Delineating productivity zones in a citrus grove using citrus production,tree growth and temporally stable soil data

The productivity of a citrus grove with variation in tree growth was mapped to delineate zones of productivity based on several indicator properties. These properties were fruit yield, ultrasonically measured tree canopy volume, normalized difference vegetation index (NDVI), elevation and apparent electrical conductivity (EC_a). The spatial patterns of soil series, soil color and EC_a, and their correspondence with the variation in yield emphasized the importance of variation in the soil in differentiating the productivity of the grove. Citrus fruit yield was positively correlated with canopy volume, NDVI and EC_a, and yield was negatively correlated with elevation. Although all the properties were strongly correlated with yield and were able to explain the productivity of the grove, citrus tree canopy volume was most strongly correlated (r = 0.85) with yield, explaining 73% of its variation. Tree canopy volume was used to classify the citrus grove into five productivity zones termed as ‘very poor’, ‘poor’, ‘medium’, ‘good’ and ‘very good’ zones. The study showed that productivity of citrus groves can be mapped using various attributes that directly or indirectly affect citrus production. The productivity zones identified could be used successfully to plan soil sampling and characterize soil variation in new fields.     

Spatial variation in tree characteristics and yield in a pear orchard

We examined the spatial structure of fruit yield, tree size, vigor, and soil properties for an established pear orchard using Moran’s I, geographically weighted regression (GWR) and variogram analysis to determine potential scales of the factors affecting spatial variation. The spatial structure differed somewhat between the tree-based measurements (yield, size and vigor) and the soil properties. Yield, trunk cross-sectional area (TCSA) and normalized difference vegetation index (NDVI, used as a surrogate for vigor) were strongly spatially clustered as indicated by the global Moran’s I for these measurements. The autocorrelation between trees (determined by applying a localized Moran’s I) was greater in some areas than others, suggesting possible management by zones. The variogram ranges for TCSA and yield were 30–45 m, respectively, but large nugget variances indicated considerable variability from tree to tree. The variogram ranges of NDVI varied from about 14–27 m. The soil properties copper, iron, organic matter and total exchange capacity (TEC) were spatially structured, with longer variogram ranges than those of the tree characteristics: 31–95 m. Boron, pH and zinc were not spatially correlated. The GWR analyses supported the results from the other analyses indicating that assumptions of strict stationarity might be violated, so regression models fitted to the entire dataset might not be fitted optimally to spatial clusters of the data.     

Management zones delineation using fuzzy clustering techniques in grapevines

Precision viticulture aims at managing vineyards at a sub-field scale according to the real needs of each part of the field. The current study focused on delineating management zones using fuzzy clustering techniques and developing a simplified approach for the comparison of zone maps. The study was carried out in a 1.0 ha commercial vineyard in Central Greece during 2009 and 2010. Variation of soil properties across the field was initially measured by means of electrical conductivity, soil depth and topography. To estimate grapevine canopy properties, NDVI was measured at different stages during the vine growth cycle. Yield and grape composition (must sugar content and total acidity) mapping was carried out at harvest. Soil properties, yield and grape composition parameters showed high spatial variability. All measured data were transformed on a 48-cell grid (10 × 20 m) and maps of two management zones were produced using the MZA software. Pixel-by-pixel comparison between maps of electrical conductivity, elevation, slope, soil depth and NDVI with yield and grape composition maps, set as reference parameters, allowed for the calculation of the degree of agreement, i.e. the percentage of pixels belonging to the same zone. The degree of agreement was used to select the best-suited parameters for final management zones delineation. For the year 2009 soil depth, early and mid season NDVI were used for yield-based management zones while for quality-based management zones ECa, early and mid season NDVI were utilized. For the year 2010 ECa, elevation and NDVI acquired during flowering and veraison were used for the delineation of yield-based management zones while for quality-based management zones ECa and NDVI acquired during flowering and harvest were utilized. Results presented here could be the basis for simple management zone delineation and subsequent improved vineyard management.     

Mapping management zones in a sandy pasture soil using an objective model and multivariate techniques

Soils occupied by dryland pastures usually have low fertility but can exhibit a high spatial variability. Consequently, logical application of fertilisers should be based on an appropriate knowledge of spatial variability of the main soil properties that can affect pasture yield and quality. Delineation of zones with similar soil fertility is necessary to implement site-specific management, reinforcing the interest of methods to identify these homogeneous zones. Thus, the formulation of the objective Rasch model constitutes a new approach in pasture fields. A case study was performed in a pasture field located in a montado (agrosilvopastoral) ecosystem. Measurements of some soil properties (texture, organic matter, nitrogen, phosphorus, potassium, cation exchange capacity and soil apparent electrical conductivity) at 24 sampling locations were integrated in the Rasch model. A classification of all sampling locations according to pasture soil fertility was established. Moreover, the influence of each soil property on the soil fertility was highlighted, with the clay content the most influential property in this sandy soil. Then, a clustering process was undertaken to delimit the homogeneous zones, considering soil pasture fertility, elevation and slope as the input layers. Three zones were delineated and vegetation indices (normalized difference vegetation index, NDVI, and normalized difference water index, NDWI) and pasture yield data at sampling locations were employed to check their differences. Results showed that vegetation indices were not suitable to detect the spatial variability between zones. However, differences in pasture yield and quality were evident, besides some key soil properties, such as clay content and organic matter.

     

The management and planning of citrus orchards at a regional scale with GIS

Citrus growing is regarded as an important cash crop in some regions of China. A geographic information system (GIS) was used to investigate the growing conditions of citrus orchards in Chongqing, China. Digital maps on topography, land use, soil types and climate were obtained and a digital elevation model (DEM) was produced at a scale of 1:10 000 using a GIS. A total of 50 representative orchards (2032 ha) were examined and extensive investigation were carried out in the summer of 2007. Topographic characteristics of the orchards studied were determined using the DEM. About 53% of the total area covered by the orchards has slopes of 8–25° and 4.4% has slopes steeper than 35°. The orchards were dominantly on south-facing slopes (42%). About 80% of the orchards were within 200–400 m in altitude. The orchards were mainly on soil developed on purple shale and limestone (86 and 14% of the total area, respectively). About 42% of the area has soil with a pH of less than 5.5. The majority of the study area (60%) has soil with organic matter contents of 1–2%. General guidelines for sustainable citrus production are proposed based on the topography and soil properties of the citrus orchards. The result of regional planning indicates that about one-third of the total area of Chongqing is suitable for citrus growth (2.68 × 10⁶ ha). A GIS-based database management system provides a new perspective on the management and planning of citrus orchards in Chongqing.     

植物源有机肥配方设计及对梨幼树的营养效应

 【目的】探讨植物源有机肥配方的设计及其在沙地梨幼树上的应用效果。【方法】以养分总量最大化、单一元素含量较高和元素间的平衡关系为基准,鸡粪为参比,从果园常见的间作物种类中优选出黄豆、绿豆、白三叶、紫花苜蓿、沙打旺植株地上部分作为基本配肥材料,加入夏季剪掉的梨树嫩梢,正交设计出32种肥料配方,腐熟后同基准选择出5种配方肥料(T1—T5)施用作为处理,农家肥(T6)施用与不施肥(T7)为对照,分别对盆栽黄金梨幼树根际土壤和幼树叶片中养分相关的指标变化进行测定和比较。【结果】施肥处理较对照显著提高根际土壤有机质含量,降低土壤失水率;提高根际土壤中矿质元素含量及其比例;提高植株生长高度和粗度、叶片干物质的积累量、叶片中矿质元素含量及其比例,提高叶片净光合速率和水分利用率。各种供试的配方肥对梨幼树根际土壤和幼树的营养效应不同：其中,T1对提高土壤碱解N、交换性Ca含量、有效Fe含量、土壤有机质含量,幼树叶片Ca、Fe含量的效果最优;T2对提高土壤有效Cu含量,叶片K含量、Cu含量,叶片干物质积累量效果最优;T3对提高土壤有效K、Mn含量,叶片Mn含量,植株光合速率的效果最优;T4对提高土壤交换性Mg、有效Zn含量,叶片平均N、Mg、Zn含量,幼树株高效果最优。综合评价结果为T1＞T2＞T4＞T3＞ T5＞T6＞T7。【结论】施用植物源有机肥能够有效提高土壤有机质含量,降低土壤失水率,改善土壤养分含量及其平衡关系,提高土壤供肥能力,改善梨幼树的生长状况,优化叶片养分含量及其相互关系,改良幼树叶片的效能,其中T1、T2效果较佳。     

肇庆特色柑橘品种汶朗蜜柚品质评价及其相关性分析

[目的]研究肇庆地区特色柑橘品种汶朗蜜柚的果实品质及其与果园土壤养分和叶片矿质营养元素之间的相关性.[方法]测定了汶朗蜜柚果园土壤pH、有机质、N、P、K等矿质元素含量、叶片N、P、K等矿质元素含量和果实可溶性固形物、可滴定酸和总糖等品质指标,并对其相关性进行分析.[结果]果园土壤中富含铁、钙元素,与汶朗地区有丰富的石灰岩、铁矿有一定的关联.叶片及土壤养分与果实品质有一定的相关性,其中果实品质的形成受树体对矿质元素的吸收和利用能力的影响大于土壤中矿质元素含量的影响.汶朗蜜柚果实品质的合成合理-满意度优于沙田柚的,单因素指标的合理满意度分析显示果皮色泽是制约汶郎蜜柚果实品质的一个重要因素,主要表现为果面疤痕.[结论]研究可为进一步探索柑橘营养生理和品质形成规律提供参考依据,并为汶朗蜜柚栽培管理提供参考.     

Soil spatial variability and site-specific fertilization maps in an apple orchard

In the present study, the spatial variability of some soil physical and chemical properties in a 0.8 ha apple orchard were studied. Sixty soil samples were taken from two sampling depths: 0–0.3 m and 0.3–0.6 m. The soil samples were analyzed for the following soil properties: soil texture, pH, cation exchange capacity and NO₃–N, NH₄–N, P, K, Na, Ca, Mg, Fe, Zn, Mn, Cu, B and organic matter content. Data analysis indicated that most of the nutrients were at sufficient levels. The site-specific application map for N was created based on the amount of N that was removed from the soil with the yield of the previous year. By applying N site-specifically, 38% of N could be saved compared to uniform application.     

Spatial variability and temporal stability of apparent soil electrical conductivity in a Mediterranean pasture

The general objectives of this study were to evaluate (i) the specificity of the spatial and temporal dynamics of apparent soil electrical conductivity (EC_a) measured by a electromagnetic induction (EMI) sensor, over 7 years, in variable conditions (of soil moisture content (SMC), soil vegetation cover and grazing management) and, consequently, (ii) the potential for implementing site-specific management (SSM). The DUALEM 1S sensor was used to measure the EC_a in a 6 ha pasture experimental field four times between June 2007 and February of 2013. Soil spatial variability was characterized by 76 samples, geo-referenced with the global positioning system (GPS). The soil was characterized in terms of texture, moisture content, pH, organic matter content, nitrogen, phosphorus and potassium. This study shows a significant temporal stability of the EC_a patterns under several conditions, behavior that is an excellent indicator of reliability of this tool to survey spatial soil variability and to delineate potential site-specific management zones (SSMZ). Significant correlations were obtained in this work between the EC_a and relative field elevation, pH, silt and soil moisture content. These results open perspectives for using the EMI sensor as an indicator of SMC in irrigation management and of needs of limestone correction in Mediterranean pastures. However, it is interesting to extend the findings to other types of soil to verify the origin of the lack of correlation between the EC_a data measured by DUALEM sensor and properties such as the clay, organic matter or phosphorus soil content, fundamental parameters for establishment of pasture SSM projects.     

Using low-cost geophysical survey to map soil properties and delineate management zones on grazed permanent pastures

Usually, soils utilised for livestock production have similar high spatial variability as those for agricultural or forest use. As a consequence, it is necessary to determine the spatial patterns of the main soil properties as the first stage to implement site-specific management. However, this has to be performed using an inexpensive technique because the profitability in these types of farm are very low, so owners need a cheap, effective, and reliable method to know which zones have similar production potential. Using soil apparent electrical conductivity (ECa) measurements, obtained with a contact sensor at many locations, as the basis to perform a directed soil sampling, 10 samples were taken at two depths (0–0.25 m and 0.25–0.50 m) in a 2.3 ha field in Évora (southern Portugal). Firstly, relationships between ECa and many soil properties were analysed using regression analysis. Six soil properties (clay, silt, fine sand, soil moisture content, pH, and cation exchange capacity) were significantly correlated with ECa. Consequently, spatial distributions of these variables were visualised using map algebra techniques. Later, a fuzzy clustering algorithm was utilised to delineate management zones, resulting in two subfields to be managed separately. Finally, a principal component analysis was conducted to analyse the influence of the soil properties and elevation on the soil variability. It was determined that elevation and clay were the most important contributing properties. Therefore, these can be regarded as key latent variables in this soil. Results showed that low-cost data based on ECa surveys can be used to implement site-specific management in soils with permanent pastures, such as those in the montado or dehesa ecosystems, in the southwest of the Iberian Peninsula.

     

Performance of an Ultrasonic Tree Volume Measurement System in Commercial Citrus Groves

Florida growers have planted citrus groves at varying spacings to improve resource efficiency and to optimize fruit production for maximum economic return. Four commercial groves with different row spacings and tree ages were scanned with a Durand-Wayland ultrasonic system to measure and map tree volumes and to examine the effect of row spacings and tree ages on ultrasonic measurements. The ultrasonically measured volumes (UVs) were compared with manually measured tree volumes (MVs) of 30 trees in each grove to examine the performance of the ultrasonic system. The ultrasonic system measured tree volumes reliably in different groves with an average prediction accuracy (APA) >90%, and correlation with manual measurement of R²=0.95–0.99. Standard error of prediction and root mean square errors were relatively higher in widely spaced old groves than closely spaced young groves. The ultrasonically sensed tree volume map showed substantial variation in canopy volumes (0–240 m³ tree⁻¹) within the grove. Therefore, the use of ultrasonic systems is a better option to quantify and map each tree volume rapidly (real-time) for planning site-specific management practices accurately in commercial groves and for estimating fruit yield.     

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.     

广西柑桔园土壤有效养分含量研究

对广西柑桔主产区果园0~30 cm土壤样品56个进行了土壤有机质和N、P、K、Ca、Mg、Fe、Cu、Zn、B含量测试分析。结果表明,土壤有机质含量比较丰富,土壤速效N、P、K缺乏分别为30.36%、32.14%和28.57%;土壤有效Ca、Mg、B缺乏比较严重,而土壤有效Fe和Cu含量过高;柑桔园土pH、有机质及多个大中微量元素有效养分之间存在显著或极显著正或负相关关系。建议在柑桔园增施Mg、B肥及石灰或其它碱性肥料,减少喷施含Cu杀菌剂。     

Ground-Sensor Soil Reflectance as Related to Soil Properties and Crop Response in a Cotton Field

Bare soil reflectance from airborne imagery or laboratory spectrometers has been used to infer soil properties such as soil texture, organic matter, water content, salinity and crop residue cover. However, the relation of soil properties to reflectance data often varies with soil type and conditions and surface reflectance may not be representative of the conditions in the root zone. The objectives of this study were to assess the soil reflectance data obtained by ground-based sensors and to model soil properties in the root zone as a function of surface soil reflectance and plant response. Ground-based sensors were used to simultaneously monitor soil and canopy reflectance in the visible and near-infrared (VNIR) along six rows and in two growth stages in a 7 ha cotton field. The reflectance data were compared to soil properties, leaf nutrients and biomass measured at 33 sampling positions along the rows. Brightness values of the blue and green bands of soil reflectance were better correlated to soil water content, particulate organic matter and extractable potassium and phosphorus, while those in the red and NIR bands were correlated to soil carbonate content, total nitrogen, electrical conductivity and foliar nutrients. The correlation of red soil reflectance with canopy reflectance was significant and indicated an indirect inverse relationship between soil fertility and plant stress. The integration of surface soil reflectance and plant response variables in a multiple regression model did not substantially improve the prediction of soil properties in the root zone. However, crop nutrient status explained a significant portion of the spatial variability of soil properties related to nitrification processes when soil reflectance did not. The implication of these findings to agricultural management is discussed.     

基于无人机多光谱影像的春玉米田管理分区研究

为了提高大尺度农田管理的针对性，探寻低成本高效的分区方法，以黑龙江省典型黑土区30.8 hm²春玉米田为对象进行分区研究。基于吐丝期无人机多光谱影像，使用多尺度分割与模糊聚类相结合的方法进行分区，同时基于播种前的土壤养分（土壤有机质、速效氮磷钾）、土壤体积含水率、电导率、pH进行模糊聚类分区并作为对照，对分区间春玉米产量和土壤养分进行方差分析，并对分区内变异系数进行比较以评价分区效果。结果表明，基于无人机影像得到4个较优管理分区为M1、M2、M3、M4，各分区产量分别为7 597.53、8 236.35、8 686.98、9 119.93 kg·hm^-2，各分区间产量差异显著，其中M1、M2、M3间土壤养分差异显著（P<0.05），分区内作物产量和土壤养分的变异系数降低；基于土壤数据确定4个分区，即S1、S2、S3、S4，春玉米产量分别为7 754.81、8 173.44、8 860.05、9 153.23 kg·hm^-2，分区间土壤养分、土壤水分差异显著（P<0.05），分区内部土壤均一性提高。综合来看，2种方法的划分结果在空间分布上具有一定的相似性，同级分区的空间重合度分别为40.00%、46.51%、57.45%、59.38%，整体重合度为51.32%。当缺乏土壤数据时，无人机多光谱影像可为农田管理分区提供参考依据。     

有机肥施用方式对柑橘园土壤肥力和柑橘养分、品质的影响

为提高上海崇明柑橘的品质和产量,研究了不同有机肥施肥量和施肥深度对柑橘园土壤肥力和柑橘养分、品质的影响.结果表明:与未施有机肥处理相比,施用有机肥可以不同程度地增加土壤中速效N、有效P和有效K的含量,最好的处理分别高出对照20.9％、24.9％和44.4％;并能提高土壤有机质的含量,最好的处理高出对照16.2％;同时减小土壤容重,降低土壤的pH,从而提高土壤肥力;施用有机肥可以增加土壤中微生物的数量,并且能提高柑橘叶片中全氮和全钾的含量,改善柑橘果实品质.     

梨树叶片黄化与根际土壤微生物及养分关系

以甘肃景泰叶片黄化梨园土壤为例,比较黄化和非黄化梨园0～20 cm和20～40 cm土壤微生物及养分,以探讨与梨树叶片黄化相关因子,为解决黄化问题提供科学依据。研究表明：黄化土壤细菌、放线菌数量都显著少于非黄化土壤的数量,浅层（0～20 cm）黄化土壤的细菌数量少于非黄化土的4662%,放线菌数量少5249%;深层（20～40 cm）黄化土的细菌数量少于非黄化土的7822%,放线菌少5013%。两者的真菌数量差异不显著。黄化土壤20～40 cm的有机质、全氮、全铁、全镁含量显著低于非黄化土壤和黄化土壤0～20 cm土层的含量。因此,梨树叶片黄化与土壤中细菌、放线菌数量减少、20～40 cm土层的有机质、全氮、全铁、全镁含量过低有关。建议重点增施黄化梨园20～40 cm土层的腐熟有机肥。     

克拉玛依市玛依湖区土壤有机质空间异质性分析

目的 研究克拉玛依市东部生态屏障的水源地玛依湖区土壤有机质的空间分布规律, 为湖区的生态环境保护提供科学依据和数据支撑。方法 以玛依湖区为研究对象,通过野外采样和室内分析,利用趋势分析法、反距离权重插值法、空间自相关法和半变异函数法分析玛依湖区不同土层深度土壤有机质的空间分布规律。结果 趋势法分析表明,玛依湖区土壤有机质含量在0~20、20~40、40~60和60~80 cm土层的变化速率存在差异,整体趋势为土壤有机质含量南北方向呈增加趋势、东西方向呈减少趋势。反距离权重插值法(IDW)研究表明,玛依湖区不同土层土壤有机质水平分布差异较大,局部地区土壤有机质含量存在明显的垂直分布特征,土壤有机质含量变化趋势同趋势法分析结果高度一致,整体表现为土壤有机质含量南北方向呈增加趋势、东西方向呈减少趋势。空间自相关法研究表明,0~20、20~40、40~60和60~80 cm土层的Moran指数分别为0.1643、0.1236、0.1955和0.2461,均在空间上呈现出显著正相关;4个土层的Z值分别为3.1510、2.5934、3.5903和4.6355,底层(40~60和60~80 cm)的土壤有机质空间正相关较显著、空间聚集程度最高,表层(0~20和20~40 cm)空间相关性不显著、空间聚集程度较低。半变异函数分析法表明,底层(40~60和60~80 cm)土层的块金效应分别为0.427和0.420,说明土壤有机质具有一定的空间相关性;表层(0~20和20~40 cm)土层的块金效应分别为0.033和0.045,土壤有机质的空间相关性较弱。结论 不同土层土壤有机质含量水平差异较大,南北方向呈增加趋势,东西方向呈减少趋势,局部地区存在明显的垂直分布特征。土壤有机质在表层(0~20和20~40 cm)空间相关性不显著,空间聚集程度较低;在底层(40~60和60~80 cm)空间相关性较显著,空间聚集程度较高。土壤有机质空间异质性受土壤类型、土壤质地、外围植被类型以及湖区面积变化的影响较大;在湖区外围生态屏障建设时,防护林树种、种植深度、种植密度的选择应当结合土壤有机质含量的空间分布状况进行。