Determining placement criteria of moisture sensors through temporal stability analysis of soil water contents for a variable rate irrigation system

Developing placement criteria for soil moisture sensors is crucial in increasing the practical functionality of a variable rate irrigation (VRI) system. In this field study, the temporal stability pattern of soil water content was compared between VRI and uniform rate irrigation (URI) treatments during growing seasons of winter wheat and summer maize to determine the placement criteria of soil water sensors. The 1.64-ha experimental site located in a highly variable alluvial flood plain was divided into four management zones according to the available water holding capacity ranging from 152 to 205 mm within the 0.6 m soil profile. In each zone, two sub-zones were created to represent VRI and URI treatments. A temporal stability analysis of soil moisture was conducted by regularly measuring soil water contents at 62 locations in the field during the growing seasons. Results showed that the VRI management changed the overall similarity of soil moisture spatial patterns when crop water consumption was provided mainly by irrigation water rather than precipitation. In each management zone, every measuring position was a time-stable location with respect to the mean soil water content. Significant linear regressions were detected between the mean clay percentile in each management zone and the clay percentile representing the mean soil water content sites, and a nearly equivalent value of fitted equation coefficient was obtained for winter wheat (1.15) and summer maize (1.19). These results demonstrated that the temporal stability of soil water content spatial patterns still existed in each management zone with the VRI management, and the clay percentile supplied a priori identification for placement of soil moisture sensors.     

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.     

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.     

Prediction of plant water status in almond and walnut trees using a continuous leaf monitoring system

Persistent drought conditions in the Central valley of California demands efficient irrigation scheduling tools such as precision or variable rate irrigation (VRI). To assist VRI scheduling, an experiment was conducted in almond and walnut orchards using a sensor system called ‘leaf monitor’, which was developed at UC Davis to detect plant water status. A Modified Crop Water Stress Index (MCWSI) was calculated to quantify plant water status using leaf temperature and environmental data collected by the leaf monitor. This technique also took into account spatio-temporal variability of plant water status. Stem water potential (SWP), which is considered a standard method for determining plant water stress (PWS), was also measured simultaneously. Relationships between measured deficit stem water potential (DSWP), which is the difference between SWP and the saturated baseline, and MCWSI were developed for both crops based on data collected during the 2013 and 2014 growing seasons. A linear relationship was found in the case of walnut crop with a coefficient of determination (r²) value of 0.67. A quadratic relationship was found in the case of almonds with a coefficient of multiple determination (R²) value of 0.75. Moreover, these results highlighted that at lower PWS of below 0.5 MPa of DSWP, almonds crops did not show any decrease in transpiration rate. However, when the stress level exceeded 0.5 MPa of DSWP, transpiration rate tended to decrease. On the other hand, walnut crop showed decrease in transpiration rate even at low PWS of below 0.5 MPa of DSWP. Temporal variability was noticed in PWS as it was found that coefficients of saturation baseline used for MCWSI method changed significantly throughout the season. MCWSI values estimated before an irrigation event was used to calculate the irrigation amount for low frequency variable rate irrigation (VRI) based on the relationship found between MCWSI and DSWP, and VRI led to an average 39% reduction in water usage as compared to the fixed 100% ET replacement irrigation method for all trees. Based on the results, leaf monitor showed potential for use as an irrigation scheduling tool.

     

Crop water stress mapping for site-specific irrigation by thermal imagery and artificial reference surfaces

Variable-rate irrigation by machines or solid set systems has become technically feasible, however mapping crop water status is necessary to match irrigation quantities to site-specific crop water demands. Remote thermal sensing can provide such maps in sufficient detail and in a timely way. In a set of aerial and ground scans at the Hula Valley, Israel, digital crop water stress maps were generated using geo-referenced high-resolution thermal imagery and artificial reference surfaces. Canopy-related pixels were separated from those of the soil by upper and lower thresholds related to air temperature, and canopy temperatures were calculated from the coldest 33% of the pixel histogram. Artificial surfaces that had been wetted provided reference temperatures for the crop water stress index (CWSI) normalized to ambient conditions. Leaf water potentials of cotton were related linearly to CWSI values with R ² = 0.816. Maps of crop stress level generated from aerial scans of cotton, process tomatoes and peanut fields corresponded well with both ground-based observations by the farm operators and irrigation history. Numeric quantification of stress levels was provided to support decisions to divide fields into sections for spatially variable irrigation scheduling.     

Can Landform Stratification Improve Our Understanding of Crop Yield Variability?

Farmers account for yield and soil variability to optimize their production under mainly economic considerations using the technology of precision farming. Therefore, understanding of the spatial variation of crop yield and crop yield development within arable fields is important for spatially variable management. Our aim was to classify landform units based on a digital elevation model, and to identify their impact on biomass development. Yield components were measured by harvesting spring barley (Hordeum vulgare, L.) in 1999, and winter rye (Secale cereale, L.) in 2000 and 2001, respectively, at 192 sampling points in a field in Saxony, Germany. The field was stratified into four landform units, i.e., shoulder, backslope, footslope and level. At each landform unit, a characteristic yield development could be observed. Spring barley grain yields were highest at the level positions with 6.7 t ha⁻¹ and approximately 0.15 t ha⁻¹ below that at shoulder and footslope positions in 1999. In 2000, winter rye harvest exhibited a reduction at backslope positions of around 0.2 t ha⁻¹ as compared to the highest yield obtained again at level positions with 11.1 t ha⁻¹. The distribution of winter rye grain yield across the different landforms was completely different in 2001 from that observed in 2000. Winter rye showed the highest yields at shoulder positions with 11.1 t ha⁻¹, followed by the level position with 0.5 t ha⁻¹ less grain yield. Different developments throughout the years were assumed to be due to soil water and meteorological conditions, as well as management history. Generally, crop yield differences of up to 0.7 t ha⁻¹ were found between landform elements with appropriate consideration of the respective seasonal weather conditions. Landform analysis proved to be helpful in explaining variation in grain yield within the field between different years.     

Automatic identification of crop and weed species with chlorophyll fluorescence induction curves

Automatic identification of crop and weed species is required for many precision farming practices. The use of chlorophyll fluorescence fingerprinting for identification of maize and barley among six weed species was tested. The plants were grown in outdoor pots and the fluorescence measurements were done in variable natural conditions. The measurement protocol consisted of 1 s of shading followed by two short pulses of strong light (photosynthetic photon flux density 1700 μmol m⁻² s⁻¹) with 0.2 s of darkness in between. Both illumination pulses caused the fluorescence yield to increase by 30–60% and to display a rapid fluorescence transient resembling transients obtained after long dark incubation. A neural network classifier, working on 17 features extracted from each fluorescence induction curve, correctly classified 86.7–96.1% of the curves as crop (maize or barley) or weed. Classification of individual species yielded a 50.2–80.8% rate of correct classifications. The best results were obtained if the training and test sets were measured on the same day, but good results were also obtained when the training and test sets were measured on different dates, and even if fluorescence induction curves measured from both leaf sides were mixed. The results indicate that fluorescence fingerprinting has potential for rapid field separation of crop and weed species.     

膜下滴灌不同灌溉定额对土壤水盐分布和春玉米产量的影响

【目的】研究膜下滴灌条件下,不同灌溉定额对土壤水盐时空分布特征、春玉米产量和水分利用效率的影响。【方法】在石羊河流域中游,通过2014-2015两年的灌溉试验,对春玉米生育期设置不同灌溉定额（4 800、4 200和3 600 m³·hm^-2）,测定0-100 cm土层内,土壤水盐时空分布特征,春玉米播种前和收获后土壤全盐量在年内和年际间的变化,春玉米产量及其构成要素。【结果】随灌水定额的增加,0-60 cm土层土壤含水率增加明显,当灌水定额从420 m³·hm^-2增加到480 m³·hm^-2时,春玉米吐丝扬花期0-60 cm土层平均含水率可保持在24.52%以上。在作物需水关键期,当灌水定额为480 m³·hm^-2时,能明显增加深层土壤的蓄水量。当灌溉定额低于360 m³·hm^-2时,灌水量严重不足,土壤水分亏缺明显。在非灌溉期,土壤盐分随水分蒸发在表层耕作土壤中积聚。垂直方向上,在0-40 cm土层发生积盐现象,80-100 cm土层发生脱盐现象。在灌溉期,在垂直方向上,随着灌溉定额的增加,土壤淋洗深度呈增加的趋势。不同灌溉定额条件下,0-20 cm土层土壤发生脱盐现象,40-100 cm土层发生积盐现象。但0-100 cm土层内,土壤全盐量盈亏量总体基本平衡。在水平方向上,土壤盐分以滴头为中心向滴灌带两侧运移,滴头间土壤水分的交汇作用将原耕层的部分盐分迁移到滴灌带的湿润锋边缘处。各处理土壤含盐量均表现为滴灌带间较滴头间增加明显。不同灌溉定额对春玉米穗长、穗行数、行粒数影响不显著,对穗粗、秃尖长、百粒重影响显著。降低灌溉定额可增加春玉米的穗粗和百粒重,但对作物增产无显著作用。【结论】膜下滴灌条件下,春玉米耗水量受灌水量影响,适度水分亏缺能提高水分利用效率（WUE）,但使春玉米产量降低4.45%-20.99%。春玉米全生育期灌水10次,灌水定额为420 m³·hm^-2,灌溉定额为4 200 m³·hm^-2的灌溉制度节水、压盐、增产效益最优。     

Regional model for nitrogen fertilization of site-specific rainfed corn in haplustolls of the central Pampas,Argentina

In semi-arid regions, soil water and nitrogen (N) are generally limiting factors for corn (Zea mays L.) production; hence, implementation of appropriate N fertilization strategies is needed. The use of precision agriculture practices based on specific site and crop properties may contribute to a better allocation of fertilizer among management zones (MZ). The aim of this study was to develop a model for diagnosis of N availability and recommendation of N fertilizer rates adjusted to MZ for dryland corn crops growing in Haplustolls. The model considered variability between MZ by including site-specific variables [soil available water content at sowing (SAW) and Available Nitrogen (soil available N-NO₃ at planting + applied N, Nd)] using spatial statistical analysis. The study was conducted in Córdoba, Argentina in Haplustolls and consisted in four field trials of N fertilizer (range 0–161 kg N ha⁻¹) in each MZ. The MZ were selected based on elevation maps analysis. Grain yields varied between MZ and increased with larger SAW and Nd at sowing. Grain responses to Nd and SAW in any MZ were not different between sites, allowing to fit a regional model whose parameters (Nd, Nd², SAW, SAW²) contributed significantly (p < 0.001) to yield prediction. Agronomical and economically optimum N rates varied among MZs. However, the spatial variability of optimum N rates among MZs within sites was not enough to recommend variable N fertilizer rates instead of a uniform rate. Variable N fertilizer rates should be recommended only if variability in SAW and soil N among MZ is greater than that found in this work.     

Use of soil nitrogen parameters and texture for spatially-variable nitrogen fertilization

Recent studies have demonstrated the potential importance of using soil texture to modify fertilizer N recommendations. The objective of this study was to determine (i) if surface clay content can be used as an auxiliary variable for estimating spatial variability of soil NO₃–N, and (ii) if this information is useful for variable rate N fertilization of non-irrigated corn [Zea mays (L.)] in south central Texas, USA across years. A 64 ha corn field with variable soil type and N fertility level was used for this study during 2004–2007. Plant and surface and sub-surface soil samples were collected at different grid points and analyzed for yield, soil N parameters and texture. A uniform rate (UR) of 120 kg N ha⁻¹ in 2004 and variable rates (VAR) of 0, 60, 120, and 180 kg N ha⁻¹ in 2005 through 2007 were applied to different sites in the field. Distinct yield variation was observed over this time period. Yield and soil surface clay content and soil N parameters were strongly spatially structured. Corn grain yield was positively related to residual NO₃–N with depth and either negatively or positively related to clay content depending on precipitation. Residual NO₃–N to 0.60 and 0.90 m depths was more related to corn yield than from shallower depths. The relationship of clay content with soil NO₃–N was weak and not temporally stable. Yield response to N rate also varied temporally. Supply of available N with depth, soil texture and growing season precipitation determined proper N management for this field.     

Impact of Residual Soil Nitrate on In-Season Nitrogen Applications to Irrigated Corn Based on Remotely Sensed Assessments of Crop Nitrogen Status

Spatial and temporal variability of soil nitrogen (N) supply together with temporal variability of plant N demand make conventional N management difficult. This study was conducted to determine the impact of residual soil nitrate-N (NO₃-N) on ground-based remote sensing management of in-season N fertilizer applications for commercial center-pivot irrigated corn (Zea mays L.) in northeast Colorado. Wedge-shaped areas were established to facilitate fertigation with the center pivot in two areas of the field that had significantly different amounts of residual soil NO₃-N in the soil profile. One in-season fertigation (48 kg N ha⁻¹) was required in the Bijou loamy sand soil with high residual NO₃-N versus three in-season fertigations totaling 102 kg N ha⁻¹ in the Valentine fine sand soil with low residual NO₃-N. The farmer applied five fertigations to the field between the wedges for a total in-season N application of 214 kg N ha⁻¹. Nitrogen input was reduced by 78% and 52%, respectively, in these two areas compared to the farmer’s traditional practice without any reductions in corn yield. The ground-based remote sensing management of in-season applied N increased N use efficiency and significantly reduced residual soil NO₃-N (0–1.5 m depth) in the loamy sand soil area. Applying fertilizer N as needed by the crop and where needed in a field may reduce N inputs compared to traditional farmer accepted practices and improve in-season N management.     

A remote irrigation monitoring and control system (RIMCS) for continuous move systems. Part B: field testing and results

Precision irrigation systems can have inherent errors that affect the accuracy of variable water application rates controllers, as well as affect the controllers’ performance when evaluated on different continuous move irrigation systems configurations. The objective of this study was to assess the performance of a remote irrigation monitoring and control system (RIMCS) installed on two separate linear move (LM) irrigation systems. The RIMCS varies water application rates by pulsing nozzles controlled by solenoids connected via relays to a single board computer (SBC) with wireless Ethernet connection to a remote server. The system also monitors irrigation system flow, pressure, position and wireless field sensor networks. The system was installed on a LM irrigation system in Prosser, Washington, USA and on a LM in the Nesson Valley of North Dakota, USA. For the LM at Prosser, four pre-defined irrigation patterns were imposed and variable rates were applied as a percentage of the nozzle base application rate. Each nozzle was pulsed across the span length and along the LM travel direction. For the LM at the Nesson Valley, a quadratic pattern was imposed pulsing banks of nozzles along the LM travel direction. Standard catch can tests were performed and the system performance was evaluated by comparing measured catch can water depths with pre-determined target values. The RIMCS accuracy was found to be in the range of the LM uniform water depth application uniformity coefficients of 88–96%. The RIMCS was successfully transferred to another LM in North Dakota as indicated by the relatively low variable rate application errors of –8.8 ± 8.1% and −0.14 ± 6.7% for the two spans.     

西南喀斯特地区轮作旱地土壤CO2通量

中国已承诺大幅降低单位GDP碳排放,农业正面临固碳减排的重任。西南喀斯特地区环境独特,旱地面积占据优势比例,土壤碳循环认识亟待加强。以贵州省开阳县玉米-油菜轮作旱地为研究对象,采用密闭箱-气相色谱法对整个轮作期土壤CO₂释放通量进行了观测研究,结果表明:(1)整个轮作期旱地均表现为CO₂的释放源。其中油菜生长季土壤CO₂通量为(178.8±104.8) mg CO₂·m^-2·h^-1,玉米生长季为(403.0±178.8) mg CO₂·m^-2·h^-1,全年平均通量为(271.1±176.4) mg CO₂·m^-2·h^-1, 高于纬度较高地区的农田以及同纬度的次生林和松林;(2)CO₂通量日变化同温度呈现显著正相关关系,季节变化与温度呈现显著指数正相关关系,并受土壤湿度的影响,基于大气温度计算得出的Q₁₀为2.02,高于同纬度松林以及低纬度的常绿阔叶林;(3)CO₂通量与土壤pH存在显著线性正相关关系,显示出土壤pH是研究区旱地土壤呼吸影响因子之一。     

基于土壤条件的边缘绿洲典型灌区灌溉需水研究

【目的】土壤性状是影响作物灌溉水生产力（IWP）与灌溉需水的关键因子。以土壤性状与作物灌溉水生产力及灌溉需水的定量关系为依据、结合区域土壤性状的空间分布,估算绿洲典型灌区作物灌溉需水及空间分布,为灌区尺度的合理用水分配及节水潜力评估提供科学依据。【方法】选择黑河中游临泽边缘绿洲平川灌区,对118个农田土壤进行取样分析,确定土壤性状的空间分布;通过不同土壤质地和肥力水平的农田玉米灌溉试验,确定土壤性状与灌溉水生产力及灌溉需水量的关系、进而依据土壤条件估算灌区尺度的灌溉需水及空间分布。【结果】平川灌区农田0-20 cm耕层土壤砂粒含量为29.4%-91.9%,平均53.6%,土壤有机质含量范围为1.37-17.7 g•kg-1,平均10.9 g•kg-1;20-100 cm土层砂粒平均含量51.3%。土壤质地为壤沙土和沙土的面积占农田总面积的50%以上;有机质含量低于10.0 g•kg-1的面积占26%,土壤持水性能弱;土壤性状在空间分布上存在高度的变异性。玉米IWP平均为1.11 kg•m-3（沙土）-2.44 kg•m-3（壤土）,与0-20 cm土层黏粉粒含量（CS1,%）、20-100 cm土层黏粉粒含量（CS2,%）、0-20 cm土层有机质含量（OM,g•kg-1）呈极显著正相关。依据土壤性状与灌溉水生产力的关系,得出平川灌区玉米灌溉水生产力平均为（2.36±0.77）kg•m-3,变动范围为0.75-3.92 kg•m-3,IWP小于2.0 kg•m-3的面积为970 hm2,占总面积的18.5%。灌区玉米生育期平均灌溉需水量为558 mm,总灌溉需水量为28.4×106 m3。【结论】土壤条件决定作物的灌溉需水与灌溉水生产力,在灌溉尺度农业水管理方面,应依据不同土壤性状的斑块单元进行地表水与地下水的合理分配与配置,并重视有利于土壤结构改善和肥力提升的施肥、耕作、灌溉等农业技术的应用。     

坡耕地不同种植模式对农田水土保持效应及土壤养分流失的影响

针对云南彝良地震灾区灾后坡耕地水土流失的现状,进行了不同种植模式的水土保持效应的研究。通过对试验小区不同种植模式下的径流小区的监测,以探明不同种植模式对农田水土和养分流失及对收获期作物粒重的影响,寻求控制和减少农田水土流失及增产的有效种植模式。结果表明,不同种植模式3次地表总径流量顺序为黄豆单作(17.0 m³·hm^-2)>马铃薯单作(15.9 m³·hm^-2)>玉米单作(13.7 m³·hm^-2)>玉米//马铃薯顺坡种植(12.6 m³·hm^-2)>玉米//黄豆(12.3 m³·hm^-2)>玉米//马铃薯(11.7 m³·hm^-2);土壤总侵蚀量顺序为马铃薯单作(930.15 kg·hm^-2)>黄豆单作(821.70 kg·hm^-2)>玉米单作(739.05 kg·hm^-2)>玉米//马铃薯顺坡种植(716.70 kg·hm^-2)>玉米//马铃薯(651.90 kg·hm^-2)>玉米//黄豆(620.10 kg·hm^-2);在地表径流量方面,最好模式玉米//马铃薯间作,比最差模式黄豆单作削减地表径流量31.2%,比马铃薯单作、玉米单作分别削减地表径流量26.4%、14.3%;在土壤侵蚀量方面,最好模式玉米//黄豆间作,比最差模式马铃薯单作削减土壤侵蚀量33.3%,比黄豆单作、玉米单作分别削减土壤侵蚀量24.5%、16.1%。在土壤养分流失方面,玉米//黄豆间作比马铃薯单作削减总氮流失30.6%;玉米//黄豆间作比马铃薯单作削减氨氮流失22.2%,并有显著差异。可见,在彝良地震灾区玉米//马铃薯和玉米//黄豆间作种植模式在减少水土养分流失方面有一定效果。     

Spatial patterns of wilting in sugar beet as an indicator for precision irrigation

Precision irrigation requires the mapping of within-field variations of water requirement. Conventional remote sensing techniques provide estimates of water status at only shallow soil depths. The ability of a water sensitive crop, sugar beet, to act as an intermediate sensor providing an integrated measure of water status throughout its rooting depth is tested here. Archive aerial photographs and satellite imagery of Eastern England show crop patterns resulting from past periglacial processes. The patterns were found to be spatially and temporally consistent. Field sampling of soil cores to 1 m depth established that the within-field wilting zones were significantly associated with coarser or shallow soils. The stress classes, determined by classification of the digitised images, were weakly correlated with total available water (Pearson correlation r = 0.588, P < 0.05). These results suggest that wilting in sugar beet can be used as an intermediate sensor for quantifying potential soil water availability within the root zone. Within-field stress maps generated in 1 year could be applied as a strategic tool allowing precision irrigation to be applied to high-value crops in following years, helping to make more sustainable use of water resources.     

A dynamic knowledge model for water management in maize

Farmland irrigation management and model establishment are always core and difficult contents in crop simulation. This research was focused on exerting the establishment theory of knowledge model, and applying the systematic analysis method and mathematic modeling technology to knowledge expression system of maize water management. Based on soil water balance, a dynamic knowledge model with systematic and wide-application characteristics for maize water management was developed, after periodically quantifying the relationship of irrigation ration between cultivars’ characteristics and environmental factors. Cases were studied on the knowledge model with the data sets of normal year in different eco-sites and those of different rain years in the same eco-sites. The results showed that there was no difference in water saving in normal years under different eco-sites, irrigation schedule changes with eco-sites greatly; but a more obvious difference in different rain years of the same eco-sites existing, with 8.6% and 31.9% of water saving in both more rainfall and normal rainfall years, respectively. Additionally, irrigation in the seedling stage did not change with year types, but it did in Knurling and filling stages. This can be concluded that the irrigation regime designed by the model is well coherent to the actual planting system, which indicated that the model had good decision-making and applicability __________ Translated from Transactions of the Chinese Society of Agricultural Engineering, 2007, 23(6): 165–169 [译自: 农业工程学报]     

Effects of plastic-film mulching and nitrogen application on forage-oriented maize in the agriculture-animal husbandry ecotone in North China

To counter the actual problems of forage shortage and low quality existing in the agriculture-animal husbandry ecotone in North China, a research was conducted to study the effects of plastic-film mulching and nitrogen application on the production of forageoriented maize with the aim of producing water-saving forage with high-yield and good quality. Field experiments combined with laboratory experimental estimation and analysis was adopted. Plastic-film mulching increased the dry biomass of forage-oriented maize by 23.8% with effectively improving the maize’s nitrogen absorption so that the apparent utilization ratio and output-input ratio of nitrogen were enhanced. The content of crude protein in maize plant was increased and thus, forage nutritive quality was improved. Plastic-film mulching remodeled the maize field water consumption scheduling pattern and increased the water use efficiency by over 10%. Nitrogen application to forage-oriented maize co-improved the biomass and the nutritive quality with the nutritive matter (percentage and yield) several times of the biomass. Nitrogen application increased maize biomass production by 36.1%–39.5% and it increased the contents of crude protein and crude fat in maize plant by 109% and 145%, respectively. The yields of the two nutritive matters increased by 160% and 210%. Nitrogen application at the rate of about 200 kg·hm⁻² to the uncovered field and the rate less than 300 kg·hm⁻² to the field with film mulching were considered as the most proper rates to guarantee high yield and good quality of forage-oriented maize and were the rates to keep the available nitrogen balanced in the soil. Plastic-film mulching and nitrogen fertilizer application to forage-oriented maize was an effective way of producing forage with high yield and good quality, relieving the shortage of animal forage and accelerating ecological recovery and economic development in this ecotone in North China. __________ Translated from Scientia Agricultura Sinica, 2006, 40(6): 1206–1213 [译自: 中国农业科学]     

Analysis of soil water availability by integrating spatial and temporal sensor-based data

An efficient irrigation system should meet crop demands for water. A limited water supply may result in reductions in yield, while excess irrigation is a waste of resources. To investigate water availability throughout the growing season, on-the-go sensing technologies (field elevation and apparent electrical conductivity) were used to analyze the spatial variability of soil relevant to its water-holding capacity. High-density data layers were used to identify strategic sites to monitor changes in plant-available water over time. To illustrate this approach, nine locations in a 37-ha agricultural field were selected for monitoring the soil matric potential and temperature at four depths (18, 48, 79 and 109 cm) using wireless technology. Using a linear regression approach, a field-specific model was developed that quantified plant-available water at every field location and at specific points in time. Further analysis was used to quantify the percentage of the field that undergoes a potential shortage in water supply. These results could be used to optimize irrigation scheduling and to assess the potential for variable-rate irrigation.