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Crop health assessment and early yield predictions are highly crucial under biotic stress conditions for crop management and market planning by farmers and policy planners. The objective of this study was, therefore, to assess the impact of different levels of wilt disease on the biophysical parameters of chickpea and developing machine learning (ML) models for early yield prediction. Field experiments were carried out over three years at the Indian Agricultural Research Institute research farm in New Delhi. Thermal and visible images were collected alongside the measurement of crop biophysical parameters, including leaf area index (LAI), photosynthesis, transpiration rate, stomatal conductance, relative leaf water content (RWC), membrane stability index (MSI), and NDVI, for 85 chickpea genotypes with varying levels of wilt resistance. ML models were developed for early yield prediction by combining visible and thermal image indices with biophysical parameters. The results showed that the canopy temperatures were directly correlated with increasing levels of wilt severity. Crop photosynthesis, stomatal conductance, transpiration, LAI, RWC, MSI, and NDVI dropped significantly with increasing levels of wilt severity. Yield reductions of 44-69% were observed in susceptible genotypes. Machine learning models were able to give accurate early yield predictions. The accuracy of the models increases as we move closer to the harvest. Ranking of the model's performances indicated that XGB is the best model to predict chickpea yield under wilt conditions. NDVI was identified as most important variable for yield prediction. The findings of the study quantified the impacts of wilt on important crop biophysical parameters and highlighted the suitability of ML models in early yield prediction under different levels of disease severity. [ABSTRACT FROM AUTHOR]

The use of thermal-based crop water stress index (CWSI) has been studied in many crops in semi-arid regions and found as an effective method in detecting real-time crop water status of commercial fields remotely and non-destructively. However, to our knowledge, no previous studies have validated the usefulness of CWSI in a temperate crop like wild blueberries. Additionally, the temporal changes of the water status estimation model has not been well-studied. In this multi-year study, Unoccupied Aerial Vehicle (UAV)-borne thermal imageries were collected in 2019, 2020, and 2021 to test the temporal effects and the impact of different approach-based reference temperatures (Twet, wet reference temperature; Tdry, dry reference temperature) on leaf water potential (LWP) estimation models using CWSI in two large adjacent wild blueberry fields in Maine, United States. We found that different sampling dates have a significant impact on LWP estimation models using CWSISE (statistical Twet and empirical Tdry reference) and CWSISS (statistical Twet and statistical Tdry reference). Further, CWSIBB calculated with bio-indicator-based Twet and Tdry reference was found more effective (r² = 0.79) in estimating LWP in 2021, compared to the CWSISE and CWSISS approaches in 2019 (r² = 0.34 & r² = 0.36), 2020 (r² = 0.38 & r² = 0.44) and 2021 (r² = 0.43 & r² = 0.46). CWSIBB -LWP model-based crop water status maps show high variation in the crop water status of wild blueberries, even in an evenly irrigated field, suggesting the potential of UAV-borne thermal cameras to detect real-time crop water status within the field, with the CWSIBB calculated from bio-indicator-based references being more reliable. Our results could be used for precision irrigation to increase the overall water use efficiency and profitability of wild blueberry production. [ABSTRACT FROM AUTHOR]

The present study addresses the applicability of the crop water stress index (CWSI) derived from canopy temperature to detect the crop water stress of paddy crop. The performance of two artificial intelligence techniques, adaptive neuro-fuzzy inference system (ANFIS) and self-organizing map (SOM), are compared while determining the CWSI of paddy crop. Field experiments were conducted with varying irrigation water applications during two seasons in 2021 and 2022. The ANFIS and SOM-simulated CWSI values were compared with the experimentally calculated CWSI (EP-CWSI). Multiple regression analysis was used to determine the upper and lower CWSI baselines. The upper CWSI baseline was found to be a function of crop height and wind speed, while the lower CWSI baseline was a function of crop height, air vapor pressure deficit, and wind speed. The performance of ANFIS and SOM were compared based on mean absolute error (MAE), mean bias error (MBE), root mean squared error (RMSE), index of agreement (d), Nash–Sutcliffe efficiency (NSE), and coefficient of correlation (R2). The ANFIS (R2=0.81 , NSE=0.73 , d=0.94 , RMSE=0.04 , MAE=0.00–1.76 and MBE=−2.13–1.32) outperformed the SOM model (R2=0.77 , NSE=0.68 , d=0.90 , RMSE=0.05 , MAE=0.00–2.13 and MBE=−2.29–1.45). Overall, the results suggest that ANFIS is a reliable tool for accurately determining CWSI in paddy crops compared to SOM. [ABSTRACT FROM AUTHOR]

As an important physiological indicator, wheat canopy temperature (CT) can be observed after flowering in an attempt to predict wheat yield and quality. However, the relationship between CT and wheat yield and quality is not clear. In this study, the CT, photosynthetic rate (Pn), filling rate, wheat yield, and wheat quality of 68 wheat lines were measured, in an attempt to establish a connection between CT and yield and quality and accelerate the selection of new varieties. This experiment used an infrared imaging camera to measure the CT of wheat materials planted in the field in 2022. Twenty materials with significant temperature differences were selected for planting in 2023. By comparing the temperature trends in 2022 and 2023, it is believed that materials 4 and 13 were cold-type materials, while materials 3 and 11 were warm-type materials. The main grain filling period of cold-type materials occurs in the middle and late stages of the grain filling period and the Pn and the thousand-grain weights of cold-type materials were higher than those of warm-type materials. Similarly, under continuous rainy conditions, cold-type materials had a higher protein and wet gluten contents, while warm-type materials had higher sedimentation values and shorter formation times. [ABSTRACT FROM AUTHOR]

Canopy temperature is an important parameter for monitoring the physiological status of maize. The study of its change law can help to improve the growth environment and increase the yield and quality. Based on the RGB, thermal infrared, and multispectral images obtained by an Unmanned Aerial Vehicle (UAV), two peak threshold methods were used in this study to eliminate the soil background and obtain the maize canopy information in the study area. Then, by using the radiation transmission model and Planck's law, the maize canopy temperature was extracted, and the correlation of canopy temperature change with the regional coverage and soil drought degree was analysed. Results indicated that the accuracy of canopy temperature extraction can be effectively enhanced by eliminating the influence of soil background. At jointing and filling stages, the Pearson correlation coefficients r of canopy temperature and coverage were 0.731 and 0.722, respectively, and the slope of the linear fitting model was less than 0, indicating that the coverage has a negative impact on canopy temperature, i.e., the higher the coverage, the lower the canopy temperature, and vice versa. Additionally, statistical analysis of the canopy temperature and temperature vegetation drought index (TVDI) clustering results at the jointing and filling stages demonstrated that the total overlapping rates of the categories were 72.5% and 41.0% respectively, suggesting that maize canopy temperature is related to regional soil drought degree, the change range of canopy temperature increases with the TVDI value, and the soil drought degree at the jointing stage has a large impact on maize canopy temperature change than that at the filling stage. This study provides technical support for extracting and analysing crop canopy temperature change by using UAV thermal infrared technology. [ABSTRACT FROM AUTHOR]

Malt barley is a crucial irrigated crop in the semi-arid Western United States, where the states of Idaho, Colorado, Wyoming, and Utah account for 92% of the irrigated production acreage and 30% of total U.S. production. In this region, spring malt barley's seasonal evapotranspiration ranges from 400 to 650 mm, and competition for limited water supplies, coupled with drought, is straining regional water resources. This study aimed to investigate the use of canopy temperature for deficit irrigation scheduling of malt barley. Specifically, the objectives were to use data-driven models to estimate well-watered (TLL) and non-transpiring (TUL) canopy temperatures, correlate the crop water stress index (CWSI) with malt barley yield and quality measures, and assess the applicability of CWSI for malt barley irrigation scheduling in a semi-arid climate. A 3-year field study was conducted with five irrigation treatments relative to estimated crop evapotranspiration (full, 75%, 50%, 25%, and no irrigation) and four replicates each. Continuous canopy temperature measurements and meteorological data were collected, and a feedforward neural network model was used to predict TLL, while a physical model was used to estimate TUL. The neural network model accurately predicted TLL, with a strong correlation (R2 = 0.99), a root mean square error of 0.89 °C, and a mean absolute error of 0.70 °C. Significant differences in calculated season-average CWSI were observed between the irrigation treatments, and relative evapotranspiration, malt barley relative yield, test weight, and plump kernels were negatively correlated with the season-average CWSI, while seed protein was positively correlated. The relationship between daily CWSI and fraction of available soil water was well described by an exponential decay function (R2 = 0.72). These results demonstrate the applicability of data-driven models for computing CWSI of irrigated spring malt barley in a semi-arid environment and their ability to assess plant water stress and predict crop yield and quality response from CWSI. [ABSTRACT FROM AUTHOR]

This study aimed to determine whether canopy and air temperature difference (ΔT) as an existing simple normalizing index can be used to detect an increase in canopy temperature induced by soil drought in urban parks, regardless of the unique energy balance and three-dimensional (3D) structure of urban trees. Specifically, we used a thermal infrared camera to measure the canopy temperature of Zelkova serrata trees and compared the temporal variation of ΔT to that of environmental factors, including solar radiation, wind speed, vapor pressure deficit, and soil water content. Normalization based on a 3D energy-balance model was also performed and used for comparison with ΔT. To represent the 3D structure, a terrestrial light detection and ranging-derived 3D tree model was used as the input spatial data. The temporal variation in ΔT was similar to that of the index derived using the energy-balance model, which considered the 3D structure of trees and 3D radiative transfer, with a correlation coefficient of 0.85. In conclusion, the thermal-image-based ΔT performed comparably to an index based on the 3D energy-balance model and detected the increase in canopy temperature because of the reduction in soil water content for Z. serrata trees in an urban environment. [ABSTRACT FROM AUTHOR]

The difference of canopy-air temperature can indirectly monitor the variation of tea tree heat and moisture. However, the time lag effect between the tea tree canopy temperature and atmospheric temperature of tea plantation will affect the monitoring effect. In order to explore the time lag effect and the variation law between canopy temperature and atmospheric temperature, the variation characteristics of tea tree canopy temperature and atmospheric temperature of tea plantation during different tea picking seasons and different weather types were analyzed based on the monitoring data of microclimate station in tea plantation and near national meteorological station in Wuyuan from March to September in 2020. The simulated models of daily average canopy temperature and atmospheric temperature of tea plantation according to different weather types were established through the linear regression method and tested to provide data support for tea meteorological service. The results showed that: 1) the diurnal variation of tea tree canopy temperature and atmospheric temperature of tea plantation showed an obviously single-peak trend during different tea picking seasons and different weather types, while the change intensity of canopy temperature was greater than that of atmospheric temperature of tea plantation, and the peak time of canopy temperature was generally about 1h earlier than that of atmospheric temperature of tea plantation. (2) The point temperature difference of tea tree canopy and atmospheric temperature of tea plantation within 24h a day were generally ranked as spring tea>autumn tea>summer tea, sunny days>cloudy days>rainy days. In general, the canopy temperature was above or near to the atmospheric temperature of tea plantation around noon, while the canopy temperature was lower than the atmospheric temperature of tea plantation at all times in rainy days. (3) From the aspects of daily average temperature, it showed that the canopy was generally lower (1-2°C) than which in the atmosphere, but the changing trend was the same. (4) All kinds of daily average temperature prediction models were approved by 0.01 level significant test, which meaned the simulation effect were good generally. What's more, the simulation effect of the atmospheric temperature of tea plantation prediction models were better than that of canopy temperature. In addition, under different weather types, the optimal effect of the prediction models were demonstrated in rainy days, followed by sunny days, and relatively poor in cloudy days. [ABSTRACT FROM AUTHOR]

Awns illustrate an important photosynthetic organ of the cereal spike, especially under water stress. Barley (Hordeum vulgare L.) spikes are distinguished by long awns; nevertheless, the actual changes in barley awn dimensions under drought stress have not been adequately studied. In the present work, six barley genotypes with varying degrees of drought tolerance were investigated in a 2-year field experiment under well-watered (WW) and terminal drought stress (TDS) conditions based on randomized complete block design with three replications. The results showed that although TDS caused a notable reduction in awn dimensions compared to WW, the density of barbs on the awn surface significantly increased in all barley genotypes. In addition, the barb contact angle decreased significantly under TDS conditions compared to WW. Awn area had a significantly positive correlation with thousand grain weight and grain yield in both treatments and growing seasons. Also, highly significant correlations were observed between leaf stomatal conductance, awn area, and barb density under both conditions. In TDS, two genotypes demonstrated lower carbon isotope discrimination: Morocco, with higher awn dimensions, and PBYT 46, with a higher increase in barbs density on the awn surface and a lower canopy temperature. This research underlines barbs density on the awn surface by reflecting the light and a lower increase in the canopy temperature plays a more pivotal role than awn dimensions on water use efficiency in barley under terminal drought. [ABSTRACT FROM AUTHOR]

Intergovernmental panel on climate change has predicted a 1.5 °C increase in temperature and a 4–27% decrease in precipitation in the next decade. Drought and heat cause 60% and 40% wheat yield losses by altering the physiology of the crop. Understanding the impact of these stresses on wheat physiological traits can help in developing tolerant genotypes. Forty-two genotypes were evaluated under non-stress (TSIR-NS), drought (TSRF-DR), and heat stress (LSIR-HT) for two crop seasons. The experiments were laid in rectangular lattice (6 × 7) design with two replications. Data for grain yield and various physiological traits were recorded at GS70 and GS75. Grain yield (GY) was reduced by 29.0%, 16.4% under heat, and by 48.7% and 30.2% under drought stress during the two seasons. Heat susceptibility index (HSI) and drought susceptibility index (DSI) of these genotypes ranged from 0.3 to 1.8 and 0.4 to 1.4. Among the top five high-yielding lines under TSIR-NS, only one (G39) was drought tolerant, while under LSIR-HT, four high-yielding lines (G40, G41, G04, and G35) of the top five genotypes were heat tolerant. Conversely, the top five high-yielding lines under TSRF-DR were drought tolerant. Overall, 21 lines were tolerant to heat stress and 22 to drought and 12 genotypes were tolerant to both stresses. Chlorophyll was higher under LSIR-HT and TSRF-DR. Normalized difference vegetation index at GS70 (NDVIA) and normalized difference vegetation index at GS75 (NDVI15DAA) suffered a drastic reduction under TSRF-DR. The stomatal conductance (gs) and transpiration (E) were greatly reduced under drought and increased under LSIR-HT. Assimilation (A) and photosynthetic water use efficiency (WUE) were reduced under heat stress. The correlation of physiological traits with GY was also calculated. The traits chlorophyll fluorescence at GS70 (CFLA), NDVI 15DAA, and E contributed toward GY under TSIR-NS, CFLA, NDVI15DAA, WUE, Canopy temperature at GS75 (CT15DAA), and gs under TSRF-DR, and A, NDVIA, CFLA, and chlorophyll fluorescence at GS75 (CFL15DAA) under LSIR-HT. CFLA contributed toward GY under all environments. Finally, traits such as A, E, WUE, and CFL15DAA were impacted by both stresses, while NDVIA and NDVI15DAA and gs were only affected by drought and CFLA and CTA were only influenced by heat stress. [ABSTRACT FROM AUTHOR]

Studying the physiological mechanisms underlying the traits associated with salt tolerance in genotypes could lead to the discovery of new genetic resources for salt tolerance. In this study, the mechanisms of salt tolerance were evaluated, based on ionic, physiological, and agronomic traits in four varieties that differ in their salt tolerance and in 18 F8 recombinant inbred lines (RILs) grown in real field conditions. The salt tolerance of plant materials was assessed under both normal (3.5 mM NaCl) and high salinity stress (150 mM NaCl) conditions for two consecutive years. Different growth and physiological traits were assessed 75 days after sowing, while ion contents in the shoots, grain yield, and its components were determined at the maturity stage. Multivariate analysis was used to conduct a comprehensive evaluation of salt tolerance across various genotypes and traits. The ANOVA results showed significant differences (p ≤ 0.05 and 0.001) among salinity, genotypes, and their interactions for all ionic and agro-physiological traits, with a few exceptions. Salinity stress resulted in a considerable increase in Na+ content and canopy temperature (CT), with a simultaneous decrease of 11.3% to 94.5% in other ionic and agro-physiological traits compared to the control treatment. However, the salt-tolerant genotypes showed minimal increases in Na+ content and CT, as well as decreases in other ionic and agro-physiological traits when compared to salt-sensitive genotypes under salinity stress. All ionic and agro-physiological traits exhibited strong correlations with each other under salinity stress, but these correlations were weak or insignificant under control conditions. The principal component analysis identified Na+ and CT as negative indicators and other ionic and agro-physiological traits as positive indicators for salt tolerance under salinity stress. The negative indicators were strongly linked to salt-sensitive genotypes, while the positive indicators were closely associated with salt-tolerant genotypes. Heatmap clustering, using multiple traits, successfully differentiated the salt-tolerant genotypes from the salt-sensitive ones. The salt-tolerant group showed a significant reduction in Na+ content by 36.9%, in CT by 10.0%, and in HI by 16.7%, along with an increase of 6.3–51.4% in other ionic and agro-physiological traits compared to the salt-sensitive group. In conclusion, the mechanisms associated with Na+ exclusion and high K+/Na+ and Ca2+/Na+ ratios, as well as chlorophyll and relative water content, along with low CT, resulted in significant improvements in growth and yield under salinity stress conditions. Given that the effectiveness of various ionic and agro-physiological traits in evaluating salt tolerance in wheat has been proven in real field conditions, these traits will play a key role in the development of salt-tolerant wheat genotypes. [ABSTRACT FROM AUTHOR]

Understanding tree transpiration variability is vital for assessing ecosystem water‐use efficiency and forest health amid climate change, yet most landscape‐level measurements do not differentiate individual trees. Using canopy temperature data from thermal cameras, we estimated the transpiration rates of individual trees at Harvard Forest and Niwot Ridge. PT‐JPL model was used to derive latent heat flux from thermal images at the canopy‐level, showing strong agreement with tower measurements (R2 = 0.70–0.96 at Niwot, 0.59–0.78 at Harvard at half‐hourly to monthly scales) and daily RMSE of 33.5 W/m2 (Niwot) and 52.8 W/m2 (Harvard). Tree‐level analysis revealed species‐specific responses to drought, with lodgepole pine exhibiting greater tolerance than Engelmann spruce at Niwot and red oak showing heightened resistance than red maple at Harvard. These findings show how ecophysiological differences between species result in varying responses to drought and demonstrate that these responses can be characterized by deriving transpiration from crown temperature measurements. Plain Language Summary: Understanding how forests use water, especially during droughts, is crucial for a changing climate. We developed a method using thermal cameras to estimate individual tree water loss (transpiration), something traditional methods lack. These cameras capture temperature data from the tree crown, which is then used to estimate transpiration rates. Tests in two forests showed this method aligns well with existing water use measurements. The study also revealed fascinating differences in how species handle drought. For instance, lodgepole pine outperformed Engelmann spruce in one forest, while red oak proved more resistant than red maple in the other. This shows that the thermal cameras can help assess how different trees resist drought conditions. This thermal camera technique has the potential to become a valuable tool for monitoring forest health as our climate evolves. Key Points: Canopy‐level evapotranspiration derived from thermal cameras agreed well with eddy covariance measurementsCrown temperature measurements facilitated the estimation of individual‐tree transpiration of co‐occurring species using the same approachThe results show interspecific differences in water use and response to drought that align with species traits [ABSTRACT FROM AUTHOR]

Analysis of field level meteorological and biometrical observations implies that year to year weather variations were significantly influencing the growth and development of plant height, number of tillers, dry matter and LAI productions over the new alluvial zone of Gangetic West Bengal. In the field of agriculture, the knowledge of albedo is very much essential for crop-growth monitoring purposes. The present research work aims to study the albedo pattern over rice field. The field experiment was conducted in Kalyani D Block farm, Nadia District, West Bengal. The albedo was measured by using pyranometer over boro (summer) rice field during the crop growing season 2017-18 and 2018-19. The canopy temperature and air temperature were measured simultaneously. This experiment noticed that the values of crop albedo was reached its highest level (8-10%) during the initial crop growing stages, thereafter, it started to decline gradually and attains its lowest level (6%) during flowering stage but again it increases to higher value (8%) at physiological maturity. The leaf area index is greater contributing factor towards the overall reflectivity of crop canopy of crop surface. The soil albedo was recorded at highest level (7-8%) during the initial crop growing stage, thereafter, it declines gradually and attained its lowest level (3-4%) during flowering stage and further it increases to 8% at physiological maturity. The relationship of Crop albedo (%) and soil albedo for different days after transplanting for two consecutive the boro rice seasons in the year 2017-18 and 2018-19 in respect to two age of seedlings and three variety, three spacing also worked out. [ABSTRACT FROM AUTHOR]

Drought stress, which is connected to climate change, is one of the key determinants pertaining to crop yield. The study was to seek investigating the repercussions of moisture stress on drought testing changes in summer soybean [Glycine max (l.) Merrill] genotypes in during of summer 2022. Three irrigation conditions were the primary determinants in a field experiment conducted using a split plot design: irrigation at sowing and seedling stage (I0), irrigation at sowing, seedling stage and 50% flowering stage (I1) and irrigation at sowing, seedling stage, 50% flowering stage and 50% pod development stage (I2), as well as 20 soybean genotypes as secondary determinants. At 50% flowering stage, drought test such as relative leaf water content (RLWC) and canopy temperature were documented, as well as percent reduction on the basis of yield. The outcomes revealed significant differences between genotypes under various irrigation regimes. Relative leaf water content (RLWC) levels decline and Relative leaf water content (RLWC) level rise considerably during irrigation at the sowing and seedling stages (I0), indicating moisture stress while increase the percent reduction on the basis of yield. With greater relative leaf water content (RLWC), minimumcanopy temperature and percent reduction, the genotype KDS-992 was shown to be tolerant of moisture stress, while genotype KDS-1271 was found to be susceptible to it. [ABSTRACT FROM AUTHOR]

Abstract Urban trees are increasingly used by cities for cooling and climate adaptation. However, efforts to increase tree cover across cities have neglected to account for the trees' health and function, which are known to control their associated environmental benefits but have been difficult to assess at scales relevant for management. Here, we use remotely sensed, high resolution canopy temperature as a proxy for tree health and function and evaluate its relation to the built environment across Minneapolis‐St. Paul (MSP) using machine learning analyses. We develop a new index that incorporates information on urban trees' health and function, in addition to their presence. This index, when applied across MSP, suggests that canopy benefits may not be distributed equally even in neighborhoods with similar canopy cover. Furthermore, accounting for tree health and function can yield more effective and equitable benefits by guiding the location and magnitude of intervention for urban tree management.

Summary: Current estimates of temperature effects on plants mostly rely on air temperature, although it can significantly deviate from leaf temperature (Tleaf). To address this, some studies have used canopy temperature (Tcan). However, Tcan fails to capture the fine‐scale variation in Tleaf among leaves and species in diverse canopies.We used infrared radiometers to study Tleaf and Tcan and how they deviate from air temperature (ΔTleaf and ΔTcan) in multispecies tropical tree plantations at three sites along an elevation and temperature gradient in Rwanda.Our results showed high Tleaf (up to c. 50°C) and ΔTleaf (on average 8–10°C and up to c. 20°C) of sun‐exposed leaves during 10:00 h–15:00 h, being close to or exceeding photosynthetic heat tolerance thresholds. These values greatly exceeded simultaneously measured values of Tcan and ΔTcan, respectively, leading to strongly overestimated leaf thermal safety margins if basing those on Tcan data. Stomatal conductance and leaf size affected Tleaf and Tcan in line with their expected influences on leaf energy balance.Our findings highlight the importance of leaf traits for leaf thermoregulation and show that monitoring Tcan is not enough to capture the peak temperatures and heat stress experienced by individual leaves of different species in tropical forest canopies. [ABSTRACT FROM AUTHOR]

Upland cotton (Gossypium hirsutum L.) is increasingly being managed under subsurface drip irrigation (SDI) in the semiarid Texas High Plains (THP). Scheduling irrigation using a thermally based crop water stress index (CWSI) has the potential to overcome limitations of soil water-based methods and facilitate efficient use of water. The objectives of this study were to develop a CWSI calculation procedure using stability correction, determine an appropriate window for averaging CWSI during daytime hours, compare CWSI with soil water-based indicators of crop water stress, and evaluate methods for estimating crop evapotranspiration (ET) using measured canopy temperatures. Infrared thermometer measurements of canopy temperature and corresponding cotton water use derived from soil water measurements were acquired under two irrigation levels (100% and 33%) under SDI during three growing seasons. A theoretical approach was used to calculate the CWSI using the Businger-Dyer stability correction. Basing daily CWSI on short 1- or 2-h periods in the afternoon overestimated crop water stress. In contrast, CWSI averaged during daytime periods with 0.25-h solar radiation and air temperature exceeding 0.3 MJ m-2 and 24°C, respectively, was strongly correlated (R2=0.76) with the soil water depletion-based stress coefficient Ks with a plausible lower canopy resistance of 25 s m-1. The CWSI was weakly correlated (R2=0.48) to the fraction of plant available water, with the CWSI exhibiting the greater increase of these two indices in response to irrigation events. Using the proposed CWSI scaling at different locations for canopies with dissimilar cover fractions yielded satisfactory estimates of crop ET (RMSE=0.74 mm d-1) compared with soil water balance-calculated ET (ETswb). When summed over weekly intervals, energy balance predictions of 0.25-h crop transpiration inferred from canopy temperature measurements had an acceptable agreement with ETswb (RMSE=0.92 mm d-1). Employing the CWSI to trigger irrigation will require targeted field studies to evaluate thresholds and strategies to optimize water management. [ABSTRACT FROM AUTHOR]

A field experiment was caried out over a period of two years (2022-23 and 2023-24) at Lovely Professional University, Phagwara, Punjab with eight irrigation treatments (based on PSI, soil moisture depletion & critical growth stages) and four replications in RBD Design. The different irrigation levels had an impact on plant growth, parameters contributing to yield, grain and straw production, as well as irrigation water use efficiency (IWUE). Among all the PSI based irrigation treatments, schedule irrigation at 0.50 PSI was found the best irrigation level for growing wheat with significant grain yield (5.67 t ha-1), IWUE (0.092 t ha-1 cm) and gave 11.16% water saving over I50% FC (irrigation as per farmer practices). To schedule irrigation as per the soil moisture depletion approach, irrigation levels I50% FC and I75% FC result in maximum grain yield over PSI & critical growth stage-based irrigation treatments, but this practice does not support sustainable wheat production in water-scarce regions. Therefore, irrigation can be tailored for wheat crops based on 0.5 PSI in water-scarce and water-abundant regions of Punjab. [ABSTRACT FROM AUTHOR]

There is growing interest in using canopy temperature (Tc), including crop water Stress index (CWSI), for irrigation management. However, Tc varies greatly in one day, while soil water content (SWC) varies little, which may lead to different conclusions on whether irrigation is needed based on CWSI at different times. For this end, Tc of winter wheat was continuously monitored, and the data of such environmental factors as atmospheric temperature and soil water content (SWC) were simultaneously collected. CWSI was calculated based on empirical formulation and Tc and CWSI were generalized based on the normalization formulation. The correlation SWC between Tc and CWSI before and after generalization was compared and error analysis was based on SWC theoretical formula. The results showed: (1) the accuracy of SWC retrieval by Tc and CWSI increased firstly and then decreased with time during the day. The optimal time for Tc monitoring SWC was between 10:00 ~ 16:00 (R2 > 0.72) and the optimal time for CWSI monitoring SWC was between 9:00 ~ 18:00 (R2 > 0.69). (2) CWSI and Tc were mapped based on the relationship between crop water stress and soil water deficit and normalized canopy temperature expressions characterized the relationship between crop water stress and soil water deficit. (3) The accuracy of inversion of SWC by mapping Tc from 18:00 ~ 8:00 is increased from 0.5 ~ 0.6 to 0.7 ~ 0.8; the accuracy of soil water content inversion by mapping CWSI from 18:00 ~ 8:00 was improved from 0.2 ~ 0.4 to 0.4 ~ 0.6. (4) The theoretical expression of SWC deduced based on CWSI also proves that considering the relationship between crop water stress and soil water deficit change can effectively reduce the relative error from 30 to 5% in the morning and evening. This study contributes to the understanding of the reason why the correlation between Tc and SWC varies greatly during the day and solves the time-limited problem of thermal infrared remote sensing monitoring of crop water stress. [ABSTRACT FROM AUTHOR]

Heatwaves and soil droughts are increasing in frequency and intensity, leading many tree species to exceed their thermal thresholds, and driving wide‐scale forest mortality. Therefore, investigating heat tolerance and canopy temperature regulation mechanisms is essential to understanding and predicting tree vulnerability to hot droughts. We measured the diurnal and seasonal variation in leaf water potential (Ψ), gas exchange (photosynthesis Anet and stomatal conductance gs), canopy temperature (Tcan), and heat tolerance (leaf critical temperature Tcrit and thermal safety margins TSM, i.e., the difference between maximum Tcan and Tcrit) in three oak species in forests along a latitudinal gradient (Quercus petraea in Switzerland, Quercus ilex in France, and Quercus coccifera in Spain) throughout the growing season. Gas exchange and Ψ of all species were strongly reduced by increased air temperature (Tair) and soil drying, resulting in stomatal closure and inhibition of photosynthesis in Q. ilex and Q. coccifera when Tair surpassed 30°C and soil moisture dropped below 14%. Across all seasons, Tcan was mainly above Tair but increased strongly (up to 10°C > Tair) when Anet was null or negative. Although trees endured extreme Tair (up to 42°C), positive TSM were maintained during the growing season due to high Tcrit in all species (average Tcrit of 54.7°C) and possibly stomatal decoupling (i.e., Anet ≤0 while gs >0). Indeed, Q. ilex and Q. coccifera trees maintained low but positive gs (despite null Anet), decreasing Ψ passed embolism thresholds. This may have prevented Tcan from rising above Tcrit during extreme heat. Overall, our work highlighted that the mechanisms behind heat tolerance and leaf temperature regulation in oak trees include a combination of high evaporative cooling, large heat tolerance limits, and stomatal decoupling. These processes must be considered to accurately predict plant damages, survival, and mortality during extreme heatwaves. [ABSTRACT FROM AUTHOR]

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In recent years, precision agriculture has seen a substantial increase in the use of unmanned aerial vehicles (UAVs). They have shown great potential in spraying, nutrient application, irrigation scheduling, field mapping, yield estimation, and crop monitoring. UAV-enabled approaches have transformed several industries, and they have enormous potential for irrigation water management and characterization of water reservoirs. This paper explores the use of UAVs for variable rate irrigation (VRI) which provides tailored irrigation based on crop water demand, weather conditions, and soil moisture levels using the indices viz canopy temperature, crop water stress index (CWSI), crop evapotranspiration, etc. UAV-VRI provides customized irrigation which increases crop yield and reduces total water uses by improving the water use efficiency. It further enables sustainable water resources management, particularly in water-scarce areas. UAVs offer versatile applications including mapping water quality, vegetation, and bathymetry of aquatic bodies such as lakes and reservoirs. The review highlights the advantages of UAVs over conventional techniques, including a cost-effective, high spatial and temporal resolution, frequent revisit time for irrigation scheduling and monitoring of water bodies which provide useful information for water resource managers and environmental researchers. However, It also discusses the challenges associated with UAVs such as legal issues, data processing, and the need for trained personnel. The massive amounts of data gathered by UAVs may be processed and analyzed using machine learning algorithms, enabling more effective and precise water management. The ongoing advancements in UAVs and machine learning ensure its potential for sustainable water resources management.

【Objective】 Change in soil water content is not only an indicator of water stresses used for irrigation management but also controls biogeochemical processes in soil. In this paper, we study the feasibility of using thermal infrared imaging to estimate soil moisture dynamics. 【Method】 The experiment was conducted in July-August 2023 in a walnut orchard in Xinjiang. Thermal infrared images of the walnut canopy were measured continuously using a thermal infrared camera. Based on the HSV color space of the images, an improved K-means segmentation algorithm was proposed to analyze the change in canopy temperature. We also measured air temperature and humidity, illuminance, wind speed, atmospheric CO2, and soil water content in the 0-80 cm soil layer, from which we proposed an inversion model to estimate soil water dynamics. 【Result】 The improved K-means algorithm increased the accuracy from 82.34% to 94.55%, and the errors between the canopy temperature acquired from the images and the measured canopy temperature were in the range of 0 to 1.0. The infrared imaging method was most accurate between14:00 pm to 16:00 pm. Our results showed that the walnut roots were most active in taking up water from the 40-60 cm soil layer 50-60 cm away horizons from the tree truck. Canopy temperature, air temperature and relative humidity, and atmospheric CO2 concentration were correlated with soil water content at significant levels; they can thus be used to estimate soil water dynamics, with a coefficient of determination of R2=0.86 and p

As an important physiological indicator, wheat canopy temperature (CT) can be observed after flowering in an attempt to predict wheat yield and quality. However, the relationship between CT and wheat yield and quality is not clear. In this study, the CT, photosynthetic rate (Pn), filling rate, wheat yield, and wheat quality of 68 wheat lines were measured, in an attempt to establish a connection between CT and yield and quality and accelerate the selection of new varieties. This experiment used an infrared imaging camera to measure the CT of wheat materials planted in the field in 2022. Twenty materials with significant temperature differences were selected for planting in 2023. By comparing the temperature trends in 2022 and 2023, it is believed that materials 4 and 13 were cold-type materials, while materials 3 and 11 were warm-type materials. The main grain filling period of cold-type materials occurs in the middle and late stages of the grain filling period and the Pn and the thousand-grain weights of cold-type materials were higher than those of warm-type materials. Similarly, under continuous rainy conditions, cold-type materials had a higher protein and wet gluten contents, while warm-type materials had higher sedimentation values and shorter formation times.

The present study aimed to examine the relationship between canopy air temperature difference and vapor pressure deficit (VPD) in wheat crops under normal or nonstressfull conditions. The treatments were undertaken on five plots, having randomized block design (RBD), each maintained at different levels of soil moisture having full irrigation; no irrigation; and 10%, 30%, and 50% soil moisture. Then canopy air temperature difference was regressed against VPD to generate non-water stress and maximum water stress baselines, and the crop water stress index (CWSI) was computed using empirical approach-baseline methods at different soil moisture deficits. It was found that irrigation treatment at 30% soil moisture deficit yielded the maximum water use efficiency. The canopy air temperature difference and VPD resulted in linear relationships, and the slope (m) and intercept (c) for lower baseline of preheading and postheading stages of wheat crop were found as m=−2.371 , c=−1.659 ; and m=−1.8952 , c=−2.32 , for the crop season of 2018–2019. Similarly, the non-water stress baseline equation in the season of 2019–2020 had m=−1.7184 , c=−2.3009 ; and m=−1.8137 , c=−1.9176 for preflowering and postflowering stages of wheat, respectively. The CWSI was determined by using the developed empirical equations for three irrigation schedules of different maximum allowable depletion (MAD) of available soil water (ASW). The developed CWSI may have the potential to improve irrigation scheduling of wheat in India. The study shows practical applications for enhancing wheat cultivation under varying soil moisture conditions. First, it recommends irrigating at 30% soil moisture deficit to maximize water use efficiency, aiding farmers in balancing crop yield and water conservation. Second, established relationships between canopy air temperature difference and VPD allow for the assessment of water stress. By utilizing regression equations, farmers can estimate the CWSI across soil moisture levels, guiding irrigation scheduling during critical growth stages. Third, the developed empirical equations enable real-time prediction of water stress. Monitoring the canopy air temperature difference and VPD offers insights into plant health, helping with informed decisions on irrigation and fertilization. Last, the findings are relevant for water-scarce regions like India, where tailored CWSI equations can be integrated into irrigation systems, promoting sustainable practices under a changing climate. This study may help farmers with practical tools for water-efficient wheat cultivation, fostering informed choices for sustainable agriculture, particularly in water-scarce regions. [ABSTRACT FROM AUTHOR]

Aims: Quantitative characterization of the time-lag effect between canopy temperature and atmospheric temperature and its controlling factors in the agricultural ecosystem may contribute to a higher inversion accuracy of soil water content using canopy-air temperature information. Methods: Tc of winter wheat were continuously monitored, and the data of such environmental factors as solar radiation (Rs), atmospheric temperature (Ta), relative humidity (RH) and soil water content (SWC) were simultaneously collected. Results: Hysteresis existed between Tc and Ta over the diel cycles, and different weather and irrigation levels did not change the direction of the time lag loop. the key driver regulating the diel hysteresis pattern between Tc and Ta varied under different weather: on rainy days, key driver was Rs while on cloudy and sunny days, the key driver was RH. the multiple regression model indicated that together Rs, Ta, RH, and SWC explained 58 ± 10% of the variation of time-lag effect. Path analysis showed on rainy days the key driver (Rs and RH) could enhance the time-lag effect through other indirect factors (Ta and SWC); on cloud days the key driver (RH and SWC) could inhibit the time-lag effect through other indirect factors (Ta); On sunny days this mutual inhibition was further significant. Conclusions: These findings indicated a dynamic process of time-lag effect between Tc and Ta with different weather and different irrigation levels. This study contributes to the understanding of the time-lag effect and its driving factors and this analysis provides the basis for further improvement in monitoring crop water deficit. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Remote Sensing is the property of Editorial Office of Journal of Remote Sensing & Science Publishing Co. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Penstemon, with more than 250 species native to North America, holds significant aesthetic and ecological value in Utah, supporting diverse pollinators. Despite their significance, the survival of penstemon is threatened by challenges such as habitat loss, climate change, and Utah’s naturally high soil salinity. To address these challenges and understand their adaptability, this study evaluated the salt tolerance of two penstemon species [Penstemon davidsonii (Davidson’s penstemon) and Penstemon heterophyllus (foothill penstemon)] under controlled greenhouse conditions. The aim was to develop baseline information for nursery production and landscape use that utilize reclaimed water for irrigation. Plants were irrigated weekly with a nutrient solution at an electrical conductivity (EC) of 1.0 dS·m-1 as control or a saline solution at an EC of 2.5, 5.0, 7.5, or 10.0 dS·m-1 for 8 weeks. Half of the plants were harvested after four irrigation events, and the remaining plants were harvested after eight irrigation events. At harvest, visual rating (0 = dead and 5 = excellent without foliage salt damage), plant width, number of shoots, leaf area, shoot dry weight, leaf greenness [Soil Plant Analysis Development (SPAD)], stomatal conductance, and canopy temperature were collected to assess the impact of salinity stress. In both species, salt damage was dependent on the salinity levels and length of exposure. After four irrigation events, both species exhibited foliage damage that increased in severity with rising EC. The most severe damage was observed in plants receiving saline solution at an EC of 10.0 dS·m-1. After eight irrigation events, P. davidsonii exposed to a saline solution with an EC of 10.0 dS·m-1 received a visual rating of 0, whereas P. heterophyllus had a visual rating of 0.4. Both species exhibited salinity-induced effects, with variations observed in the specific parameters and the degree of response. Penstemon davidsonii exhibited significant salinity stress, as indicated by reduced leaf area, shoot dry weight, SPAD reading, and stomatal conductance with increasing EC of the saline solution. In addition, in both species, at both harvests, canopy temperatures increased either linearly or quadratically by 8% to 36% as the EC levels of the saline solution increased. These results indicate that P. davidsonii was more sensitive to salinity stress than P. heterophyllus. [ABSTRACT FROM AUTHOR]

Canopy temperature provides valuable information for efficient irrigation management and for detecting drought injury in a fast and non-destructive way. It also helps quantify the trade-offs between water conservation and the cooling benefit of the irrigated urban landscape, a critical issue in semiarid inland southern California with limited available water resources. Two adjacent hybrid bermudagrass and tall fescue irrigation trials were conducted to determine canopy temperature changes under a wide range of irrigation treatments from 2017 to 2019 in Riverside, California, USA. The canopy temperature data were also used to develop an empirical crop water stress index (CWSI) for each species. The CWSI values ranged from -0.15 to 0.71 for tall fescue and from -0.28 to 0.54 for hybrid bermudagrass. We observed a moderate correlation between visual rating scores (VR) and CWSI values for tall fescue (r = -0.68) and hybrid bermudagrass (r = -0.61). The fitted linear regression between VR and CWSI data suggested CWSI thresholds close to zero for both species to maintain their acceptable visual quality. The irrigation level consistently showed a significant effect on canopy temperature for both species. On average, a 10% decrease in irrigation application increased the canopy temperature of tall fescue and hybrid bermudagrass by 1.3°C and 0.9°C, respectively. Therefore, deficit irrigation might reduce the cooling benefits of irrigated urban lawns in the semiarid climate of inland southern California. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Drainage & Irrigation Machinery Engineering / Paiguan Jixie Gongcheng Xuebao is the property of Editorial Department of Drainage & Irrigation Machinery Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Tropospheric ozone (O3 ) has often formed in the emission of volatile organic compounds and nitrogen oxides from human activities. The elevated O3 concentration can seriously reduce the photosynthetic rate of wheat in the late grain-filling stage. The resulting loss of wheat yield can then threaten the food security and the carbon-water cycle of farmland ecosystems. Particularly, there is a closely coupled relationship between grain yield and field water use of wheat. Taking the Nongmai 88 variety as the research object, this study aims to investigate the impacts of elevated O3 on farmland water and heat flux in the wheat field. The response of wheat field transpiration to elevated O3 concentrations was also determined using free air ozone concentration enrichment system (O3 -FACE) simulation. The field microclimate was continuously monitored on AA (ambient air) and E-O3 (1.5 × ambient O3 concentration) in O3 -FACE. There was a great variation in the water and heat flux at different stages of wheat growth under elevated O3, according to the residual energy balance. The results show that latent heat flux was an important energy consumption item of wheat farmland ecosystem, accounting for 61.65%(AA) and 63.77%(E-O3 ) of energy expenditure, respectively. Sensible heat flux and soil heat flux accounted for 24.50%(AA), 21.07%(E-O3 ) and 13.95% (AA), 15.20%(E-O3 ), respectively.In terms of diurnal variation, net radiation, soil heat flux, both sensible and latent heat flux shared the "n" type unimodal trends, reaching the maximum at noon. The net radiation increased gradually during the wheat growing season. Whereas, the latent heat flux showed a trend of first increasing and then decreasing. The sensible heat flux was opposite to the latent one, indicating the trend of first decreasing and then increasing. The latent heat flux decreased in the senescent leaf, while the sensible heat flux increased rapidly. There was no significant effect of elevated O3 on the net radiation, soil heat flux, sensible and latent heat flux, as well as their energy distribution from the wheat jointing to the milk maturity stage. The elevated O3 also accelerated the senescence of wheat leaf in the period from milk ripening to ripening, leading to a reduction in the chlorophyll content. There was a great decrease in the mean and peak value of latent heat flux and evapotranspiration. However, the elevated O3 had no significant effect on evapotranspiration, grain yield and water use efficiency. As such, excellent O3 resistance was achieved to cultivate this variety under the elevated O3, especially for the high grain yield and water use efficiency in the wheat field. This finding can provide new evidence to evaluate the water and heat flux of winter wheat farmland, in order to simulate the farmland water use and grain yield under elevated O3 and variety replacement. [ABSTRACT FROM AUTHOR]

Introduction Rice is one of the most important agricultural products in the world, and it has the second place in terms of annual production after wheat. Cultivation of rice in most regions of the world is done in the form of transplanting, but the long period of preparing transplant and sometimes high mortality of transplants in the main field, high water consumption, the impossibility of direct use of transplanting machines in heavy soil textures and high labor costs have caused it is an undeniable necessity to find suitable methods of planting rice with the aim of reducing the inhibiting effects of these factors especially reducing water consumption and achieving optimal performance. On the other hand, choosing the suitable planting date is another important agricultural management to achieve optimal crop performance. In this experiment, the effect of different land preparation (planting bed) methods and different transplanting dates were investigated on the physiological characteristics and yield of three rice varieties in Shavor region, Khuzestan province, Iran. The purpose of this experiment was to determine the role of planting date and planting bed on the growth and development aspects of rice transplants and their interations on reducing the inhibiting effects of production factors. Material and methods This experiment was carried out in the form of split split plots based on randomized complete block design with three replications in the research field of Shavor Research Station, Khuzestan province, Iran, in 2021 and 2022. The experimental factors were land preparation (planting bed) methods in four levels including puddling, flat with field capacity, flat with dry soil and raised bed in the ridge with dry soil as the main factor, transplanting date in three levels including 2, 12 and 23 June as the sub-factor, and rice variety in three levels including Champa, Anbori Germez Paboland and Daniyal as the sub-sub-factor. To prepare the planting beds (puddling, flat with field capacity and flat with dry soil), the soil was leveled by leveler after plowing and disking, and to prepare the raised bed in the ridge, the ridges (with a width of 50 cm and a height of 20 cm) were created by a ditcher after plowing, disking and leveling. The measured traits in this study were paddy yield, biological yield, harvest index, chlorophyll index, canopy temperature and stomatal conductance. Research findings The results of combined analysis of variance showed that the effect of planting bed, planting date and variety as well as their interactions on rice yield were statistically significant. The results of the comparison of two years means showed that the highest grain yield was belonged to flat bed with dry soil on the planting date of 2 June in Anbori Germez Paboland variety (5.68 ton.ha-1), and the highest biological yield was obtained from the flat bed with field capacity on the planting date of 23 June in Anbori Germez Paboland variety (13.63 ton.ha-1). Also, the highest harvest index (51.71 %) and the best canopy temperature at the stage of panicle emergence (32.22 °C) was observed in the treatment of flat bed with dry soil on the planting date of 23 June in Champa variety. Conclusion According to the results of grain yield as the most important goal of rice planting, it seems that by cultivation of the local variety “Anbori Germez Paboland” on the flat bed at 2 June through the provision of environmental conditions (non-implementation of puddling and preventing negative effects on plant growth), and a suitable temperature (preventing the occurrence of stress in the flowering and seeding stage), can obtain a high grain yield. [ABSTRACT FROM AUTHOR]

Drought is the most important factor limiting winter wheat yield in the North China Plain (NCP). Choosing high-yielding cultivars is an important measure to minimize the negative effects of drought stress. Field studies were conducted with 10 cultivars in the 2020–2022 seasons under three irrigation treatments (I0, without irrigation; I1, irrigated at jointing stage; I2, irrigated at jointing and anthesis stages) in the NCP to examine the water use strategies and root and shoot traits of high-yielding cultivars under different water supply conditions. The results showed that yield variation among cultivars was 21.2–24.6%, 23.7–25.9% and 11.6–15.3% for the I0, I1 and I2 treatments, respectively. Under water deficit conditions (I0 and I1), high-yielding cultivars reduced water use during vegetative stages and increased soil water use during reproductive stages, especially water use from deeper soil layers. Those cultivars with higher root length density (RLD) in deep soil layers exhibited higher water uptake. Each additional millimeter of water used after anthesis from the 100–200 cm soil layers increased grain yield by 23.6–29.6 kg/ha and 16.4–28.5 kg/ha under I0 and I1, respectively. This water use strategy enhanced dry matter accumulation after anthesis, decreased canopy temperature (CT) and increased relative leaf water contents (RLWC), which ultimately improved grain yield. For winter wheat grown under I2, cultivars that decreased water use after anthesis had higher water productivity (WP). Root length (RL), root weight (RW) and root:shoot ratio were each negatively correlated with grain yield, while above-ground biomass was positively correlated with grain yield. Therefore, higher dry matter accumulation and smaller root systems are two important traits of high-yielding cultivars under sufficient water supply conditions (I2) in the NCP. [ABSTRACT FROM AUTHOR]

Crop water stress index (CWSI) has been widely used in soil moisture monitoring. However, the influence of the time lag effect between canopy temperature and air temperature on the accuracy of soil moisture monitoring with different CWSI models has not been further investigated. Therefore, based on the continuous record of canopy temperature and air temperature, this study explored the influence of canopy-air temperature hysteresis on the diagnosis of soil moisture with three CWSI models (CWSIT—theoretical, CWSIE—empirical, CWSIH—hybrid). The results show (1) the peak time of canopy temperature was ahead of that of air temperature, and the lag time varied under different soil moisture conditions. When the soil moisture was seriously deficient, the lag time decreased. However, from jointing-heading period to filling-ripening period, the lag time became longer. (2) The values of CWSIT, CWSIE, and CWSIH decreased when the time lag effect was considered. In jointing-heading period, heading-filling period, and filling-ripening period, CWSIT had the highest accuracy in soil moisture monitoring without the consideration of the time lag effect. When the time lag effect was considered, the monitoring accuracy of CWSIE and CWSIH was greatly improved and higher than that of CWSIT, while that of CWSIT was reduced. The findings provided a basis for further improving the accuracy of soil moisture monitoring with CWSI models. [ABSTRACT FROM AUTHOR]

Pre-exposure of plants to moderate stress may create a "stress memory" that enables a fast protective response to next stress event. Protocols to differentiate the crop genotypes for such traits are essential for genetic improvement of plant stress tolerance. We hypothesized that memory due to soil moisture deficit may get reflected in leaf canopy temperature responses to fluctuating ambient temperature. We conducted a factorial completely randomized block design experiment with two treatments: well-watered (WW) and water deficit stress (WS) in three and two popular cultivars of sugarcane and sorghum, respectively, with eight replications. The 30 and 15 days old plants of sugarcane and sorghum were exposed to soil moisture deficit for 25 and 10 days, respectively, followed by their recovery. For differentiating the response of plants after stress recovery (ASR), the WW and WS plants were labelled as WWASR and WSASR, respectively. After 30 days of recovery, canopy temperature responses to ambient temperature fluctuations were monitored. Warming of the canopy was faster in WSASR as compared to WWASR plants. Further, there was a difference within the WSASR cultivars, indicating the existence of genetic variation in recalling and responding to desiccation caused by increasing ambient temperature. These indicated that water exhaustive and non-exhaustive C4 plants differ in their adaptive mechanisms associated with transpirational cooling of the plant canopy. The pixel-wise analysis of thermal images of plants provided a more effective differentiation of stress responses among sugarcane and sorghum cultivars compared to the conventional method of recording canopy temperature. The existence of cultivar differences suggests that the trait representing stress memory can be phenotyped with protocols optimized with the IR imaging system and may serve as a promising tool for phenotyping crop stress tolerance. [ABSTRACT FROM AUTHOR]

A field experiment was caried out over a period of two years (2022-23 and 2023-24) at Lovely Professional University, Phagwara, Punjab with eight irrigation treatments (based on PSI, soil moisture depletion & critical growth stages) and four replications in RBD Design. The different irrigation levels had an impact on plant growth, parameters contributing to yield, grain and straw production, as well as irrigation water use efficiency (IWUE). Among all the PSI based irrigation treatments, schedule irrigation at 0.50 PSI was found the best irrigation level for growing wheat with significant grain yield (5.67 t ha-1), IWUE (0.092 t ha-1 cm) and gave 11.16% water saving over I50% FC (irrigation as per farmer practices). To schedule irrigation as per the soil moisture depletion approach, irrigation levels I50% FC and I75% FC result in maximum grain yield over PSI & critical growth stage-based irrigation treatments, but this practice does not support sustainable wheat production in water-scarce regions. Therefore, irrigation can be tailored for wheat crops based on 0.5 PSI in water-scarce and water-abundant regions of Punjab.

A thorough understanding of how crops respond to water stress is essential for effective irrigation management under changing climate conditions and declining water resources. Amongst the various methods of irrigation, crop water stress index (CWSI)-based irrigation is popular due to its non-invasive techniques that require less data and can precisely indicate the severity of crop water deficiency. The present study focuses on establishing the upper- and lower-baselines of canopy-air temperature difference (Tc-Ta) for the estimation of the CWSI and to determine the CWSI threshold for maize and wheat crops. The upper- and lower-baseline of (Tc-Ta) was established using the relationship between (Tc-Ta) and vapor pressure deficit (VPD) for different irrigation treatments such as 60 %ETc, 70 %ETc, 80 %ETc, 90 %ETc, and 100 %ETc with irrigation interval of 1-day, 2-days, and 3-days. The study showed that the baselines varied with the growth stages of the crop and with irrigation treatments and reached the maximum in Anthesis and Silking growth stage for wheat and maize, respectively. The threshold of CWSI was estimated by developing a relationship between the normalized values of grain yield (GY) and irrigation water productivity (WPI). For the Rabi wheat, a quadratic correlation was identified between CWSI and WPI (r2 = 0.89), and GY (r2 = 0.93). Similarly, for Kharif maize, a quadratic relationship was noted between CWSI and both WPI (r2 = 0.75) and GY (r2 = 0.85). From the study, it was found that the CWSI thresholds of Rabi wheat and Kharif maize are 0.29 and 0.31, respectively. Based on the study, it can be concluded that by utilizing the thresholds for a winter wheat-summer maize cropping system, high GY and WPI can be achieved.