote sensing and grain yield in irrigated maize

Advances in agricultural technology have led to the development of active remote sensing equipment that can potentially optimize N fertilizer inputs. The objective of this study was to evaluate a hand-held active remote sensing instrument to estimate yield potential in irrigated maize. This study was done over two consecutive years on two irrigated maize fields in eastern Colorado. At the six- to eight-leaf crop growth stage, the GreenSeeker? active remote sensing unit was used to measure red and NIR reflectance of the crop canopy. Soil samples were taken before side-dressing from the plots at the time of sensing to determine nitrate concentration. Normalized difference vegetation index (NDVI) was calculated from the reflectance data and then divided by the number of days from planting to sensing, where growing degrees were greater than zero. An NDVI-ratio was calculated as the ratio of the reflectance of an area of interest to that of an N-rich portion of the field. Regression analysis was used to model grain yield. Grain yields ranged from 5 to 24 Mg ha^?1. The coefficient of determination ranged from 0.10 to 0.76. The data for both fields in year 1 were modeled and cross-validated using data from both fields for year 2. The coefficient of determination of the best fitting model for year 1 was 0.54. The NDVI-ratio had a significant relationship with observed grain yield (r ² = 0.65). This study shows that the GreenSeeker? active sensor has the potential to estimate grain yield in irrigated maize; however, improvements need to be made.     

Development of an in-season estimate of yield potential utilizing optical crop sensors and soil moisture data for winter wheat

When utilizing optical sensors to make in-season agronomic recommendations in winter wheat, one parameter often required is the in-season grain yield potential at the time of sensing. Current estimates use an estimate of biomass, such as normalized difference vegetation index (NDVI), and growing degree days (GDDs) from planting to NDVI data collection. The objective of this study was to incorporate soil moisture data to improve the ability to predict final grain yield in-season. Crop NDVI, GDDs that were adjusted based upon if there was adequate water for crop growth, and the amount of soil profile (0–0.80 m) water were incorporated into a multiple linear regression model to predict final grain yield. Twenty-two site-years of N fertility trials with in-season grain yield predictions for growth stages ranging from Feekes 3 to 10 were utilized to calibrate the model. Three models were developed: one for all soil types, one for loamy soil textured sites, and one for coarse soil textured sites. The models were validated with 11 independent site-years of NDVI and weather data. The results indicated there was no added benefit to having separate models based upon soil types. Typically, the models that included soil moisture, more accurately predicted final grain yield. Across all site years and growth stages, yield prediction estimates that included soil moisture had an R² = 0.49, while the current model without a soil moisture adjustment had an R² = 0.40.     

不同基础地力土壤优化施肥对水稻产量和氮肥利用率的影响

【目的】研究江汉平原地区不同基础地力土壤和优化施肥对水稻产量和氮肥利用率的影响。【方法】以江汉平原水稻主推品种丰两优香一号为试验材料,通过3年田间小区试验,考察分析土壤基础地力不同的稻田优化施肥、农民习惯施肥和不施肥处理的产量、氮肥贡献率、土壤氮素依存率和氮肥利用率等的差异。【结果】土壤基础地力不同的稻田均是优化施肥处理的产量最高,与农民习惯施肥处理比较,高地力和低地力稻田优化施肥处理的产量分别平均提高6.9%和5.0%;与不施肥处理比较,产量分别平均提高17.3%和30.3%。与农民习惯施肥处理比较,优化施肥处理的氮肥吸收利用率、农学利用率和偏生产力均大幅度提高。高地力稻田土壤氮素依存率高、氮肥贡献率小、施肥增产的潜力小;低地力稻田土壤氮素依存率低、氮肥贡献率大、施肥增产的潜力大。【结论】优化施肥可以降低水稻产量对土壤基础地力的依赖,提高氮肥利用率。     

早稻、大豆、油菜三熟制栽培施肥效应研究

通过一年三熟制栽培的田间定位施肥试验 ,探讨水稻、大豆、油菜对不同施肥的反应及土壤养分的变化。试验结果表明 ,在低丘马肝泥水稻田三熟条件下每季施N 75kg/hm2 ,P2 O53 7.5kg/hm2 ,K2 O 75kg/hm2 ,稻、豆、油全年增产效果显著 ,增产 3 65 2 .5kg/hm2 ;不同作物施肥的增产效果是油菜 >水稻 >大豆 ;几种施肥处理的单位面积油分、蛋白质产量增加 ,尤其是NPK、NP、P区的油菜蛋白质及油分产量较CK增加 2 .8～ 3 .7倍 ;连年定位施肥对大豆、油菜成熟期植株体养分含量的影响较大 ,不同的施肥处理和作物不同的器官均不相同 ;经 4年施肥后的不同施肥区的土壤全N、P、K含量变化不明显 ,而速效态养分则随不同肥料处理有较大变化。     

Identifying important factors influencing corn yield and grain quality variability using artificial neural networks

Soil, landscape and hybrid factors are known to influence yield and quality of corn (Zea mays L.). This study employed artificial neural network (ANN) analysis to evaluate the relative importance of selected soil, landscape and seed hybrid factors on yield and grain quality in two Illinois, USA fields. About 7 to 13 important factors were identified that could explain from 61% to 99% of the observed yield or quality variability in the study site-years. Hybrid was found to be the most important factor overall for quality in both fields, and for yield as well in Field 1. The relative importance of soil and landscape factors for corn yield and quality and their relationships differed by hybrid and field. Cation exchange capacity (CEC) and relative elevation were consistently identified as among the top four most important soil and landscape factors for both corn yield and quality in both fields in 2000. Aspect and Zn were among the top five most important factors in Fields 1 and 2, respectively. Compound topographic index (CTI), profile curvature and tangential curvature were, in general, not important in the study site-years. The response curves generated by the ANN models were more informative than simple correlation coefficients or coefficients in multiple regression equations. We conclude that hybrid was more important than soil and landscape factors for consideration in precision crop management, especially when grain quality was a management objective.     

Topdressing nitrogen recommendation for early rice with an active sensor in south China

Fertilizing based on soil test and crop nitrogen (N) demand is the key to optimize yields and minimize fertilizer cost. In 2008, a field experiment with different N rates was conducted with early rice near Yingtan City, Jiangxi Province, in southern China. Canopy normalized difference vegetation index (NDVI) with an active sensor and plant N uptake (PNU) were collected at key fertilization stages; and the sufficiency index (SI) was calculated as the ratio of under-fertilized and well-fertilized NDVI. Rice PNU and yield were positively correlated with NDVI and SI at the tillering and panicle initiation stages. Canopy SI improved the PNU and yield estimations when the relationship was validated with a different dataset. A spectrally-determined N topdressing model (SDNT) was established and used in combination with a target yield strategy and split-fertilization scheme. An allocation coefficient for plant N requirement to accommodate the potential for high yield and soil N supply was introduced. Optimum nitrogen use efficiency (NUE) at different growth stages was incorporated into the model. The model was validated with data from a 2009 plot experiment and three production fields in 2010. The difference of recommended N rate and yield between SDNT and the current yield curve recommendation method was 2.1 and ?0.7 % at high planting density and ?2.4 and ?4.8 % at low planting density, respectively. Compared with farmers’ N management, the SDNT strategy resulted in similar or higher yield with reduced N rates, higher NUE and higher net profit in both 2009 and 2010. Because canopy NDVI can be obtained while sidedressing N fertilizer in a single field pass, the potential of SDNT to accommodate within-field spatial and temporal variability in N availability should improve N management in rice.     

秸秆还田与水分管理对双季水稻氮素吸收及氮肥?利用率的影响

秸秆还田是促进农田养分循环的重要方式,也对提升农田地力有较好效果。以南方典型双季稻田为研究对象,设置三个秸秆还田水平和两种水分管理方式的两因子田间定位试验,于定位试验开展后的第5年通过测定早稻和晚稻季稻田土壤无机氮、微生物生物量氮动态、植株吸氮量动态以及收获期主要土壤肥力因子、水稻产量和植株各部分氮素累积量,分析秸秆还田与水分管理制度下水稻氮素吸收和氮肥利用率的特征及其影响因素。结果表明:秸秆还田提高了土壤有机碳和全氮含量以及土壤p H,长期淹水较之间歇灌溉降低了土壤有机碳、全氮和全磷含量。在氮肥用量一致条件下,早稻季秸秆还田降低了分蘖期土壤氮素有效性,导致水稻生育期内氮素吸收量显著下降,且显著降低水稻籽粒产量及氮肥利用率;氮肥利用率较对照下降2.0~7.6个百分点,且随秸秆还田量的增加而降低。晚稻季秸秆还田提高了生育期内土壤氮素有效性,显著提高了水稻生育期内氮素吸收量,增加水稻产量且显著提高氮肥利用率;氮肥利用率较对照提高8.6~13个百分点,且随秸秆还田量的增加而增加。研究表明,间歇灌溉和长期淹水灌溉两种水分管理方式对水稻氮素吸收、籽粒产量及氮肥利用率的影响差异不显著。早稻季秸秆还田配合长期淹水灌溉将加剧水稻产量和氮肥利用率下降。双季稻稻田实行间歇灌溉下的早稻季秸秆不还田、晚稻季秸秆全量还田(6 t/hm2)有利于获得较高水稻产量和氮肥利用率。     

Comparison of QuickBird Satellite Imagery and Airborne Imagery for Mapping Grain Sorghum Yield Patterns

Timely and accurate information on crop conditions obtained during the growing season is of vital importance for crop management. High spatial resolution satellite imagery has the potential for mapping crop growth variability and identifying problem areas within fields. The objectives of this study were to use QuickBird satellite imagery for mapping plant growth and yield patterns within grain sorghum fields as compared with airborne multispectral image data. A QuickBird 2.8-m four-band image covering a cropping area in south Texas, USA was acquired in the 2003 growing season. Airborne three-band imagery with submeter resolution was also collected from two grain sorghum fields within the satellite scene. Yield monitor data collected from the two fields were resampled to match the resolutions of the airborne imagery and the satellite imagery. The airborne imagery was related to yield at original submeter, 2.8 and 8.4 m resolutions and the QuickBird imagery was related to yield at 2.8 and 8.4 m resolutions. The extracted QuickBird images for the two fields were then classified into multiple zones using unsupervised classification and mean yields among the zones were compared. Results showed that grain yield was significantly related to both types of image data and that the QuickBird imagery had similar correlations with grain yield as compared with the airborne imagery at the 2.8 and 8.4 m resolutions. Moreover, the unsupervised classification maps effectively differentiated grain production levels among the zones. These results indicate that high spatial resolution satellite imagery can be a useful data source for determining plant growth and yield patterns for within-field crop management.     

Within and between-field spatial variation in soil phosphorus in permanent grassland

Soil phosphorus (P) concentrations above certain critical thresholds are a problem in many areas leading to its transport into surface and ground waters. Site-specific nutrient applications and the development of nutrient management plans for farms would help to optimize nutrient applications, meet crop requirements and take into consideration current soil nutrient status. In Northern Ireland, high concentrations of soil P are common, whereas low concentrations of soil potassium (K) and sulphur (S) have been reported in many silage fields. This study used grid and transect soil sampling to measure within- and between-field spatial variation in soil Olsen-P status across a 50-ha permanent grassland site used for silage production. Soil phosphorus indices ranged from Index 1 to Index 4 within single fields. The spatial patterns of soil P across fields suggested that there was scope for site-specific P fertilizer applications, with variable quantities of P being applied to different fields and within individual fields. Site-specific nutrient management has the potential to reduce excess P applications in some areas and avoid deficiencies in others, thereby minimizing environmental problems and optimizing yield.     

长期施用氮磷肥对旱地冬小麦籽粒产量和锌含量的影响

【目的】小麦是中国北方地区的主要粮食作物,主要种植在低锌的石灰性土壤上,其籽粒锌含量普遍偏低,因此小麦籽粒锌营养强化是近年研究的热点。小麦氮磷与锌的吸收利用存在互作效应。利用从2004年起在中国西北旱地潜在缺锌的石灰性土壤上开展的长期定位试验,研究长期氮磷施用下的小麦产量与锌含量的变化。【方法】田间试验采用完全随机区组设计,设不施肥(CK)、单施氮肥(N160,施160 kg N·hm~(-2))、单施磷肥(P100,施100 kg P2O5·hm~(-2))和氮磷配施(N160P100,施160 kg N·hm~(-2)、100 kg P2O5·hm~(-2))4个处理。于2012—2016年连续4年进行田间取样,分析小麦的生物量、产量、产量构成,及锌含量与锌吸收和分配。【结果】与不施肥相比,长期单施氮肥使小麦穗数降低9%,籽粒产量和地上部生物量均降低12%,而籽粒锌含量由不施肥处理的29.4 mg·kg-1提高到42.8 mg·kg-1,提高幅度为46%,籽粒和地上部的锌吸收量分别增加29%和37%,地上部的氮锌比和磷锌比分别降低13%和45%;长期单施磷肥使小麦穗数、籽粒产量和地上部生物量分别增加18%、15%和16%,籽粒锌含量、籽粒和地上部的锌吸收量却分别降低31%、19%和17%,同时地上部的氮锌比和磷锌比分别提高19%和83%;氮磷配施的小麦穗数、籽粒产量和地上部生物量也显著增加,增加幅度分别为40%、46%和38%,籽粒和地上部的锌吸收量还分别提高36%和34%,但籽粒的锌含量仅降低8%,同时地上部的氮锌比和磷锌比分别提高43%和27%。与单施磷肥相比,氮磷配施不仅提高了籽粒产量,还提高了籽粒锌含量,主要原因是施用氮肥能够增加小麦锌吸收,减缓了磷肥对小麦锌吸收的抑制作用。【结论】在生产实践中,单施氮肥虽可以提高小麦籽粒的锌含量,达到食物锌营养强化的目的,但长期单施氮肥会导致土壤养分不平衡,不利于维持和提高小麦产量。长期单施磷肥虽能够提高小麦籽粒产量,但抑制小麦锌吸收,不利于籽粒锌累积,降低籽粒含量。因此,在黄土高原旱地石灰性土壤上,建议合理进行氮磷配施,以保证小麦生产高产优质。     

Management Zones Classified With Respect to Drought and Waterlogging

Within-field variations in potential grain yield may be due to variations in plant available soil water. Different water holding capacities affect yield differently in different years depending on weather. By estimating plant-water availability in different weathers, scenarios could be created of how yield potential and thereby fertilizer demand may vary within fields. To test this, measured cereal grain yields from a dry, a wet and an intermediate year were compared with different soil moisture related variables in a Swedish arable field consisting of clayey and sandy areas. Soil water budget calculations based on weather data and maximum plant available water (PAW), estimated from soil type and rooting data, were used to assess drought. A reasonable correlation between estimated and measured soil moisture was achieved. In the dry year, drought days explained differences in yield between the clayey and the sandy soil, but yield was better explained directly by maximum PAW, elevation, clay content and soil electrical conductivity (SEC). Yield correlated significantly with SEC and elevation within the sandy soil in the dry year and within the clayey soil in the wet year, probably due to water and nitrogen limitation respectively. Dense SEC, elevation and yield data were therefore used to divide the field into management zones representing different risk levels for drought and waterlogging. These could be used as a decision support tool for site-specific N fertilization, since both drought and waterlogging affect N fertilization demand.     

Effect of Nitrogen Regimes on Grain Yield,Nitrogen Utilization,Radiation Use Efficiency,and Sheath Blight Disease Intensity in Super Hybrid Rice

Poor nitrogen use efficiency in rice production is a critical issue in China. Site-specific N managements (SSNM) such as real-time N management (RTNM) and fixed-time adjustable-dose N management (FTNM) improve fertilizer-N use efficiency of irrigated rice. This study was aimed to compare the different nitrogen (N) rates and application methods (FFP, SSNM, and RTNM methods) under with- and without-fungicide application conditions on grain yield, yield components, solar radiation use efficiency (RUE), agronomic-nitrogen use efficiency (AE_N), and sheath blight disease intensity. Field experiments were carried out at Liuyang County, Hunan Province, China, during 2006 and 2007. A super hybrid rice Liangyou 293 (LY293) was used as experimental material. The results showed that RTNM and SSNM have great potential for improving agronomic-nitrogen use efficiency without sacrificing the grain yield. There were significant differences in light interception rate, sheath blight disease incidence (DI) and the disease index (ShBI), and total dry matter among the different nitrogen management methods. The radiation use efficiency was increased in a certain level of applied N. But, the harvest index (HI) decreased with the increase in applied N. There is a quadratic curve relationship between grain yield and applied N rates. With the same N fertilizer rate, different fertilizer-N application methods affected the RUE and grain yield. The fungicide application not only improved the canopy light interception rate, RUE, grain filling, and harvest index, but also reduced the degree of sheath blight disease. The treatment of RTNM under the SPAD threshold value 40 obtained the highest yield. While the treatment of SSNM led to the highest nitrogen agronomic efficiency and higher rice yield, and decreased the infestation of sheath blight disease dramatically as well. Nitrogen application regimes and diseases control in rice caused obvious effects on light interception rate, RUE, and HI. Optimal N rate is helpful to get higher light interception rate, RUE, and HI. Disease control with fungicide application decreased and delayed the negative effects of the high N on rice yield formation. SSNM and RTNM under the proper SPAD threshold value obtained highyield with high efficiency and could alleviate environmental pollution in rice production.     

黄土高原旱地冬小麦籽粒锌含量差异与主要土壤理化性状的关系

【目的】中国黄土高原旱地小麦籽粒锌含量普遍偏低,但存在较大的变异现象。揭示小麦籽粒锌含量变异的原因,从而调控作物锌营养,提高小麦籽粒锌含量。【方法】在2014—2015和2015—2016年,对地处黄土高原的山西、陕西、甘肃旱地冬小麦主产区的379个农户麦田土壤(0—100 cm土层)和小麦植株进行取样分析,研究旱地冬小麦籽粒锌含量差异及其与主要土壤理化性状的关系。【结果】该区域小麦籽粒锌含量介于12.2—50.7mg·kg~(-1)。相关分析表明,0—100 cm各土层水分含量和有效铁、多数土层的pH和有效磷、表土层的有效锰和有效铜均与小麦籽粒锌含量呈显著负相关;表层土壤(0—20 cm)硝态氮、速效钾、有效锌与籽粒锌含量呈极显著正相关;各土层土壤有机质和全氮含量、多数土层的铵态氮含量均与籽粒锌含量无显著相关关系。当籽粒锌含量达到高锌组水平(平均39.2 mg·kg~(-1))时,收获期0—100 cm土层水分含量为8.2%,比低锌组低23%;0—20 cm土层pH为8.3,比低锌组低1.4%;硝态氮、速效钾和有效锌含量分别为23、150和0.54 mg·kg~(-1),比低锌组高246%、27%和35%;有效磷、有效铁、有效锰、有效铜含量分别为12.1、3.2、10.6和1.0 mg·kg~(-1),比低锌组低21%、37%、6%和33%。【结论】黄土高原旱地田块间小麦籽粒锌含量存在较大的变异。土壤水分、pH、硝态氮、有效磷、速效钾和有效态铁锰铜锌含量是引起籽粒锌含量差异的原因,其中以水分和有效铁影响最大。优化农田水分和养分管理措施,提高土壤水分、氮、钾、锌供应能力,在不影响作物产量的情况下适当调控土壤磷、铁、锰、铜供应能力,有利于提高黄土高原地区小麦籽粒锌含量。