Use of aerial thermal imaging to estimate water status of palm trees

A methodology to estimate water status of palm trees from aerial thermal images was developed. Deficit irrigation of 80% in three drip-irrigated date-palm plots in the northern Dead Sea region was manipulated during the winter of 2007 and 2008. An uncooled thermal camera was used for extensive aerial imaging to detect palm trees and pure-canopy pixels by using only aerial thermal images. An automatic procedure, based on watershed segmentation analysis, was developed which enabled detection of all palm trees in the thermal images. Two new methods were developed to select palm trees and pure pixels within them: basin-based and pixel-based. From the temperatures of pure-canopy pixels, significant differences were found between palm trees under commercial and deficit irrigation regimes, in all three plots. Automated detection of canopy, based on aerial thermal images, is a key step towards commercial mapping of within-plot water-status variability. A protocol, based on the developed methodology, was suggested for mapping water status variability in a palm plot, and for irrigation scheduling.     

作物非充分灌溉决策指标研究进展

为了有效地进行非充分灌溉,通过不同方面研究土壤和作物水分亏缺的诊断方法,从而制定科学有效的灌水指标。对目前非充分灌溉的土壤、灌溉、作物等指标的研究现状及存在的问题进行了的阐述,讨论了非充分灌溉决策指标今后研究发展的方向。从目前国内外研究情况来看,应用叶水势、茎直径变化、冠层温度等作物指标来精确诊断作物的水分状况,已逐渐成为非充分灌溉研究领域关注的热点,但其基础理论、监测方法及不同作物的应用效果仍需进一步研究完善。因此,单纯从一种灌溉决策指标出发确定灌溉量是不全面的,如何建立非充分灌溉条件下不同地区、作物的灌溉指标体系将是今后中国重要的研究内容。     

Crop water stress index derived from multi-year ground and aerial thermal images as an indicator of potato water status

Potato yield and quality are highly dependent on an adequate supply of water. In this study, 3 years of information from thermal and RGB images were collected to evaluate water status in potato fields. Irrigation experiments were conducted in commercial potato fields (Desiree; drippers). Two water-deficit scenarios were tested: a short-term water deficit (by suppressing irrigation for a number of days before image acquisition), and a long-term cumulative water deficit. Ground and aerial images were acquired in various phenological stages along the potato growing season. Effects of irrigation treatments were recorded by thermal indices and biophysical measurements of stomatal conductance (SC), leaf water potential, leaf osmotic potential and gravimetric water potential in soil. Canopy temperature was delineated from the thermal images with and without fused information from the RGB image. Crop water stress index (CWSI) was calculated, using three forms of minimum baseline temperature: empirical, theoretical and statistical. An empirical evaluation of maximum baseline temperature of Tair + 7 °C was used in all CWSI forms examined. Statistical tests and comparison of CWSI with biophysical measurements were performed to evaluate the responses to irrigation treatments. The results indicated a high correlation of CWSI with SC from tuber initiation to maturity based on ground and aerial data (0.64 ≤ R² ≤ 0.99). Similar trends of increasing CWSI from well to deficit-irrigated treatments were found in all three growing seasons. The results also showed that CWSI may be calculated based merely on thermal imagery data.     

海伦县主要农作物气候生态适应性的试验研究

本文通过在自然状态下的大面积田间试验与平行气象观测相结合的方法,研究了松嫩平原北部地区的气象条件(包括太阳辐射、气温、降水)与当地主栽作物玉米、大豆、小麦、甜菜的生长发育及群体生产力之间的关系,并得出结论:1.当地光能资源潜力较大,热量条件是主要限制因子,自然降水量是影响因子。2.玉米对当地光、热、水资源的综合利用程度最高,大豆和甜菜次之,小麦略差。3.但就气候生态适应性而言,以大豆表现最佳,甜菜次之,小麦和玉米略差。     

基于红外热图像的棉花花铃期水分胁迫指数与光合参数的关系

[目的]分析棉花冠层水分胁迫指数(CWSI)与光合参数的相关关系,建立CWSI与光合参数的相关模型,为CWS1用于定量监测新疆棉花冠层水分胁迫状况的研究提供依据.[方法]在棉花生长的花铃期,利用Fluke热像仪获取2个棉花品种4水平水分处理冠层的红外热图像,运用图像处理技术,提取棉花冠层受光叶片的温度,并将湿人工参考表面(WARS)的温度运用到Jones定义的作物水分胁迫指数(CWSI)的经验公式中,计算CWSI;同时,采用LI-6400便携式光合仪测得棉花叶片净光合速率(Pn)、气孔导度(Gs)和蒸腾速率(Tr),并探索棉花水分胁迫指数与其光合参数的定量关系.[结果]水分胁迫下CWSI值升高,而Pn、Gs和Tr值相应降低.花铃期的4个关键生育时期CWSI分别与Pn、Gs和Tr呈极显著的线性负相关关系,CWSI与Pn、Gs和Tr的平均相关系数分别为rCWSI-Pn=-0.8823**、rCWSI-GS=-0.9073**和rCWSI-Tr,=-0.9356**.[结论]棉花水分胁迫指数CWSI与光合参数Pn、Gs和Tr同步反映棉花冠层的水分状况.     

Mapping crop water stress index in a ‘Pinot-noir’ vineyard: comparing ground measurements with thermal remote sensing imagery from an unmanned aerial vehicle

Characterizing the spatial variability in water status across vineyards is a prerequisite for precision irrigation. The crop water stress index (CWSI) indicator was used to map the spatial variability in water deficits across an 11-ha ‘Pinot noir’ vineyard. CWSI was determined based on canopy temperatures measured with infrared temperature sensors placed on top of well-watered and water-stressed grapevines in 2009 and 2010. CWSI was correlated with leaf water potential (Ψ_L) (R ² = 0.83). This correlation was also tested with results from high resolution airborne thermal imagery. An unmanned aerial vehicle equipped with a thermal camera was flown over the vineyard at 07:30, 09:30, and 12:30 h (solar time) on 31 July 2009. At about the same time, Ψ_L was measured in 184 grapevines. The image obtained at 07:30 was not useful because it was not possible to separate soil from canopy temperatures. Using the airborne data, the correlation between CWSI and Ψ_L had an R ² value of 0.46 at 09:30 h and of 0.71 at 12:30 h, suggesting that the latter was the more favorable time for obtaining thermal images that were linked with Ψ_L values. A sensitivity analysis of varying pixel size showed that a 0.3 m pixel was needed for precise CWSI mapping. The CWSI maps thus obtained by airborne thermal imagery were effective in assessing the spatial variability of water stress across the vineyard.     

Recalibrating plant water status of winter wheat based on nitrogen nutrition index using thermal images

Precision Agriculture - Accurate and timely assessment of crop water status is imperative for in-season irrigation scheduling in crop production. The canopy water stress index and water deficit...     

Field performance in agricultural settings of a wireless temperature monitoring system based on a low-cost infrared sensor

Continuous measurement of plant canopy temperature is useful in both research and production agriculture settings. Industrial-quality infrared thermometers which are often used for measurement of canopy temperatures, while reliable, are not always cost effective. For this study a relatively low-cost, consumer-quality infrared thermometer was incorporated into a wireless monitoring system intended for use in plant physiological studies and in agricultural production settings. The field performance of this low-cost wireless system was compared to that of a typical research system based on an industrial-quality infrared thermometer. Performance was evaluated in terms of: reliability of data acquisition, quality of seasonal temperature measurements, seasonal stability of the consumer-quality infrared sensor, and the equivalence of temperatures measured by the consumer-quality and industrial-quality temperature sensors. Results indicate that for many common uses of plant temperature data, the two sensors provide functionally equivalent results. The cost savings and ease of use associated with the low-cost wireless temperature monitoring system present advantages over the higher-cost industrial-quality sensors which may make them a viable alternative in many agricultural settings.     

Agricultural applications of a low-cost infrared thermometer

Plant canopy temperature is used in many studies of plant/environment interactions and non-contact measurement is often made with radiometric surface thermometers commonly referred to as infrared thermometers. Industrial-quality infrared thermocouples are widely available and often used in agricultural research. While research on canopy temperature has provided management tools for production agriculture, the high cost of the industrial-quality infrared thermocouples has limited their adoption and use in production agriculture settings. Our objective was to evaluate a low-cost consumer-quality infrared thermocouple as a component of a wireless thermal monitoring system designed for use in a production agriculture setting. The performances of industrial-quality and low-cost consumer-quality sensors were compared under controlled constant temperature and under field conditions using both grass and cotton canopies. Results demonstrate that under controlled constant-temperature the two types of infrared thermocouples were “significantly the same” at 10 °C, 20 °C and 30 °C and “significantly not the same” at 40 °C and 50 °C. Across the temperature range tested, the consumer-quality infrared thermocouples temperature reading was closer to the thermocouple reading than the industrial-quality infrared thermocouples. A field comparison of industrial-quality and consumer-quality infrared thermocouple sensors monitoring a grass canopy and a cotton canopy indicated that the two types of sensors were similar over a 13–35 °C range. The measurement of temperature made with two types of sensors would not differ significantly. Based on these results we conclude that the lower-cost consumer-quality infrared thermometers are suitable for use in production agricultural applications.     

基于热红外图像的小麦品种抗旱性鉴定与评价

【目的】分析不同基因型小麦冠层的温度参数相关信息,探寻快速高效筛选冬小麦抗旱品种的指标和方法,给冬小麦抗旱品种筛选提供参考依据。【方法】本研究以小麦为研究对象,获取干旱胁迫下10个抗旱性存在差异的小麦品种冠层热红外图像,采用温度频率直方图等分析方法提取冠层温度特征参数,明确温度特征参数与抗旱指数之间定量关系,分析冠层温度特征参数对筛选冬小麦抗旱品种的有效性。【结果】基于产量抗旱指数（DRI）的分级标准将测定小麦品种分为4种抗旱类别,其抗旱性越强,最大光化学效率（F_v/F_m）,植株含水量（PWC）,气孔导度（G_s）,蒸腾速率（T_r）和籽粒产量越稳定。基于热红外图像提取冠层温度特征参数,小麦抗旱性越强,冠层温度的差异性越小,冠层温度的离散程度也较小。产量抗旱指数（DRI）与拔节期、孕穗期和开花期的作物冠层温度与环境温度的偏差（CTD）均呈现极显著的正相关关系,相关系数r为0.79—0.84,而与冠层温度标准差（CTSD）、变异系数(CTCV)、水分胁迫指数（CWSI）和冠层相对温差（CRTD）呈显著负相关（r=-0.56—-0.78）。基于单一生育时期冠层温度特征参数建立了产量抗旱指数（DRI）回归模型,估算精度为r²=0.73—0.87,其中以拔节期预测模型精度最高。而基于3个生育时期的相关冠层温度参数CTD、CTCV、CTSD CWSI组合构建产量抗旱指数（DRI）预测模型,较基于单一生育时期预测精度显著提升（r²=0.95）。【结论】利用热红外图像可进行小麦品种抗旱性的早期鉴定与快速评价,这对促进作物高效节水生产具有重要意义。     

间作甜菜的生产技术研究

通过甜菜与白菜不同间作方式、甜菜喷施不同促进剂与抑制剂的田间试验,研究了不同栽培措施对甜菜产量与品质的影响。结果表明,间作甜菜受种植密度与白菜胁迫的影响,较单作甜菜产量显著降低,白菜与甜菜2∶1间作甜菜产量为单作的28.9%,2∶2间作甜菜产量为单作的50.1%;白菜采收后停止灌溉,不同种植方式的甜菜含糖量无明显差异;生长调节剂对甜菜含糖量无显著影响。白菜采收后控水是保证与促进甜菜糖分品质的关键。     

Using high resolution UAV thermal imagery to assess the variability in the water status of five fruit tree species within a commercial orchard

This paper deals with the assessment of heterogeneity in water status in a commercial orchard, as a prerequisite for precision irrigation management. Remote sensing-derived indicators could be suitable for mapping water stress over large areas, and recent studies have demonstrated that high resolution airborne thermal imagery enables the assessment of discontinuous canopies as pure tree crowns can be targeted, thus eliminating the background effects. Airborne campaigns were conducted over a drip-irrigated commercial orchard in Southwestern Spain composed of five different orchard tree crops. An unmanned aerial vehicle with a thermal camera onboard was flown three times during the day on 8 July 2010, at 9, 11 and 13 h (local time). Stem water potential was measured at the same time of the flights. In some irrigation units, irrigation was stopped prior to the measurement date to induce water deficits for comparative purposes. Several approaches for using the thermal data were proposed. Daily evolution of the differential between canopy and air temperature (T _c  ? T _a ) was compared to tree water status. The slope of the evolution of T _c  ? T _a with time was well correlated with water status and is proposed as a novel indicator linked with the stomatal behavior. The Crop Water Stress Index (CWSI) was calculated with the temperature data from the 13.00 h flight using an empirical approach for defining the upper and lower limits of T _c  ? T _a . The assessment of variability in water status was also performed using differences in relative canopy temperatures. Ample variability was detected among and within irrigation units, demonstrating that the approach proposed was viable for precision irrigation management. The assessment led to the identification of water-stressed areas, and to the definition of threshold CWSI values and associated risks. Such thresholds may be used by growers for irrigation management based on crop developmental stages and economic considerations.     

Spring Wheat Response to Fertilizer Nitrogen Following a Sugar Beet Crop Varying in Canopy Color

Experiments were conducted in the Red River Valley (RRV) of Minnesota to determine the responses of hard red spring wheat (Triticum aerstivum L.) to fertilizer N after a sugar beet (Beta vulgaris L.) crop that varied spatially in canopy color and N content. A color aerial photograph was acquired of the sugar beet field just prior to root harvest, and six sites were selected that varied in sugar beet canopy color, three each of green and yellow canopy sites. The three green sugar beet canopies returned 369, 265, and 266 kg N ha^–1 to the soil while the three yellow sugar beet canopies returned 124, 71, and 73 kg N ha^–1 to the soil. Spring wheat response to fall-applied urea-N fertilizer (0, 45, 90, 135, and 180 kg N ha^–1) was determined the following year at each of the above antecedent canopy sites. Soil NO₃-N in the top 0.6 m of soil varied among the locations with a range of 35 to 407 kg NO₃-N ha^–1 at the green canopy sites and 12 to 23 kg NO₃-N ha^–1 at the yellow canopy sites. Application of fertilizer N according to traditional recommendation methods would have resulted in fertilizer applications at all three yellow canopy sites and two of the three green canopy sites. At the antecedent green sugar beet canopy sites, fertilizer N had little or no effect on spring wheat grain yields, grain N concentration, anthesis dry matter, and anthesis N content. In contrast, fertilizer N increased all four parameters at the antecedent yellow sugar beet canopy sites. The data indicate that fertilizer N management can be improved by using remote sensing to delineate management zones according to antecedent sugar beet canopy color.     

Low altitude remote sensing technologies for crop stress monitoring: a case study on spatial and temporal monitoring of irrigated pinto bean

Site-specific crop management is a promising approach to maximize crop yield with optimal use of rapidly depleting natural resources. Availability of high resolution crop data at critical growth stages is a key for real-time data-driven decisions during the production season. The goal of this study was to evaluate the possibility of using small unmanned aerial system (UAS)-based remote sensing technologies to monitor the crop stress of irrigated pinto beans (Phaseolus vulgaris L.) with varied irrigation and tillage treatments. A small UAS with onboard multispectral and infrared thermal imaging sensors was used to collect data from bean field plots on three growth stages in 2015 and 2016, respectively. Indicators including green normalized vegetation index (GNDVI), canopy cover (CC, ratio of ground covered by crop canopy to the total plot area) and canopy temperature (CT, °C) of crops were extracted from imaging data and correlated with ground-reference crop yield and leaf area index (LAI) estimated with a handheld ceptometer. Results show that GNDVI, CC and CT were able to differentiate crops with full and deficit irrigation treatments at each of the three growth stages in both years. Developed indicators were strongly correlated with to the crop yield with Pearson correlation coefficients (r) of approximate 0.71 and 0.72 for GNDVI and CC, respectively, in the early growth stage (54 days after planting) in both years. Canopy temperature showed even stronger correlation (r > 0.8) with yield at early growth stage. Performance of small UAS-based imagery-based indicators in crop stress monitoring and crop yield estimation was better than or comparable to that of the ground-based LAI estimates, indicating the potential of such remote sensing tool in rapid crop stress monitoring and management.     

两系法杂交稻安全制种的低温防御灌水理论与技术

 归纳了中国南方稻区8月中下旬低温的发生频率、强度和持续时间。明确了保证两系法杂交稻制种纯度的灌水增温幅度以2℃为宜。测定了培矮64S育性敏感期的幼穗高度和冠层结构特征，分析了灌水后冠层增温的空间和时间规律。结果表明，灌水的有效增温高度在株高40 cm以内，以20 cm处最为显著，平均可达3.1℃。提出防御低温的灌水技术为：15～20 cm的灌水深度；流动灌水；晴（昙）天17时灌水，次日10时排水，阴（雨）天24 h灌水；田块比较大时，适当增加入水口和出水口数量。通过不育系花粉育性和自交结实率的观测，证实了该技术的有效性。     

不同灌溉量下氮肥施用时期对甜菜光合物质生产及产量的补偿作用

【目的】研究不同灌溉定额下氮肥施用时期对甜菜生理指标、灌溉水生产率、氮肥农学利用率及氮肥偏生产力的影响,为甜菜水肥高效利用提供理论依据。【方法】采用裂区试验设计,主区为2个灌溉定额,副区为5个氮肥施用时期(纯N总量一致120 kg/hm²)。【结果】同一氮肥施用时期,随着灌溉量的减少甜菜Pn、Er、茎叶干重、根干重、总干重、单根重、产量、产糖量(除N4处理)及氮肥偏生产力均呈下降趋势,甜菜含糖率、产量增产率、灌溉水生产力及氮肥农学利用效率均有提高;同一灌溉量,随着氮肥施用时期的后移各项测定指标先增后减,N4处理补偿指数最优,灌溉定额4 650比5 850 m³/hm²甜菜各项指标补偿指数提高-1.6%~27.5%。【结论】在北疆甜菜产区合理的水氮管理模式为:灌溉定额4 650 m³/hm²,氮肥基施1/2,7月中旬追施1/2。     

河套灌区调亏畦灌对加工番茄生长发育、产量和果实品质的影响

采用大田畦灌试验,研究花期和坐果期分别实施67%和33%的灌水量对河套地区加工番茄生长发育、产量和果实品质的影响。结果表明:花期水分亏缺会使土壤电导率显著增大,而坐果期不明显。各调亏处理的硬度均显著增大,储藏性能得到了提高。调亏处理后口感品质指标(可溶性固形物、有机酸与糖酸比)和营养品质指标(维生素C、可溶性糖与番茄红素)平均值均高于充分灌溉处理,且随亏缺度加深而不同幅度增加,但只有可溶性固形物TSS和维生素C含量在重度亏缺时达到显著差异;在轻度亏缺下,坐果期处理优于花期,有效产量和水分生产率相对对照分别提高了10.25%和7.28%。在加工番茄果期实施67%灌水量的轻度亏缺,可以得到最高有效产量和水分生产率,且各外观品质、储藏品质、口感品质和营养品质均有所提高。     

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.     

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.