Determination of Optimum Growing Degree-Days (GDD) Range Before Winter for Wheat Cultivars with Different Growth Characteristics in North China Plain

To provide base for adjusting the sowing date,achieving the yield potential of wheat cultivars with different growth characteristics,and improving the utilization rate of natural resource in the North China Plain （NCP）,a 4-yr field experiment of growing degree-days （GDD） before winter （realized through different sowing dates） with three wheat （Triticum aestivum L.） cultivars of each type of semi-winterness and weak springness was carried out at 20 test experimental sites （32°4’N36°1’N） of Henan Province in the NCP.The results showed that：（i） yield of semi-winterness wheat was significantly higher than weak springness wheat （P〈0.01）;（ii） there was a quadratic regression between the yield and GDD before winter.According to the regression equation,the optimum GDD range with high yield of semi-winterness and weak springness wheats was 750-770 and 570-590°C d,respectively;（iii） under the optimum GDD condition,the foliar age on the main stem of semi-winterness and weak springness wheats was 7.67-7.91 and 6.36-6.86 leaves,respectively,calculated by the linear regression equation between foliar age and GDD before winter;（iv） both semi-winterness and weak springness wheats were in the double ridge stage of spike differentiation under the condition of the optimum GDD range,and at this time,the foliar age on the main stem of semi-winterness and weak springness wheats was about 7.80 and 6.07 leaves,respectively,which was consistent with the results calculated by the liner regression equation.Therefore,we could consider that the sowing date is appropriate if the foliar age is about 7.8 and 6.3 leaves for semi-winterness and weak springness wheats,respectively.According to the results of this study,choosing semi-winterness wheat and planting 710 d earlier would improve yield and natural resource utilization in NCP.

Optimizing Eastern Gamagrass Forage Harvests Using Growing Degree Days

Tripsacum dactyloides (L.) L., commonly known as eastern gamagrass, is useful for grazing, stored forage, soil amelioration and conservation, and as a biofuel feedstock. Our goal was to calculate accumulated growing degree days (GDD) from existing datasets collected for eastern gamagrass forage production experiments in northwestern Oklahoma, and discuss the use of GDD, instead of calendar harvest dates, in the production of eastern gamagrass forage. Growing degree days were calculated from 1 January each year using the “optimum day method”. For 10 harvest years, the first eastern gamagrass harvest required 690 ± 26 cumulative GDD. Based on long-term weather data from Woodward, Oklahoma, this would place the first harvest on or near 1 June. The second harvest required 635 ± 27 cumulative GDD which would place the second harvest on or near 15 July and the third harvest required 690 ± 23 cumulative GDD placing it on or near 30 August. Each of the 30 harvest required an average of 670 ± 15 cumulative GDD. Using GDD to predict harvest events is a useful tool that forage producer can use in the production of eastern gamagrass forage in the USA and possibly elsewhere.

A Short Growing Season Negatively Affects Progeny Vigor in Jointed Goatgrass (<i>Aegilops cylindrica</i>)

Seed production and percent germination in jointed goatgrass were negatively affected by a shorter vernalization period in field studies conducted at Oregon State University. Our objective was to determine if a shorter growing season experienced by a maternal jointed goatgrass plant similarly affected seedling vigor in the progeny. Seed mass, percent germination, emergence, seedling height and biomass, including roots, were recorded or evaluated on progeny that were produced from three jointed goatgrass populations grown under a long or short growing season in a common garden experiment in eastern Oregon, an area where jointed goatgrass is known to commonly infest natural resources, including winter wheat. Seeds produced under a shorter growing season weighed less, were slower to germinate, and displayed lower percent germination compared with seeds produced under a long growing season. Seedlings from a short growing season were slower to emerge, and produced less shoot biomass compared to seedlings produced under a long growing season. Seedling roots and shoots were shorter when seeds were produced under a short growing season. A shorter growing season negatively affected jointed goatgrass seedling vigor. If resources for jointed goatgrass management are limited, strategies should focus on controlling plants that emerge in the fall, because they have the potential to produce more vigorous seedlings compared to plants that emerge in late winter or early spring.

Growing Season and Phenological Stages of Small Grain Crops in Response to Climate Change in Alaska

The climate change in Alaska has caused earlier spring snowmelt and the growing season expanded. However, the effect of climate change on crop phenological stages, heading (BBCH 55) and maturity (BBCH 85), is unknown. In this study, the trends of growing-season length (GSL), phenological stages of crops and climatic parameters, and the correlations between climatic parameters and the phenological stages were analyzed using the climate data and crop data over the period of 1978 to 2016. The longer GSL was found in Fairbanks (64.83˚N, 147.77˚W) and in Delta Junction (64.05˚N, 145.60˚W) but not in Palmer (61.60˚N, 149.11˚W). Sowing dates did not change significantly in three locations. The decreasing trends of heading and maturity of crops were observed but varied with location. Heading of barley and oat significantly advanced 3 and 3.1 d decade-1, respectively from 1989 to 2016 in Fairbanks while no change of heading was observed in Delta Junction and Palmer. Maturity of barley, oat and wheat significantly advanced 2.6, 3.8 and 3.9 d decade-1, respectively from 1978 to 2016 in Fairbanks (P < 0.05);maturity of oat and wheat significantly advanced 4.4 and 3.4 d decade-1 from 1978 to 2015, respectively in Delta Junction (P < 0.05). The increasing temperature trends and decreasing precipitation trends were found in Fairbanks and Delta Junction but varied with phenological stages of crops. Sowing was more important for heading than for maturity of crops. The effect of climate change on heading was less important than that on maturity. Earlier maturity of crops in Fairbanks may be attributed to increased temperatures, that in Delta Junction to both increased minimum temperature and decreased precipitation and that in Palmer to temperature and precipitation.

基于形态模型的棉花(Gossypium hirsutum L.)虚拟生长系统研究

【目的】基于棉花形态器官形成过程的定量描述,模拟棉花三维生长过程,为虚拟棉作研究提供技术基础。【方法】基于2005-2006年棉花品种、播期、氮素、水分和DPC化控试验,将系统分析方法和数学建模技术应用于棉花植株的形态建成,通过对棉花形态数据的定量分析,构建了棉花形态建成模型,主要包括:主茎叶长宽、主茎叶柄长、主茎节间长粗、果枝叶长宽、果枝叶柄长、果节长粗以及棉铃高度和直径等模型。结合OpenGL技术,在Visual C++6.0平台上实现了棉花虚拟生长系统VGSC(virtual growth system for cotton)。【结果】棉花形态模型采用Logistic方程描述各器官尺寸随GDD(生长度日,℃·d)、氮素、水分及DPC的动态变化过程,利用2006年的试验数据对模型进行检验,棉花主茎叶长宽、主茎叶柄长、主茎节间长粗、果枝叶长宽、果枝叶柄长、果节长粗以及棉铃高度和直径的观测值与模拟值的根均方差分别为0.85、0.82、0.87、0.57、0.086、0.65、0.74、0.8、0.73、0.016、0.36和0.4cm,模型预测性好。此外,以NURBS(non-uniform rational B-spline,非均匀有理B样条)曲面模拟棉花叶片及棉铃形状,以圆柱体实现茎(节)可视化表达,构建的虚拟生长系统主要包括模型库、数据库和人机界面。【结论】用户输入系统所需的相关参数值,就可较好地模拟显示棉花器官、个体和群体的三维动态生长过程。

秋季刈割对紫花苜蓿主根贮藏有机物质的影响

为了解秋季刈割对紫花苜蓿根贮有机物质在越冬期间变化情况及对翌年越冬率、头茬产量的影响,本文以‘公农1号’紫花苜蓿为试验材料,测定第二次刈割后900GDD,1000GDD,1100GDD,1200GDD刈割的紫花苜蓿在2013年秋末至2014年初春越冬期间主根中非结构性碳水化合物和含氮化合物的含量。结果表明:种植翌年,第二次刈割后1000GDD刈割的紫花苜蓿越冬率及头茬产量显著高于其他刈割处理(P<0.05),与未刈割处理间差异不显著;整个越冬期间,紫花苜蓿根贮藏性有机物质含量呈先上升后下降的趋势。综上所述,吉林省中东部地区秋季刈割具有可行性,且在第二次刈割后1000GDD时刈割不会影响牧草翌年产量。

棉花株高变化动态分析及模型研究

【目的】研究棉花品种间相对有效积温与相对株高的关系,通过相对有效积温监测,为棉花株高变化提供理论参考。【方法】采用品种试验,利用归一化和聚类分析法,设置29个新疆主栽品种,从三叶期开始,每隔7 d定点、定株测量棉花株高;当年气象数据从石河子气象局获取。【结果】不同品种间,棉花相对株高随相对有效积温的变化规律一致,建立了三大类基于相对有效积温的棉花相对株高模拟模型Y=a/(1+exp(b-cx))1d。其中,第Ⅰ类(棉花三叶期(相对株高值<0.14)至十一叶期(相对株高<0.7),株高生长速率较慢):Y=0.997/(1+exp(26.08-33.62X))1/8.66(r=0.997 6);第Ⅱ类(棉花三叶期(相对株高值在0.14~0.18)至十一叶期(相对株高在0.7~0.8),株高生长速率较快):Y=0.997/(1+exp(26.09-28.65X))1/8.41(r=0.996 7);第Ⅲ类(棉花三叶期(相对株高值>0.18)至十一叶期(相对株高>0.8),株高生长速率最快):Y=1.02/(1+exp(8.55-12.68X))1/3.25(r=0.997 3)。对模型检验结果表明,RMSE=1.699 8 cm,模拟值与观测值误差小,能反映常规条件下棉花株高的生长发育状况。【结论】Richards函数可以有效地预测棉花相对株高变化。

冬油菜适宜绿色面积指数动态设计的知识模型

在分析和提炼油菜栽培理论与技术研究资料的基础上,通过定量描述冬油菜绿色面积指数动态与品种类型、生态环境和生产技术水平之间的动态关系,运用系统工程与动态建模的方法,以基于生理发育时间的动态生长度日为主线,建立了系统化和广适性的冬油菜适宜绿色面积指数动态设计的知识模型,它包括群体叶面积指数动态和角果面积指数动态。利用不同生态点的常年逐日气象资料以及不同品种类型、不同产量目标资料对所建知识模型进行了实例分析,结果表明知识模型对不同条件下冬油菜适宜绿色面积指数的设计具有较好的可靠性和适用性。

1981—2020年沈阳地区春玉米生长季水热资源时空特征

利用沈阳地区7个气象站点逐日气象数据以及春玉米生育期数据,对1980—2020年春玉米播种期、苗期、拔节期、抽雄期、成熟期和全育期的生长度日(GDD)、高温度日(HDD)、降水量及其气候倾斜率的时空变化特征进行了分析。结果表明:春玉米全育期生长度日呈上升趋势,各生育期生长度日空间分布差异不太显著,总体上呈由北向南递增趋势,高值主要分布在浑南区和苏家屯区,低值分布在康平县和法库县。春玉米全育期高温度日呈递增趋势,除康平县在成熟期高温度日呈减少趋势,其他各地生育期高温度日均呈增加趋势,空间上由西北向东南不断递增。沈阳地区在近40 a春玉米全生育期均呈降低趋势,空间上由东南向西北呈递减趋势,在苗期各地降水均呈增加趋势,其他时期均以减少趋势为主。沈阳地区春玉米全育期热量资源呈增加趋势,但降水量呈减少趋势,此种趋势增大了该地区极端高温和气象干旱风险。

小麦越冬前阶段发育与热效应、形态建成的关系

本研究应用小麦越冬前生长阶段发育估测算法（Haunstages），从阶段发育与叶片数量、生长度日及叶热间距3个方面解析了不同处理下阶段发育与有效积温和形态建成的关系。结果表明，在所有的处理中，Haunstage0～Haun stage2．5主茎叶片数量、生长度日和叶热间距差异性不大。Haunstage 2．5之后，陇鉴301和宁麦5号主茎生长度日和叶热间距总体上表现为高密度小、叶片较多；低密度大、相应叶片少。低密度下随着施肥水平的提高，生长度日和叶热间距增大，高密度中等肥料配比水平能够增大主茎生长度日和叶热间距，当生长阶段达到Haunstage3．5时，陇鉴301和宁麦5号生长度日和叶热间距达到整个越冬前的最大值，1R17恰好相反。

Spatio-temporal reconstruction of air temperature maps and their application to estimate rice growing season heat accumulation using multi-temporal MODIS data

The accumulation of thermal time usually represents the local heat resources to drive crop growth.Maps of temperature-based agro-meteorological indices are commonly generated by the spatial interpolation of data collected from meteorological stations with coarse geographic continuity.To solve the critical problems of estimating air temperature(T a) and filling in missing pixels due to cloudy and low-quality images in growing degree days(GDDs) calculation from remotely sensed data,a novel spatio-temporal algorithm for T a estimation from Terra and Aqua moderate resolution imaging spectroradiometer(MODIS) data was proposed.This is a preliminary study to calculate heat accumulation,expressed in accumulative growing degree days(AGDDs) above 10 ℃,from reconstructed T a based on MODIS land surface temperature(LST) data.The verification results of maximum T a,minimum T a,GDD,and AGDD from MODIS-derived data to meteorological calculation were all satisfied with high correlations over 0.01 significant levels.Overall,MODIS-derived AGDD was slightly underestimated with almost 10% relative error.However,the feasibility of employing AGDD anomaly maps to characterize the 2001-2010 spatio-temporal variability of heat accumulation and estimating the 2011 heat accumulation distribution using only MODIS data was finally demonstrated in the current paper.Our study may supply a novel way to calculate AGDD in heat-related study concerning crop growth monitoring,agricultural climatic regionalization,and agro-meteorological disaster detection at the regional scale.

Climate change and finger millet: Perception, trend and impact on yield in different ecological regions in Central Nepal

The views of local people on climate change along different ecological regions are relatively unexplored in Nepal. This study was conducted in 13 villages in central Nepal at different altitudes to document the views of small holder farmers and compare their perception with trends of climatic variables, finger millet yield, natural disasters, plant phenology(flowering and fruiting), status of forest and wild life, as well as the spread of diseases and pests. Analysis on the climatic data of stations for 36-41 years between 1975 and 2016 showed significant increases in the minimum temperature in lower tropical climatic region(<500 m), upper tropical to subtropical climatic region(500-2000 m) and temperate climatic region(2000-3000 m) by 0.01, 0.026 and 0.054℃/year, respectively, and an increase of maximum temperature by 0.008, 0.018, and 0.019℃/year, respectively. Rainfall showed a strongly significant decreasing trend in all elevation regions. This result matches with the views of respondents except 38% respondent from temperate climatic region. People from the temperate climatic region also mentioned that current onset of snowfall is delayed but amount of snowfall remained the same. From the documented records, except events of wild fire, frequency of natural disasters events have increased in the recent years, which was in harmony with the views of local people. Multi-linear regression analysis showed that contribution of climatic variables on finger millet yield in lower tropical climatic region and upper tropical to subtropical regions was 23% and 57.3%, respectively, which was supported by increasing trend on average growing degree day(GDD) temperature at the rate of 0.01℃ in upper tropical to subtropical region and 0.007℃ in lower tropical climatic region yearly. Finger millet yield has been increasing at the rate of 7.39 and 36.9 kg/ha yearly in lower tropical climatic region and upper tropical to subtropical climatic region, respectively. This result provides deeper understanding of people's perception of causes and effects of climate change on diverse variables along different elevation and related magnitude which can contribute to policy making in Nepal.

日本血吸虫在钉螺体内发育成熟积温的初步研究

目的 了解现场环境中日本血吸虫在中间宿主—钉螺体内发育成熟的积温。方法 采用人工感染后放回现场环境饲养定期逸蚴的方法 ,连续记录现场温度 ,计算钉螺逸出尾蚴的积温。结果 长江流域 4省 5地 6 6 8只钉螺经 1∶2 0毛蚴感染后 ,共逸得感染性钉螺 15 5只 ,感染率为 2 3 .2 0 % ,逸出尾蚴的最低积温为 1489.43日度 ,最高积温为 2 96 0 .38日度 ,平均积温为 1793 .93± 2 32 .45日度 ;其中日本血吸虫在江滩型、水网型、山丘型环境钉螺体内发育成熟的平均积温分别为 176 3.0 1± 2 0 3 .5 1日度、192 9.49± 30 6 .38日度和 1734.19± 10 3 .39日度。结论 日本血吸虫在长江流域钉螺体积温达到 1489.

Deduction of a meteorological phenology indicator from reconstructed MODIS LST imagery

Phenology is a valuable attribute of vegetation to assess the biological impacts from climate change.A challenge of phenological research is to obtain information on both high temporal resolution and fine spatial scale observations.Here,we constructed an air temperature map based on temporal merging and spatial interpolation algorithms to overcome the cloud-related problem from the MODIS LST product.Then,we derived the accumulated growing degree days(AGDD)from the constructed mean air temperature map to use as a meteorological indicator.Further,we verified the indicator with the seasonal mean air temperature and the green-up date of a Quercus mongolica forest determined from the field-based measurements.The AGDD threshold for each Q.mongolica forest when the first leaf has unfolded was detected from the EXG trajectory extracted from digital camera images.A comparison between meteorological and MODIS-derived AGDD showed good agreement between them.There was also high consistency between DoYs extracted from AGDD and EVI based on curvature K for Q.mongolica forests of 30 sampling sites throughout South Korea.The results prove that microclimatic factors such as elevation,waterbody,and land-use intensity were faithfully reflected in the reconstructed images.Therefore,the results of this study could be applied effectively in areas where microclimatic variation is very severe and for monitoring phenology of undergrowth,which is difficult to detect from reflectance imaging.

Impact of temperature on yield and related traits in cotton genotypes

Cotton growth and development is influenced by various uncontrollable environmental conditions. Temperature variations in the field can be created by planting at different dates. The objective of the present study was to evaluate the effect of planting dates and thermal temperatures（growing degree days） on yield of 4 cotton genotypes, viz., CIM-598, CIM-599, CIM-602 and Ali Akbar-703. Plants were subjected to 6 planting dates during 2013 and 2014 in a trial conducted in randomized complete block design with four replications. For boll number, boll weight and seed cotton yield, cotton genotypes exhibited significant differences, CIM-599 produced the highest seed cotton yield of 2 062 kg ha^（–1） on account of maximum boll number and boll weight. The highest seed cotton yield was recorded in planting dates from 15 th April to 1st May whereas early and delayed planting reduced the yield due to less accumulation of heat units. Regression analysis revealed that increase of one unit（15 days） from early to optimum date（15th March to 15 th April） increased yield by 93.58 kg ha^–1. Delay in planting also decreased the seed cotton yield with the same ratio. Thus it is concluded that cotton must be sown from 15 th April to 1st May to have good productivity in this kind of environment.

A New Scheme for Predicting Leaf Onset in Summer-Green Vegetation in the Northern Hemisphere

A modified thermal time model(MTM) was developed to reproduce the leaf onset for summer-green vegetation in the Northern Hemisphere. The model adopts the basic concept of a thermal time model(TM) in that leaf onset is primarily triggered by growing degree days(GDD). Based on global phenology data derived from satellite observations, a new parameterization for the critical model parameter Tb(i.e., baseline temperature for GDD calculation) has been introduced, and the spatial distribution of Tb was calculated. Simulations of leaf onset during 1982–2000 in the range 30–90°N showed a significant improvement of MTM over the standard TM model with constant Tb. The mean error and mean absolute error of the climatological simulation were 1.11 and 6.8 days, respectively, and 90% of the model error(5th and 95 th percentiles) was between-12.4 and 13.7 days.

Alpine tundra species phenology is mostly driven by climate-related variables rather than by photoperiod

The study of plant phenology has frequently been used to link phenological events to various factors,such as temperature or photoperiod.In the high-alpine environment,proper timing of the phenological cycle has always been crucial to overcome harsh conditions and potential extreme events(i.e.spring frosts)but little is known about the response dynamics of the vegetation,which could shape the alpine landscape in a future of changing climate.Alpine tundra vegetation is composed by an array of species belonging to different phytosociological optima and with various survival strategies,and snowbed communities are a relevant expression of such an extreme-climate adapted flora.We set eight permanent plots with each one in a snowbed located on the Cimalegna plateau in Northwestern Italy and then we selected 10 most recurring species among our plots,all typical of the alpine tundra environment and classified in 3different pools:snowbed specialists,grassland species and rocky debris species.For 3 years we registered the phenophases of each species during the whole growing season using an adaptation of the BBCH scale.We later focused on the three most biologically relevant phenophases,i.e.,flower buds visible,full flowering,and beginning of seed dispersion.Three important season-related variables were chosen to investigate their relationship with the phenological cycle of the studied species:(i)the Day Of Year(DOY),the progressive number of days starting from the 1 st of January,used as a proxy of photoperiod,(ii)Days From Snow Melt(DFSM),selected to include the relevance of the snow dynamics,and(iii)Growing Degree Days(GDD),computed as a thermal sum.Our analysis highlighted that phenological development correlated better with DFSM and GDD than with DOY.Indeed,models showed that DOY was always a worse predictor since it failed to overcome interannual variations,while DFSM and marginally GDD were better suited to predict the phenological development of most of the species,despite differences intemperature and snowmelt date among the three years.Even if the response pattern to the three variables was mainly consistent for all the species,the timing of their phenological response was different.Indeed,species such as Salix herbacea and Ranunculus glacialis were always earlier in the achievement of the phenophases,while Agrostis rupestris and Euphrasia minima developed later and the remaining species showed an intermediate behavior.However,we did not detect significant differences among the three functional pools of species.

Improving Quantitative and Qualitative Characteristics of Wheat (Triticum aestivum L.) through Nitrogen Application under Semiarid Conditions

Nitrogen(N),the building block of plant proteins and enzymes,is an essential macronutrient for plant functions.A field experiment was conducted to investigate the impact of different N application rates(28,57,85,114,142,171,and 200 kg ha^(−1))on the performance of spring wheat(cv.Ujala-2016)during the 2017–2018 and 2018–2019 growing seasons.A control without N application was kept for comparison.Two years mean data showed optimum seed yield(5,461.3 kg ha^(−1))for N-application at 142 kg ha^(−1) whereas application of lower and higher rates of N did not result in significant and economically higher seed yield.A higher seed yield was obtained in the 2017–2018(5,595 kg ha^(−1))than in the 2018–2019(5,328 kg ha^(−1))growing seasons under an N application of 142 kg ha^(−1).It was attributed to the greater number of growing degree days in the first(1,942.35°C days)than in the second year(1,813.75°C).Higher rates of N(171 and 200 kg ha^(−1))than 142 kg ha^(−1) produced more number of tillers(i.e.,948,300 and 666,650 ha^(−1),respectively).However,this increase did not contribute in achieving higher yields.Application of 142,171,and 200 kg ha^(−1) resulted in 14.15%,15.0%and 15.35%grain protein concentrations in comparison to 13.15%with the application of 114 kg ha^(−1).It is concluded that the application of N at 142 kg ha^(−1) could be beneficial for attaining higher grain yields and protein concentrations of wheat cultivar Ujala-2016.

Quantifying and Validating Soybean Seed Emergence Model as a Function of Temperature

Developing a model for soybean seed emergence offers a tool producers could use for planting date options and in predicting seedling emergence. In this study, temperature effects on soybean seed emergence were quantified, modeled, and validated. The data for seed emergence model development was generated at varying temperatures, 20&deg;C/12&deg;C, 25&deg;C/17&deg;C, 30&deg;C/22&deg;C, 35&deg;C/27&deg;C, and 40&deg;C/32&deg;C, on two soybean cultivars, Asgrow AG5332 and Progeny P 5333 RY. Time for 50% emergence (t50%) was recorded, and seed emergence rate (SER) was estimated as reciprocal to time at each temperature in both the cultivars. No differences were observed between the cultivars in their response to temperature. A quadratic model (QM) best described the relationship between t50% and SGR and temperature (R2 = 0.93). Two sets of experiments were conducted to validate the model. In Experiment 1, 17 time-series planting date studies with the same cultivars were used by utilizing diurnal and seasonal changes in temperature conditions. In the second experiment, sunlit growth chambers with 3 different day/night temperatures, low—20&deg;C/12&deg;C, optimum—30&deg;C/22&deg;C, and high—40&deg;C/32&deg;C, and 64 soybean cultivars belonging MG III, IV, and V, were used. Air temperature and t50 were recorded, and SGR was estimated in all experiments. No differences were recorded among the cultivars for t50% and SGR, but differences were observed among seeding date and temperature experiments. We tested QM and traditionally used Growing Degree Days models against the data collected in validation experiments. Both the model simulations predictions agreed closely with the observed data. Based on model statistics, R2, root mean square errors (RMSE), and comparison of observations and predictions to assess model performance, the QM model performed better than the GDD model for soybean seed emergence under a wide range of cultivars and environmental conditions.

Regional growth model for summer maize based on a logistic model:Case study in China

The growing degree days(GDD)is an important factor for crop growth because it affects dry matter formation and crop yield.In this study,the universal logistic models were established employing GDD and the relative GDD(RGDD)as the main parameters to characterize summer maize growth indices such as plant height(H),leaf area index(LAI),and dry matter accumulation(DMA).The relationships were analyzed between the growth indices,harvest index(HI),water consumption,and yield in maize.By considering China as an example,the results showed that the logistic model performed well at simulating the changes in the summer maize growth indices in different regions and the universal model parameters were within specific ranges.Furthermore,the logistic model with RGDD as the independent variable was more suitable for modeling summer maize growth in large areas than GDD.The relationship between the maximum LAI and HI was described by a quadratic polynomial function.HI was optimal(0.53)when the maximum LAI was about 5.13.The maximum LAI,maximum H,and maximum DMA could be described by a quadratic polynomial function of water consumption during the growing season.The summer maize yield could be predicted with a binary quadratic equation using the maximum GDD and water consumption.This study confirmed that a logistic model can be used to establish a universal growth model for summer maize in large areas.Reasonable ranges of parameters were recommended for the logistic model,as well as the reasonable water consumption and each growth index value for summer maize.These results will be helpful for predicting the growth and yield of summer maize.