Spatial and Temporal Variability of Corn Grain Yield: Site-Specific Relationships of Biotic and Abiotic Factors

Inadequate information on factors affecting crop yield variability has contributed to the slow adoption of site-specific farming (SSF). This study was conducted to determine the effects of biotic and abiotic factors on the spatial and temporal variability of irrigated corn grain yields and to derive information useful for SSF. The effects of water (80% evapotranspiration (ET) and 50% ET), hybrid (drought-tolerant and -susceptible), elevation, soil index (SI)(texture), soil NO₃–N, arthropods, and diseases on corn grain yield were investigated at Halfway, TX on geo-referenced locations. Grain yields were influenced by interrelationships among biotic and abiotic factors. Grain yields were consistently high under high water treatment, at higher elevations, and on soils with high SI (high clay and silt). Soil NO₃–N increased grain yields when water was adequate. Management zones for variable rate fertilizer and water application should, therefore, be based on information on elevation, SI, and soil NO₃–N. The effects of arthropods, diseases, and crop stress (due to drought and N) on corn grain yield were unpredictable. Spider mite (Oligonychus pratensis) and common smut (Ustilago zeae) damage occurred under hot and dry conditions in 1998. Spider mite infestations were high in areas with high soil NO₃–N. Moderate air temperatures and high relative humidity in 1999 favored southwestern corn borer (Diatraea grandiosella) and common rust (Puccinia maydis) incidences. Knowledge of conditions that favor arthropods and diseases outbreak and crop stress can improve the efficiency of scouting and in-season management of SSF. Management of SSF can be improved when effects of biotic and abiotic factors on grain yield are integrated and evaluated as a system.     

Strategies for increasing the capture,storage, and utilization of precipitation in semiarid regions

Crop production in semiarid regions is always challenging because of the high variability of amount and distribution of precipitation.These regions become more important each year, however, because the rapidly increasing and more prosperous world population seeks greater consumption of animal products(meat, milk and eggs) that requires additional grain to that consumed directly.The dry areas of the developing world where approximately 40% of the world population lives comprise about 40% of the earth's land area.Crop production, particularly cereal grains, must increase in these areas to meet these growing demands.Grain yield of cereal crops is a function of the amount of water used for evapotranspiration(ET), the portion of ET used for transpiration(T), the units of water as T to produce 1 unit of biomass, and the harvest index(HI).The most important factor is the amount of evapotranspiration not only because it is closely proportional to grain yield, but because it tends to also make the other factors more favorable.Therefore, even small increases in ET can be significant.Strategies for manipulating soil and plant conditions for increasing ET, and how additional ET affects the other factors, are discussed for water deficient areas.The use of crop residues as mulch is highly beneficial but often insufficient in dryland regions or is required for animal feed and fuel.Plastic mulch, mainly restricted to China, has significantly increased grain yields in dryland areas by decreasing evaporation from the soil surface.     

氮肥和底墒对小麦同化产物累积与运转的调节效应模型

以氮肥和底墒为变量,采用最优二次D饱和设计,系统分析了氮肥与底墒对小麦生长后期同化产物累积运转过程的影响,在同化产物累积与运转方面建立了一些数学模型,结果表明,小麦籽粒产量决定于抽穗后累积同化产物的能力,随着抽穗后同化产物积累量的增加,籽位产量中来源于抽穗后光合产物的比例上升,产量构成因素也随之改善;小麦籽粒产量与调运贮藏同化产物的能力呈显着负相关,籽粒中有9%～36%来自抽穗前贮藏同化产物;通过水肥措施的应用可显着提高或改善同化产物的累积与分配比例,并提高水分和肥料的利用效率.     

A flexible approach to managing variability in grain yield and nitrate leaching at within-field to farm scales

We up-scaled the APSIM simulation model of crop growth, water and nitrogen dynamics to interpret and respond to spatial and temporal variations in soil, season and crop performance and improve yield and decrease nitrate leaching. Grain yields, drainage below the maximum root depth and nitrate leaching are strongly governed by interaction of plant available soil water storage capacity (PAWC), seasonal rainfall and nitrogen supply in the water-limited Mediterranean-type environment of Western Australia (WA). APSIM simulates the interaction of these key system parameters and the robustness of its simulations has been rigorously tested with the results of several field experiments covering a range of soil types and seasonal conditions in WA. We used yield maps, soil and weather data for farms at two locations in WA to determine spatial and temporal patterns of grain yield, drainage below the maximum root depth and nitrate leaching under a range of weather, soil and nitrogen management scenarios. On one farm, we up-scaled APSIM simulations across the whole farm using local weather and fertiliser use data and the average PAWC values of soil type polygons. On a 70 ha field on another farm, we used a linear regression of apparent soil electrical conductivity (EC_a) measured by EM38 against PAWC to transform an EC_a map of the field into a high resolution (5 m grid) PAWC map. We then used regressions of simulated yields, drainage below the maximum root depth and nitrate leaching on PAWC to upscale the APSIM simulations for a range of weather and fertiliser management scenarios. This continuous mapping approach overcame the weakness of the soil polygons approach, which assumed uniformity in soil properties and processes within soil type polygons. It identified areas at greatest financial and environmental risks across the field, which required focused management and simulated their response to management interventions. Splitting nitrogen applications increased simulated wheat yields at all sites across the field and decreased nitrate leaching particularly where the water storage capacity of the soil was small. Low water storage capacity resulted in both low wheat yields and large leaching loss. Another management option to decrease leaching may be to grow perennial vegetation that uses more water and loses less by drainage.Paper from the 5th European Conference on Precision Agriculture (5ECPA), Uppsala, Sweden, 2005     

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.     

An on-farm approach to quantify yield variation and to derive decision rules for site-specific weed management

Grain yield often varies within agricultural fields as a result of the variation in soil characteristics, competition from weeds, management practices and their causal interactions. To implement appropriate management decisions, yield variability needs to be explained and quantified. A new experimental design was established and tested in a field experiment to detect yield variation in relation to the variation in soil quality, the heterogeneity of weed distribution and weed control within a field. Weed seedling distribution and density, apparent soil electrical conductivity (EC_a) and grain yield were recorded and mapped in a 3.5 ha winter wheat field during 2005 and 2006. A linear mixed model with an anisotropic spatial correlation structure was used to estimate the effect of soil characteristics, weed competition and herbicide treatment on crop yield. The results showed that all properties had a strong effect on grain yield. By adding herbicide costs and current grain price into the model, thresholds of weed density were derived for site-specific weed control. This experimental approach enables the variation of yield within agricultural fields to be explained, and an understanding of the effects on yield of the factors that affect it and their causal interactions to be gained. The approach can be applied to improve decision algorithms for the patch spraying of weeds.     

长期施肥对绿洲农田土壤生产力及土壤硝态氮积累的影响

 在甘肃河西绿洲灌漠土上进行的长期定位试验表明，连续20年不施用任何肥料，导致农田土壤生产能力严重衰退。2001年不施肥的小麦产量仅是试验开始时（1982年）的25.7%，2000年的玉米产量为1984年的28.2%。肥料是影响农田土壤生产力的重要因素，不同肥料的影响程度依次是：氮肥＞有机肥＞磷肥＞钾肥，其平均增产率分别为36.5%、27.3%、24.7%和2.9%。随着试验年限的延长，不施任何肥料的对照产量持续降低，故氮肥的增产效果增加；磷肥增产效果比较平稳；钾肥在试验开始后最初6年（1982～1987年）无显著增产效应，中期具有一定的增产作用（1988～1992年），后期8年（1993～2001年）显著增产。施用有机肥的增产作用随着试验延续呈逐步增加的趋势，表明长期施用有机肥具有明显的残效叠加效应。不同施肥处理对土壤中NO-3-N的积累与分布有显著的影响。施用化肥的处理（NP和NPK）导致NO3--N在土壤剖面中大量积累，尤其是在20～140 cm土层。化肥与有机肥配合施用(MNP 和 MNPK) NO3--N在土壤剖面中的积累显著低于化肥处理。长期连续施用化肥和有机肥均导致土壤剖面中硝态氮的积累；与化肥相比，有机肥导致更深土壤剖面（140～180 cm）中硝态氮的积累，因此，长期有机无机肥配合施用可显著增加绿洲农田土壤生产力，维持和提高土壤质量，但从持续农业发展及保护生态环境等方面考虑，应适当降低施肥量。     

聚天门冬氨酸/盐对水稻田面水氮素变化及养分利用的影响

为探究聚天门冬氨酸/盐(PASP)对稻田氮素流失及水稻养分利用的调控作用,本研究以普通聚天门冬氨酸钙/锌盐和改性聚天门冬氨酸钙/锌盐为供试材料,在干旱棚条件下,通过水稻桶栽试验研究了PASP对水稻田面水氮浓度变化和水稻生长、氮磷钾养分吸收及土壤养分的影响。结果表明,与常规尿素对照处理相比,各聚天门冬氨酸/盐处理降低了田面水氮素浓度,尤其在施肥后第3 d和第5 d,铵态氮和硝态氮浓度显著降低了16.8%～44.7%和20.4%～42.8%。聚天门冬氨酸/盐的施用有利于水稻生长及产量提高,水稻株高、有效穗数、秸秆产量和籽粒产量以及氮、磷、钾养分吸收量均表现出增加趋势,其中改性聚天门冬氨酸钙盐处理显著增加了水稻株高(12.0%)、有效穗数(13.8%)、秸秆产量(9.26%)及籽粒氮含量(8.32%),氮肥表观利用率提高了8.4%,但差异不显著。聚天门冬氨酸/盐处理土壤氮含量也有所增加,尤其是NH4+-N含量显著增加,但土壤有效磷和速效钾含量受影响不大。综合水稻产量、养分吸收利用以及田面水氮素流失风险,改性聚天门冬氨酸/盐处理效果优于普通聚天门冬氨酸/盐,且改性聚天门冬氨酸钙盐处理最好。田间应用效果有待进一步验证。     

氮肥用量对小麦开花后根际土壤特性和产量的影响

【目的】明确小麦开花后根际土壤特性动态特征及其与产量和籽粒氮素积累量之间的关系,能够为生产上合理施肥、提高氮肥利用效率和减轻环境污染提供理论依据。【方法】2014—2015和2015—2016年在小麦季设置4个氮肥水平(0,CK;150 kg N·hm~(-2),N150;240 kg N·hm~(-2),N240和300 kg N·hm~(-2),N300)并于小麦开花期、灌浆中期和成熟期分层(0—20 cm和20—40 cm)测定小麦根际和非根际土壤铵态氮、硝态氮、蔗糖酶、脲酶,同时测定根、茎、叶和穗生物量及其氮素含量;重点分析根际土壤特性与小麦籽粒产量和氮素积累量之间的关系。【结果】(1)与CK相比,N150、N240和N300处理2年小麦籽粒产量的平均值分别增加99%、130%和107%,且处理之间差异显著。随施氮量的增加小麦根、茎、叶、穗生物量和地上部氮素积累量均呈增加趋势;氮肥回收率呈下降趋势,且处理之间差异显著。(2)从开花到成熟期,0—20 cm和20—40 cm土层小麦根际和非根际土壤铵态氮、硝态氮含量、土壤蔗糖酶和脲酶(0—20 cm除外)活性均呈下降趋势。处理CK、N150、N240和N300根际土壤铵态氮和硝态氮含量显著低于非根际土壤。4个处理2年0—20 cm根际土壤铵态氮含量平均值比非根际土壤降低29%,硝态氮含量降低22%;20—40 cm根际土壤铵态氮含量比非根际土降低34%,硝态氮含量降低14%。而根际土壤蔗糖酶和脲酶活性显著高于非根际土。4个处理2年0—20 cm根际土壤蔗糖酶活性比非根际土壤提高29%,脲酶活性提高15%;20—40 cm根际土壤蔗糖酶活性比非根际土壤提高33%,脲酶活性提高13%。(3)相关分析结果表明,小麦籽粒产量和籽粒氮素积累量均与0—20 cm和20—40 cm根际和非根际土壤无机氮(铵态氮+硝态氮)、脲酶和蔗糖酶(2016年籽粒氮素积累量除外)呈显著正相关。【结论】小麦根际土壤可利用性氮素含量小于非根际土壤,而酶活性高于非根际土;根际和非根际土壤与籽粒产量和籽粒氮素积累量呈显著正相关。根际和非根际土壤特性显著影响小麦籽粒产量。     

Soil Test,Aerial Image and Yield Data as Inputs for Site-specific Fertility and Hybrid Management Under Maize

Several potential sources of information exist to support precision management of crop inputs. This study evaluated soil test data, bare-soil remote sensing imagery and yield monitor information for their potential contributions to precision management of maize (Zea mays L.). Data were collected from five farmer-managed fields in Central New York in 1999, 2000, and 2001. Geostatistical techniques were used to analyze the spatial structure of soil fertility (pH, P, K, NO₃ and organic matter content) and yield variables (yield, hybrid response and N fertilization response), while remote sensing imagery was processed using principal component analysis. Geographic information system (GIS) spatial data processing and correlation analyses were used to evaluate relationships in the data. Organic matter content, pH, P, and K were highly consistent over time and showed high to moderate levels of spatial autocorrelation, suggesting that grid soil sampling at 2.5–5.5ha scale may be used as a basis for defining fertility management zones. Soil nitrate levels were strongly influenced by seasonal weather conditions and showed low potential for site-specific N management. Aerial image data were correlated to soil organic matter content and in some cases to yield, mainly through the effect of drainage patterns. Aerial image data were not well correlated with soil fertility indicators, and therefore were not useful for defining fertility management zones. Yield response to hybrid selection and nitrogen fertilization rates were highly variable among years, and showed little justification for site-specific management. In conclusion, we recommend grid-based management of lime, P, and K, but no justification existed within our limited study area for site-specific N or hybrid management.