Inverse meta-modelling to estimate soil available water capacity at high spatial resolution across a farm

Geo-referenced information on crop production that is both spatially- and temporally-dense would be useful for management in precision agriculture (PA). Crop yield monitors provide spatially but not temporally dense information. Crop growth simulation modelling can provide temporal density, but traditionally fail on the spatial issue. The research described was motivated by the challenge of satisfying both the spatial and temporal data needs of PA. The methods presented depart from current crop modelling within PA by introducing meta-modelling in combination with inverse modelling to estimate site-specific soil properties. The soil properties are used to predict spatially- and temporally-dense crop yields. An inverse meta-model was derived from the agricultural production simulator (APSIM) using neural networks to estimate soil available water capacity (AWC) from available yield data. Maps of AWC with a resolution of 10 m were produced across a dryland grain farm in Australia. For certain years and fields, the estimates were useful for yield prediction with APSIM and multiple regression, whereas for others the results were disappointing. The estimates contain ‘implicit information’ about climate interactions with soil, crop and landscape that needs to be identified. Improvement of the meta-model with more AWC scenarios, more years of yield data, inclusion of additional variables and accounting for uncertainty are discussed. We concluded that it is worthwhile to pursue this approach as an efficient way of extracting soil physical information that exists within crop yield maps to create spatially- and temporally-dense datasets.     

Application of artificial neural networks in yield prediction of potato crop

Forecasting of crop yield is helpful in food management and growth of a nation, which has specially agriculture based economy. In the last few decades, Artificial Neural Networks have been used successfully in different fields of agricultural remote sensing especially in crop type classification and crop area estimation. The present work employed two types of Artificial Neural Networks i.e., a Generalized Regression Neural Network (GRNN) and a Radial Basis Function Neural Network (RBFNN) to predict the yield of potato crops, which have been sown differently (flat and rough). Crop parameters like leaf area index, biomass and plant height were used as input data, while the yield of potato fields as output dataset to train and test the Neural Networks. Both GRNN and RBNN predicted potato crop yield accurately. However based on quick learning capability and lower spread constant (0.5), the GRNN was found a better predictor than RBFNN. Furthermore, the rough surface field was found more productive than flat field.     

百色市主要农作物土地生产潜力研究

[目的]探讨百色市主要农作物的土地生产潜力估算方法,为提高百色市主要农作物的土地生产潜力提供参考.[方法]用农业生态区域法估算主要农作物的光温生产潜力;在光温生产潜力的基础上用水分订正系数进行修订,估算出主要农作物的气候生产潜力;在气候生产潜力基础上用土地质量系数进行修订,估算出主要农作物的土地生产潜力.[结果]百色市主要农作物光温、气候和土地生产潜力均以水稻最高,其余依次为玉米、大豆和红薯.4种作物土地生产潜力分别为：5466.0、5074.4、2414.3和1190.5 kg/ha.[结论]百色市主要农作物的土地生产潜力较低,为提高百色市主要农作物的土地生产潜力,应优化农作物品种结构,引进高产优质的农作物品种,提高土壤肥力,加强水肥管理和以农田水利为重点的农业基础设施建设等.     

A simulation model-assisted study on water and nitrogen dynamics and their effects on crop performance in the wheat-maize system I: The model

Based on data collected from field experiments, a comprehensive model was built on the Ithink (a registered trademark of iSee Systems) platform to simulate the dynamics of water and nitrogen, and crop performance in the winter wheat-summer maize double cropping system of the North China plain. The model, consisting of seven sub models, i.e. weather generator, phenology, biomass, dry matter partitioning, water balance, nitrogen balance, and nitrogen absorption and partitioning, well reflects water and nitrogen use and their relationship with crop yield under field conditions. A vertical water movement equation is employed in the water balance sub model to account for movement between layers. Crop transpiration and soil evaporation are simulated separately according to potential evaporation, crop cover and a soil water deficit coefficient. Soil evaporation is from the surface layer only while crop transpiration comprises the total amount of water absorbed by the root system from all soil layers. The model considers that nitrogen transformations, transfers and uptake are fulfilled by root systems. Transformation of nitrogen as mineralization, fixation and denitrification are responsive to soil moisture and temperature. Nitrogen movement is simulated with a convection-dispersion equation with nitrate as the soil solute. Nitrogen absorption and partitioning sub model includes the effects of water and nitrogen supply, crop nitrogen demand and nitrogen content in various crop organs. The model can be used to simulate crop yield, water-and nitrogen-use efficiencies and water-nitrogen leaching to specific soil layers in different water and nitrogen management practices.     

Modeling the biomass of energy crops:Descriptions,strengths and prospective

The assessment of the biomass of energy crops has garnered widespread interest since renewable bioenergy may become a substantial proportion of the future energy supply, and modeling has been widely used for the simulation of energy crops yields. A literature survey revealed that 23 models have been developed or adapted for simulating the biomass of energy crops, including Miscanthus, switchgrass, maize, poplar, willow, sugarcane, and Eucalyptus camaldulensis. Three categories(radiation model, water-controlled crop model, and integrated model with biochemical and photosynthesis and respiration approaches) were addressed for the selected models according to different principles or approaches used to simulate biomass production processes. EPIC, ALMANAC, APSIM, ISAM, MISCANMOD, MISCANFOR, SILVA, DAYCENT, APEX and SWAT are radiation models based on a radiation use efficiency approach(RUE) with few empirical and statistical parameters. The Aqua Crop model is a typical water-crop model that emphasizes crop water use, the expression of canopy cover, and the separation of evapotranspiration to soil evaporation and plant transpiration to drive crop growth. CANEGRO, 3PG, Crop Syst and DSSAT are integrated models that use photosynthesis and respiration approaches. SECRETS, LPJm L, Agro-BGC, Agro-IBIS, and WIMOVAC/Bio Cro, DNDC, DRAINMOD-GRASS, and Ag TEM are integrated models that use biochemical approaches. Integrated models are mainly mechanistic models or combined with functional models, which are dynamic with spatial and temporal patterns but with complex parameters and large amounts of input data. Energy crop models combined with process-based models, such as EPIC in SWAT and CANEGRO in DSSAT, provide good examples that consider the biophysical, socioeconomic, and environmental responses and address the sustainability and socioeconomic goals for energy crops. The use of models for energy crop productivity is increasing rapidly and encouraging; however, relevant databases, such as climate, land use/land cover, soil, topography, and management databases, arescarce. Model structure and design assumptions, as well as input parameters and observed data, remain a challenge for model development and validation. Thus, a comprehensive framework, which includes a high-quality field database and an uncertainty evaluation system, needs to be established for modeling the biomass of energy crops.     

Soil organic carbon dynamics and crop yield for different crop rotations in a degraded ferruginous tropical soil in a semi-arid region: a simulation approach

In recent years, simulation models have been used as a complementary tool for research and for quantifying soil carbon sequestration under widely varying conditions. This has improved the understanding and prediction of soil organic carbon (SOC) dynamics and crop yield responses to soil and climate conditions and crop management scenarios. The goal of the present study was to estimate the changes in SOC for different cropping systems in West Africa using a simulation model. A crop rotation experiment conducted in Farak?-Ba, Burkina Faso was used to evaluate the performance of the cropping system model (CSM) of the Decision Support System for Agrotechnology Transfer (DSSAT) for simulating yield of different crops. Eight crop rotations that included cotton, sorghum, peanut, maize and fallow, and three different management scenarios, one without N (control), one with chemical fertilizer (N) and one with manure applications, were studied. The CSM was able to simulate the yield trends of various crops, with inconsistencies for a few years. The simulated SOC increased slightly across the years for the sorghum-fallow rotation with manure application. However, SOC decreased for all other rotations except for the continuous fallow (native grassland), in which the SOC remained stable. The model simulated SOC for the continuous fallow system with a high degree of accuracy normalized root mean square error (RMSE)=0·001, while for the other crop rotations the simulated SOC values were generally within the standard deviation (s.d.) range of the observed data. The crop rotations that included a supplemental N-fertilizer or manure application showed an increase in the average simulated aboveground biomass for all crops. The incorporation of this biomass into the soil after harvest reduced the loss of SOC. In the present study, the observed SOC data were used for characterization of production systems with different SOC dynamics. Following careful evaluation of the CSM with observed soil organic matter (SOM) data similar to the study presented here, there are many opportunities for the application of the CSM for carbon sequestration and resource management in Sub-Saharan Africa.     

从作物轮作角度评价华南典型赤红壤农区耕地质量空间差异

为从作物轮作角度分析华南典型赤红壤农区耕地质量空间差异,针对华南典型赤红壤农区构建作物轮作系统遥感分类体系,基于空间分析、文献支持、野外实地调查、农户访谈与专家知识,建立不同作物轮作系统与耕地质量等级之间的关联关系;基于Sentinel-1与Sentinel-2时间序列遥感数据、利用决策树制图方法,开展作物轮作系统遥感制图,并在不同空间尺度分析耕地质量空间差异与规律。结果表明,作物轮作系统与耕地质量之间存在关联关系,总体而言,水田轮作系统由于化肥投入较低、对土壤干扰较小、长时间被水面覆盖,不易引起土壤酸化等耕地质量问题,耕地质量等级较高;蔬菜、果园系统由于化肥投入较高,耕地质量一般较低,具体表现为土壤酸化、土壤重金属污染等问题。研究区蔬菜轮作系统比例最高,其次为果园系统。研究区耕地质量总体一般,主要为三等地,呈现出明显的空间分异。本研究初步探明作物轮作与耕地质量的关联关系,并将作物轮作遥感制图结果应用于耕地质量空间差异研究,由于耕地质量特征较难直接通过遥感反演获取,通过监测地表作物种植情况进而反演耕地质量具有理论可行性,未来有必要深入解析作物轮作、地形地貌、气象水文等要素与耕地质量的关联关系,构建大数据驱动的耕地质量时空差异评估技术体系,支撑跨尺度耕地质量监测与评价研究。     

陕西安塞县农业地域资源优势及开发

通过对典型的黄土丘陵沟壑区——陕西省安塞县土壤状况、气候特征、农业水资源供需、作物种植种类及产量进行研究和分析,指出该县具有的地域资源优势是土地辽阔、光照充足、昼夜温差大,适宜种植且高产优质的作物较多。针对农业资源开发利用过程中面临的环境建设任务重、土壤生产力低、交通欠发达、科技发展水平落后和农业投入不足等问题,提出了资源开发利用原则、具体措施及开发过程中值得注意的若干问题。     

From statistics to grids: A two-level model to simulate crop pattern dynamics

Crop planting patterns are an important component of agricultural land systems. These patterns have been significantly changed due to the combined impacts of climatic changes and socioeconomic developments. However, the extent of these changes and their possible impacts on the environment, terrestrial landscapes and rural livelihoods are largely unknown due to the lack of spatially explicit datasets including crop planting patterns. To fill this gap, this study proposes a new method for spatializing statistical data to generate multitemporal crop planting pattern datasets. This method features a two-level model that combines a land-use simulation and a crop pattern simulation. The output of the first level is the spatial distribution of the cropland, which is then used as the input for the second level, which allocates crop censuses to individual gridded cells according to certain rules. The method was tested using data from 2000 to 2019 from Heilongjiang Province, China, and was validated using remote sensing images. The results show that this method has high accuracy for crop area spatialization. Spatial crop pattern datasets over a given time period can be important supplementary information for remote sensing and thus support a wide range of application in agricultural land systems.     

县域尺度作物产量和土壤有机碳密度时空变化及其相互关系

基于作物产量和表层(0~20 cm)土壤有机碳密度(SOCD)数据,利用GIS技术研究了县域尺度(青海乐都县)小麦产量时空变化特征及其与农田表层SOC关系。结果表明,乐都县小麦单产和SOCD在空间分布上具有显著区域特征,地形、土地利用方式等结构性因素影响SOCD和作物产量的相关关系。20世纪80年代和2000年以后,乐都县小麦单产与SOCD在空间上呈相反分布,高产区SOCD最低,低产区SOCD最高。这两个时间段,高产区小麦单产增幅仅为0.5%,SOCD增幅却达11.5%;中、低产区小麦单产均呈增加趋势,增幅分别为12.9%、18.9%,SOCD却呈降低趋势,降幅分别为24.6%、29.8%。     

Modelling impacts of precision irrigation on crop yield and in-field water management

Precision irrigation technologies are being widely promoted to resolve challenges regarding improving crop productivity under conditions of increasing water scarcity. In this paper, the development of an integrated modelling approach involving the coupling of a water application model with a biophysical crop simulation model (Aquacrop) to evaluate the in-field impacts of precision irrigation on crop yield and soil water management is described. The approach allows for a comparison between conventional irrigation management practices against a range of alternate so-called ‘precision irrigation’ strategies (including variable rate irrigation, VRI). It also provides a valuable framework to evaluate the agronomic (yield), water resource (irrigation use and water efficiency), energy (consumption, costs, footprint) and environmental (nitrate leaching, drainage) impacts under contrasting irrigation management scenarios. The approach offers scope for including feedback loops to help define appropriate irrigation management zones and refine application depths accordingly for scheduling irrigation. The methodology was applied to a case study in eastern England to demonstrate the utility of the framework and the impacts of precision irrigation in a humid climate on a high-value field crop (onions). For the case study, the simulations showed how VRI is a potentially useful approach for irrigation management even in a humid environment to save water and reduce deep percolation losses (drainage). It also helped to increase crop yield due to improved control of soil water in the root zone, especially during a dry season.     

康保县农业发展的技术途径

本文回顾了河北省康保县1949～1994年的粮食生产状况,分析了当地水土资源特点,阐明了康保县粮食生产发展的潜力。结合国家“七·五”、“八·五”攻关项目旱地农业张北试验区的研究成果,提出了康保县农业发展的途径和大幅度提高粮食产量及资源利用效率的关键技术措施。     

对浙江省浦江县作物养分限制因子的TechnoGIN分析

用TechnoGIN计算浙江省浦江县作物养分限制因子时发现,按目前农业技术水平,要实现一定的目标产量,在养分投入一致,不同土地单元同一土地利用类型养分过剩率并不相同;不同作物在同一土地单元养分过剩量也各不相同.一般经济作物比粮食作物的养分过剩率相对较大,旱作作物则相对表现养分不足.不同土地利用类型氮的淋溶和挥发量也可以通过TechnoGIN进行计算,其结果可以对环境进行评判.因此TechnoGIN不仅是计算作物养分利用的一个有效工具.它的结果对指导农业生产和进行环境保护也有一定的参考价值.     

Sensing technologies for precision specialty crop production

With the advances in electronic and information technologies, various sensing systems have been developed for specialty crop production around the world. Accurate information concerning the spatial variability within fields is very important for precision farming of specialty crops. However, this variability is affected by a variety of factors, including crop yield, soil properties and nutrients, crop nutrients, crop canopy volume and biomass, water content, and pest conditions (disease, weeds, and insects). These factors can be measured using diverse types of sensors and instruments such as field-based electronic sensors, spectroradiometers, machine vision, airborne multispectral and hyperspectral remote sensing, satellite imagery, thermal imaging, RFID, and machine olfaction system, among others. Sensing techniques for crop biomass detection, weed detection, soil properties and nutrients are most advanced and can provide the data required for site specific management. On the other hand, sensing techniques for diseases detection and characterization, as well as crop water status, are based on more complex interaction between plant and sensor, making them more difficult to implement in the field scale and more complex to interpret. This paper presents a review of these sensing technologies and discusses how they are used for precision agriculture and crop management, especially for specialty crops. Some of the challenges and considerations on the use of these sensors and technologies for specialty crop production are also discussed.     

山西省马铃薯增产途径探讨

山西是中国马铃薯主产省区之一,但单产较低,其主要原因是种薯质量差、气候干旱、土壤瘠薄、种植技术落后等。因此,只有从全面推广优质脱毒种薯入手,采用旱作农业技术,增施肥料,培肥地力,大力改善生产条件,运用科学栽培技术,加强田间管理,才能大幅度提高马铃薯单产。     

旱地马铃薯全膜双垄覆盖集雨沟播技术效益研究

在宁夏西吉县黄土丘陵缓坡地上对旱地马铃薯全膜双垄覆盖集雨沟播技术进行试验研究。结果表明：秋季和早春全膜双垄面覆盖、春季播种技术均具有明显的节水增效作用,以秋季全膜双垄沟播技术效果最为突出。该技术具有较强的纳水保墒、平抑地温的作用,能大大提高作物产量和水分利用效率;缩短作物全生育期,可有效防止早霜冻等自然灾害的侵袭;能改善土壤物理性状,培肥地力,有利于农田土壤肥力的可持续提高。     

棉花作物系数的遥感获取——以新疆石河子棉花垦区为例

作物系数是计算作物需水量和农田蒸散量必要的参数,作物系数的遥感获取对于农田生态系统的水分平衡研究具有重要意义。利用Landsat ETM 遥感影像及Penman-Montieth方程,通过计算不同生长状况下棉花的作物需水量和参考作物蒸散量,实现棉花作物系数的遥感获取;在此基础上进一步分析作物系数对反照率、气象因子和植被生长参数等的敏感性。结果表明:1)利用遥感获取作物系数的空间分布是有效可行的;2)作物系数主要受植被生长状况的影响,反照率和气象因子对作物系数的影响相对次要;3)作物系数随气温、大气压、空气湿度和风速等气象因素的增大而增大,并且这种正效应随着植被覆盖度的增大而增大;4)作物系数与作物生长状况直接相关,仅仅根据作物生长阶段确定作物系数存在不合理性。     

Mapping subsoil acidity and shallow soil across a field with information from yield maps, geophysical sensing and the grower

Management decisions, such as subsoil liming or varying fertilizer inputs to take account of soil depth and anticipated yields require knowledge of where subsoil constraints to root growth occur across the field. We used selected yield maps based on criteria derived from crop simulation, apparent soil electrical conductivity (EC_a), gamma-ray emission maps and a soil type map drawn by the grower to predict the spatial distribution of subsoil acidity and shallow soil across a field. Yield maps integrate the effects of variation in soil and climate, and it was only under specific seasonal conditions that subsoil constraints depressed yields. We used crop simulation modelling to select yield maps with a large information content on the spatial distribution of these constraints and to omit those with potentially misleading information. Yield and other spatial data layers were used alone or in combination to develop subsoil mapping options to accommodate differences in data availability, access to precision agriculture techniques and the grower’s aptitude and preference. One option used gamma-ray spectrometry and EM38 survey as a dual-sensing system to improve data interpretation. Gamma-ray spectrometry helped to overcome the inability of current EC_a-based methods to sense soil depth in highly weathered sandy soil over cemented gravel. A feature of the approaches presented here is the use of grower and agronomist knowledge, and experience to help interpret the spatial data layers and to evaluate which approach is most suitable and likely to be adopted to suit an individual.     

陕西渭北农田土壤盐碱化空间分布及影响因素

为明确陕西省渭北地区农田土壤的盐碱化空间分布和主要影响因素,为区域耕地资源合理利用和低产田改良提供理论支持,以渭河以北、渭北低山及两侧的黄土高原和台塬为研究中心,通过区域调查、田间采样及室内分析,获得渭北0~60cm土层的盐碱化数据及相对应的空间、土壤性质、地下水、作物产量数据,对土壤盐渍化程度的分布状况进行定量评价,结合GIS软件绘制不同土壤层次的盐碱化分布图,结果表明:渭北0~60cm农田土壤盐碱化主要以轻度盐土和非碱化土为主,分别占农田总面积的93.5%和95.4%,各土层盐碱量从上到下逐渐增加,40~60cm土层含盐量达2.06g/kg,含碱量达4.93g/kg。土壤含盐量和碱化度较高区域分布在临渭区、富平县和蒲城县交界区域(卤泊滩周边)及黄河、渭河、洛河交汇的大荔县部分区域(盐池洼周边),韩城市黄河沿岸区域含盐量也较高。渭北农田0~20cm土层含盐量受地下水因素的影响最为明显,贡献率为43.55%,其次为空间因素和土壤因素。20~40cm土层受土壤因素影响最为显著,贡献率达44.14%,空间、地下水、管理因素次之。40~60cm土层较20~40cm土层受土壤因素影响更为显著,贡献率为68.34%,管理、空间、地下水因素次之。     

基于LMDI模型的我国省域粮食生产变化影响因素分析

从耕地利用角度对影响粮食生产变化的因素在时间和空间上产生的影响进行科学分析;应用对数平均迪氏分解法(Logarithmic mean weigh division,LMDI)将影响1980—2010年我国省域粮食生产变化的因素分为粮食单产、复种指数、耕地面积和粮作比例;对粮食生产及其分解因素的统计指标在省级层面进行分析。结果表明:1980—2010年我国粮食产量增加22 592.3万t,粮食生产格局重心由南重北轻逐渐演变为北重南轻;4个因素中粮食单产对粮食产量变化起到最显著的促进作用,但增产作用逐年降低,并被复种指数和粮作比例所替代;耕地面积减少在一定程度上限制了我国粮食产量的持续增加;全国各省域之间粮食生产变化的分解因素效应有比较显著的空间差异,河北、湖北、新疆等14个区域的粮食单产和复种指数效应的叠加效应使得其粮食生产增加显著,而上海、浙江、福建等复种指数与粮作比例的叠加效应对粮食增产的影响最大。粮食单产效应的逐渐减小与耕地面积累积效应起负面作用表明我国粮食生产增加主要是粮食单产作用,且正逼于其上限,耕地利用中要严格保护数量,提升耕地质量。