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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]

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]

The monitoring of canopy temperature (Tc) helps to establish appropriate watering methods. This study calculates the crop water stress index (CWSI) for four irrigation regimes in semi-arid region, India. Plots 1, 2, 3, and 4 had soil moisture depletion of 50% (drip system), 25% (drip system), unregulated (farmer replicated flood system), and 50% (flood system) with irrigation. In this work, we examined the value of employing a portable infrared thermometer (IRT) to measure wheat canopy temperature (Tc) at two geographical locations. The IRT field of view is 51.28–5,128 cm2, or 10–100 cm from the canopy crown. The field of view change from 10 to 100 cm affects Tc and CWSI in the four irrigation treatments, ranging from 0.65 to 2.71% and 9.2 to 36.4%, respectively. The research found that increasing the IRT from 10 to 100 cm reduced slope by 5.7% and intercept by 20.6% in lower baselines. The R2 for CWSI and soil moisture was 0.78 (10 cm) and 0.77 (100 cm). Drip-irrigated plots are more sensitive to IRT spatial resolution than flood-irrigated plots. The findings suggest that CWSI studies may benefit from specific sample methods for Tc evaluation. HIGHLIGHTS Drip-irrigated (DI) plots give lesser CWSI as compared to flood-irrigated (FI) plots.; DI plots are more sensitive to the location of the infrared thermometer (IRT) than FI plots.; The highest change in canopy temperature (Tc) and CWSI was observed in the most frequently irrigated DI plot.; The work highlights the impact of change in the field of view of IRT on Tc, lower baselines, and CWSI.; Relationship between CWSI and soil moisture studied.;

Background: Wheat is an important food crop of world. This crop has the wider adaptability due to its genetic makeup. The sowing environment and varieties interaction plays important role to enhance its productivity and optimum utilization of the resources. As this crop has wider adaptability so we planned our experiment to study the grain yield, heat use and water use efficiency of diverse wheat varieties which have been recommended in different wheat growing zones, sown at different environment in North-western India, to increase the varietal spectrum. Methods: The field experiment was conducted in 2017-18 and 2018-19 at the research farm of the Punjab Agricultural University, Ludhiana, India. The experiment was conducted with four sowing dates (November 5, November 25, December 15 and January 5) in main plot and six wheat varieties (HS 562, HD 2967, HD 3086, HI 1544, MACS 6222 and WR 544) in sub-plot of split plot design with three replications. Result: The wheat crop sown on November 5 recorded the highest emergence count, plant height, heat use efficiency, normalized difference vegetative index, yield attributes, grain yield and water use efficiency than later sowing dates. Among the wheat varieties, HS 562 recommended for northern hill zone recorded heat use efficiency, helio-thermal use efficiency, at leaf value, effective tillers, grains per earhead, grain yield and water use efficiency similar to HD 3086 recommended for North-western zone. The varieties recommended for other zones like HI 1544, MACS 6222 and WR 544 could not perform similar to the HD 3086. [ABSTRACT FROM AUTHOR]

Genetic diversity plays an important function in the improvement of germplasm which has a direct association with the crop productivity. A number of statistical methods have been employed to investigate genetic diversity among the genotypes of various crops. Approaches like principal component and cluster analysis are useful and most frequently used for identifying plant characters individually and assisting breeders in genetically enhancing attributes in wheat genotypes. This research was carried out at the experimental field of On-farm Research Division (OFRD), Bangladesh Agricultural Research Institute (BARI), Shyampur, Rajshahi, Bangladesh, to study the genetic diversity and selection of high yielding wheat genotypes with their important agronomic and physiological traits among studied genotypes in drought condition by using principal component and cluster analyses. A total of 70 bread wheat genotypes were evaluated in 7 × 10 alpha lattice design in non-irrigated drought conditions during 2018-2019 cropping season. The first four principal components (PCs) with eigen values greater than 1.0 accounting for 82.81% of the total observed variation among genotypes. Traits with maximum values in PC1 were spikes m-2 (SPM), thousand grain weight (TGW), ground coverage (GC), normalized difference vegetation index (NDVI), grain yield (GY), biomass (BM), and harvest index (HI) while PC2 comprised heading days (HD) and BM. The major contributors to PC3 were grains spike-1 (GPS) and GC, whereas the maximum value of trait in PC4 was in relative leaf water content (RWC). The principal component biplot selected 21 high yielding genotypes than the average yield as they were distributed on the positive side of the PC1. The cluster analysis grouped 70 genotypes into six diverse clusters. Cluster Ⅱ containing same 21 genotypes previously selected by principal component biplot provided the highest SPM (257.4), GPS (42.2), TGW (40.51 g), GC (0.27), NDVI(0.73), SPAD (44.24), RWC (88.33%), grain yield (3216kg ha-1), BM (8535 Kg ha-1) and HI (0.37) belonging to the lowest canopy temperature at vegetative stage (16.14˚C) and canopy temperature at grain filling stage (24.64˚C) and moderate HD (71.65 days). Based on the results of the current study the best genotypes can be used as important breeding materials in upcoming breeding schemes for drought tolerance. [Fundam Appl Agric 2023; 8(1.000): 435-446]

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Canopy temperature (CT) is considered a reliable proxy for stomatal conductance. Low CT values of plant canopies under water-limited conditions are associated with high transpiration indicating plants' drought tolerance. Many U.S. Pacific Northwest (PNW) adapted wheat (Triticum aestivum L.) cultivars lack stress-adaptive traits resulting in poor performance in drought environments. This study aims to identify the stress-adaptive traits by evaluating the CT in spring wheat populations across different soil moisture conditions in the PNW. An infrared thermometer was used to estimate the CT in two families of recombinant inbred lines, 'Alpowa' × 'Express' (AE population) and 'Hollis' × 'Drysdale' (HD population), in rainfed and irrigated environments of the dryland PNW in 2011 to 2013. Higher reductions in grain yield up to 170%, spike length up to 25%, and spikelets spike−1 up to 19% were observed in a rainfed environment compared to the reductions in an irrigated environment. A significant variation in CT was observed in both AE and HD populations. With 1 °C increase in CT at the anthesis stage, grain yield was lowered up to 38 g m−2. Low CT was associated with high grain yield and agronomic traits in both wheat populations (r = − 0.18 to − 0.55, P ≤ 0.05). The highest association between CT and grain yield was observed at anthesis (r = − 0.47) and milking (r = − 0.38) stages (P ≤ 0.001). Our results show that screening for low CT during terminal wheat growth stage is an effective strategy for improving the selection of new drought-tolerant wheat varieties in the PNW. [ABSTRACT FROM AUTHOR]

The Crop Water Stress Index (CWSI) is a useful tool for evaluating irrigation scheduling and achieving water conservation and crop yield goals. This study examined the CWSI under different water stress conditions for the scheduling of wheat crop irrigation and developed indices using the leaf canopy temperature in Faisalabad, Pakistan. The experiments were conducted using a randomized, complete block design and four irrigation treatments with deficit levels of D0%, D20%, and D40% from the field capacity (FC) and D100% (100% deficit level). The CWSI was determined at pre-heading and post-heading stages through the lower baseline (fully watered crop) and upper limit (maximum stress). These baselines were computed using the air temperature and canopy temperature of plant leaves and the vapor pressure deficit (VPD). The CWSI for each irrigation treatment was calculated and the average seasonal CWSI value for the whole season was used to develop the empirical relationships for scheduling irrigation. The relationships between the air canopy temperatures and the VPD resulted in slope (x) = −0.735 and interception (c) = −0.8731 as well as x = −0.5143 and c = −1.273 at the pre- and post-heading stages, respectively. The values of the CWSI for the treatment at deficit levels of D0%, D20%, D40%, and D100% were found to be 0.08, 0.61, 0.20, and 0.64, respectively. The CWSI values developed in this study can be effectively used to promote better the monitoring of irrigated wheat crops in the region. [ABSTRACT FROM AUTHOR]

Developing varieties adapted to dry conditions is one of the biggest targets for breeders. It is important to use inexpensive spectral sensing methods saving time in variety development. The aim of this study was to select bread wheat genotypes having high grain yield by using spectral sensing methods. Twenty-five bread wheat (Triticum aestivum L.) genotypes were evaluated under rainfed condition at three locations in Central Anatolia Region. The experiment was arranged in randomized complete block design with three replications. Grain yield (GY), Canopy Temperature (CT), Soil Plant Analysis Development (SPAD) and Normalized Difference Vegetation Index (NDVI) values were recorded. GY, CT, SPAD and NDVI were found to be statistically significant in terms of both genotype and environment. The relationship between grain yield and NDVI (R²=0.321**) values was linear. The positive correlation of GY (0.5671**) and SPAD (0.1729*) with NDVI suggest that NDVI can be used as efficient and precise selection criteria for identifying high effiency wheat varieties under rainfed conditions. [ABSTRACT FROM AUTHOR]

Background: Recently genomic selection (GS) has emerged as an important tool for plant breeders to select superior genotypes. Multi-trait (MT) prediction model provides an opportunity to improve the predictive ability of expensive and labor-intensive traits. In this study, we assessed the potential use of a MT genomic prediction model by incorporating two physiological traits (canopy temperature, CT and normalized difference vegetation index, NDVI) to predict 5 complex primary traits (harvest index, HI; grain yield, GY; grain number, GN; spike partitioning index, SPI; fruiting efiiciency, FE) using two cross-validation schemes CV1 and CV2. Results: In this study, we evaluated 236 wheat genotypes in two locations in 2 years. The wheat genotypes were genotyped with genotyping by sequencing approach which generated 27,466 SNPs. MT-CV2 (multi-trait cross validation 2) model improved predictive ability by 4.8 to 138.5% compared to ST-CV1(single-trait cross validation 1). However, the predictive ability of MT-CV1 was not significantly different compared to the ST-CV1 model. Conclusions: The study showed that the genomic prediction of complex traits such as HI, GN, and GY can be improved when correlated secondary traits (cheaper and easier phenotyping) are used. MT genomic selection could accelerate breeding cycles and improve genetic gain for complex traits in wheat and other crops. [ABSTRACT FROM AUTHOR]

Deficit irrigation is a common approach in water-scarce regions to balance productivity and water use, whereas drought stress still occurs to various extents, leading to reduced physiological performance and a decrease in yield. Therefore, seeking a rapid and reliable method to identify wheat varieties with drought resistance can help reduce yield loss under water deficit. In this study, we compared ten wheat varieties under three deficit irrigation systems (W0, no irrigation during the growing season; W1, irrigation at jointing; W2, irrigation at jointing and anthesis). UAV thermal imagery, plant physiological traits [leaf area index (LAI), SPAD, photosynthesis (Pn), transpiration (Tr), stomatal conductance (Cn)], biomass and yield were acquired at different growth stages. Wheat drought resistance performance was evaluated through using the canopy temperature extracted from UAV thermal imagery (CT-UAV), in combination with hierarchical cluster analysis (HCA). The CT-UAV of W0 and W1 treatments was significantly higher than in the W2 treatment, with the ranges of 24.8–33.3 °C, 24.3–31.6 °C, and 24.1–28.9 °C in W0, W1 and W2, respectively. We found negative correlations between CT-UAV and LAI, SPAD, Pn, Tr, Cn and biomass under the W0 (R2 = 0.41–0.79) and W1 treatments (R2 = 0.22–0.72), but little relevance for W2 treatment. Under the deficit irrigation treatments (W0 and W1), UAV thermal imagery was less effective before the grain-filling stage in evaluating drought resistance. This study demonstrates the potential of ensuring yield and saving irrigation water by identifying suitable wheat varieties for different water-scarce irrigation scenarios. [ABSTRACT FROM AUTHOR]

Leaf rolling is an important agronomic trait in wheat (Triticum aestivum L.). Moderate leaf rolling keeps leaves upright and maintains the relatively normal photosynthesis of plants under drought stress. However, the molecular mechanism of wheat leaf rolling remains unclear. Here, we identified a candidate gene TaMYB5-3A that regulates leaf rolling by using a genome-wide association study (GWAS) in a panel of 323 wheat accessions. Phenotype analysis indicated that the leaves of tamyb5 mutants were flatter than that of the wild type under drought condition. A nucleotide variation in the TaMYB5-3A coding region resulted in a substitution of Thr to Lys, which corresponds to two alleles SNP-3A-1 and SNP-3A-2. The leaf rolling index (LRI) of the SNP-3A-1 genotype was significantly lower than that of the SNP-3A-2 genotype. In addition, TaMYB5-3A alleles were associated with canopy temperature (CT) in multiple environments. The CT of the SNP-3A-1 genotype was lower than that of the SNP-3A-2 genotype. Gene expression analysis showed that TaMYB5-3A was mainly expressed in leaves and down-regulated by PEG and ABA treatment. TaMYB5 induces TaNRL1 gene expression through the direct binding to the AC cis-acting element of the promoter of the target gene, which was validated by EMSA (electrophoretic mobility shift assay). Our results revealed a crucial molecular mechanism in wheat leaf rolling and provided the theoretical basis and a gene resource for crop breeding. [ABSTRACT FROM AUTHOR]

Nitrogen (N) deficiency and heat stress (HS) are major abiotic stresses that affect the quantity and quality of wheat grains. This study was conducted to examine wheat varietal response to RSI and RNDVI at the anthesis stage and their relationship to yield and yield-related traits under variable N supply and terminal heat stress. Twelve wheat varieties were evaluated in 2016–2017 and 2017–2018 at the National Agricultural Research Centre (NARC), Islamabad, Pakistan. The experiment was divided into three sets, i.e., N120 (120 kg N/ha), N60 (60 kg N/ha) and N0 (0 kg N/ha), based on the nitrogen fertilizer application. The physiological and yield-related parameters were recorded. Mean grain yield for all twelve varieties, averaged from two years of data, ranged between 1655.0 and 3890.1 kg/ha. Maximum RSI (0.99), RNDVI (1.03) and GY (3890.9 kg/ha) were recorded for FSD-08, while AARI-11 showed minimum RSI (0.50), RNDVI (0.56) and GY (1396.40 kg/ha). In the present study, mean CTD was lower, at N0 (3.57 °C), followed by N60 (5.07 °C) and N120 (5.47 °C) on average for the two years of data. The strong positive correlation of RSI and RNDVI with grain yield at R2 = 0.73 and R2 = 0.49 suggest that these parameters can be used as efficient and precise selection criteria for identifying nitrogen-use-efficient wheat varieties under terminal heat-stress conditions. This work will help the researchers to identify and develop nitrogen-use-efficient and thermos-tolerant wheat cultivars by minimizing the negative impacts of heat stress at the anthesis stage. [ABSTRACT FROM AUTHOR]

Canopy temperature (CT) is often related to potential yield and is a possible yield indicator in breeding programs. However, it is difficult to evaluate genetic variations of CT accurately in large-scale investigations, such as breeding programs, because CT is strongly affected by environmental conditions. In this study, to precisely evaluate these genetic variations, we determined the environmental factors that affect CT measurement and proposed a convenient normalization method to minimize their influence. We measured the CT of CT-high or CT-low cultivars in the field under various conditions. We found that as the sun and shade levels were alternated, the CT changed within seconds; the position in the field also critically affected the CT. However, even under these conditions, the differences between cultivars became clearer if CT was normalized by neighboring lines. Additionally, we revealed that CT measurements between 12:00 and 15:00 maximized the difference between cultivars. Using our normalization technique under the favorable conditions specified can help breeders select high-yield lines using CT in breeding programs. [ABSTRACT FROM AUTHOR]

A primary selection target for wheat (Triticum aestivum) improvement is grain yield. However, the selection for yield is limited by the extent of field trials, fluctuating environments, and the time needed to obtain multiyear assessments. Secondary traits such as spectral reflectance and canopy temperature (CT), which can be rapidly measured many times throughout the growing season, are frequently correlated with grain yield and could be used for indirect selection in large populations particularly in earlier generations in the breeding cycle prior to replicated yield testing. While proximal sensing data collection is increasingly implemented with high-throughput platforms that provide powerful and affordable information, efficient and effective use of these data is challenging. The objective of this study was to monitor wheat growth and predict grain yield in wheat breeding trials using high-density proximal sensing measurements under extreme terminal heat stress that is common in Bangladesh. Over five growing seasons, we analyzed normalized difference vegetation index (NDVI) and CT measurements collected in elite breeding lines from the International Maize and Wheat Improvement Center at the Regional Agricultural Research Station, Jamalpur, Bangladesh. We explored several variable reduction and regularization techniques followed by using the combined secondary traits to predict grain yield. Across years, grain yield heritability ranged from 0.30 to 0.72, with variable secondary trait heritability (0.0–0.6), while the correlation between grain yield and secondary traits ranged from −0.5 to 0.5. The prediction accuracy was calculated by a cross-fold validation approach as the correlation between observed and predicted grain yield using univariate and multivariate models. We found that the multivariate models resulted in higher prediction accuracies for grain yield than the univariate models. Stepwise regression performed equal to, or better than, other models in predicting grain yield. When incorporating all secondary traits into the models, we obtained high prediction accuracies (0.58–0.68) across the five growing seasons. Our results show that the optimized phenotypic prediction models can leverage secondary traits to deliver accurate predictions of wheat grain yield, allowing breeding programs to make more robust and rapid selections. [ABSTRACT FROM AUTHOR]

A primary selection target for wheat (Triticum aestivum) improvement is grain yield. However, the selection for yield is limited by the extent of field trials, fluctuating environments, and the time needed to obtain multiyear assessments. Secondary traits such as spectral reflectance and canopy temperature (CT), which can be rapidly measured many times throughout the growing season, are frequently correlated with grain yield and could be used for indirect selection in large populations particularly in earlier generations in the breeding cycle prior to replicated yield testing. While proximal sensing data collection is increasingly implemented with high-throughput platforms that provide powerful and affordable information, efficient and effective use of these data is challenging. The objective of this study was to monitor wheat growth and predict grain yield in wheat breeding trials using high-density proximal sensing measurements under extreme terminal heat stress that is common in Bangladesh. Over five growing seasons, we analyzed normalized difference vegetation index (NDVI) and CT measurements collected in elite breeding lines from the International Maize and Wheat Improvement Center at the Regional Agricultural Research Station, Jamalpur, Bangladesh. We explored several variable reduction and regularization techniques followed by using the combined secondary traits to predict grain yield. Across years, grain yield heritability ranged from 0.30 to 0.72, with variable secondary trait heritability (0.0–0.6), while the correlation between grain yield and secondary traits ranged from −0.5 to 0.5. The prediction accuracy was calculated by a cross-fold validation approach as the correlation between observed and predicted grain yield using univariate and multivariate models. We found that the multivariate models resulted in higher prediction accuracies for grain yield than the univariate models. Stepwise regression performed equal to, or better than, other models in predicting grain yield. When incorporating all secondary traits into the models, we obtained high prediction accuracies (0.58–0.68) across the five growing seasons. Our results show that the optimized phenotypic prediction models can leverage secondary traits to deliver accurate predictions of wheat grain yield, allowing breeding programs to make more robust and rapid selections.

The Crop Water Stress Index (CWSI) is a useful tool for evaluating irrigation scheduling and achieving water conservation and crop yield goals. This study examined the CWSI under different water stress conditions for the scheduling of wheat crop irrigation and developed indices using the leaf canopy temperature in Faisalabad, Pakistan. The experiments were conducted using a randomized, complete block design and four irrigation treatments with deficit levels of D0%, D20%, and D40% from the field capacity (FC) and D100% (100% deficit level). The CWSI was determined at pre-heading and post-heading stages through the lower baseline (fully watered crop) and upper limit (maximum stress). These baselines were computed using the air temperature and canopy temperature of plant leaves and the vapor pressure deficit (VPD). The CWSI for each irrigation treatment was calculated and the average seasonal CWSI value for the whole season was used to develop the empirical relationships for scheduling irrigation. The relationships between the air canopy temperatures and the VPD resulted in slope (x) = −0.735 and interception (c) = −0.8731 as well as x = −0.5143 and c = −1.273 at the pre- and post-heading stages, respectively. The values of the CWSI for the treatment at deficit levels of D0%, D20%, D40%, and D100% were found to be 0.08, 0.61, 0.20, and 0.64, respectively. The CWSI values developed in this study can be effectively used to promote better the monitoring of irrigated wheat crops in the region.

Nitrogen (N) deficiency and heat stress (HS) are major abiotic stresses that affect the quantity and quality of wheat grains. This study was conducted to examine wheat varietal response to RSI and RNDVI at the anthesis stage and their relationship to yield and yield-related traits under variable N supply and terminal heat stress. Twelve wheat varieties were evaluated in 2016–2017 and 2017–2018 at the National Agricultural Research Centre (NARC), Islamabad, Pakistan. The experiment was divided into three sets, i.e., N120 (120 kg N/ha), N60 (60 kg N/ha) and N0 (0 kg N/ha), based on the nitrogen fertilizer application. The physiological and yield-related parameters were recorded. Mean grain yield for all twelve varieties, averaged from two years of data, ranged between 1655.0 and 3890.1 kg/ha. Maximum RSI (0.99), RNDVI (1.03) and GY (3890.9 kg/ha) were recorded for FSD-08, while AARI-11 showed minimum RSI (0.50), RNDVI (0.56) and GY (1396.40 kg/ha). In the present study, mean CTD was lower, at N0 (3.57 °C), followed by N60 (5.07 °C) and N120 (5.47 °C) on average for the two years of data. The strong positive correlation of RSI and RNDVI with grain yield at R2 = 0.73 and R2 = 0.49 suggest that these parameters can be used as efficient and precise selection criteria for identifying nitrogen-use-efficient wheat varieties under terminal heat-stress conditions. This work will help the researchers to identify and develop nitrogen-use-efficient and thermos-tolerant wheat cultivars by minimizing the negative impacts of heat stress at the anthesis stage.

Climate change leads to increase in temperature of wheat growing regions with adverse effects on its yield. Breeding wheat genotypes for high temperature tolerance and yield related characters is a dire need of the day. This study was designed to evaluate eleven accessions of wheat including seven heat tolerant lines and four heat susceptible testers and they were crossed in line into tester mating design. The resultants F1 hybrids and their parents were assessed for heat tolerance in open field and field covered with plastic sheet tunnel (to artificially induce heat stress). At maturity, data were taken on morphological and physiological factors for estimation of genetic variation and combining ability effects. Highly significant variability was detected among genotypes for all studied parameters. Existing genetic variability among genotypes, under natural and heat stress treatments, showed the potential of present breeding material. These entries may be used in future to develop heat tolerant genotypes. Combining ability analysis showed the variable trend of general combining effects between lines and testers, and specific combining effects among combinations. In lines HTSBWON-15-0079, HTSBWON-15-0040 and HTSBWON-15-0089 and testers HTSBWON-15-0014 and Millat-11 were best general combiners in both circumstances. Outcomes of specific combining ability showed that crosses HTSBWON-15-0079 × HTSBWON-15-0014, HTSBWON-15-0079 × Millat-11 and HTSBWON-15-0040 × Millat-11 were best specific combiners for heat related traits like canopy temperature and electrolyte leakage. Non additive type of genetic effect was exhibited by almost all characters. [ABSTRACT FROM AUTHOR]

Sodicity is a major soil constraint in many arid and semi-arid regions worldwide, including Australia, which adversely affects the ability of crops to take up water and nutrients from the soil, reducing yield. Reliable methods and tools are required for appropriate selection of traits, may provide a better understanding of crop responses to multiple stresses, especially in sodic soil. A novel strategy was developed using unmanned aerial vehicle (UAV)-thermal imaging and agglomerative hierarchical clustering-based techniques to evaluate and rank the physiological performance of 18 contrasting wheat genotypes grown on a moderately sodic and a highly sodic soil in north-eastern Australia. We obtained UAV-thermal imaging data at different times of the day (9:30, 12:00, and 15:00 hrs) close to flowering stage. Crop biophysical parameters (Leaf potassium concentration, normalized difference vegetation index, crop water uptake, stomatal conductance, plant moisture content, and aboveground biomass) were measured at close to flowering by destructive plant sampling and ground-based proximal sensing and yield was machine harvested at maturity. Canopy temperatures derived from thermal imagery between 28.9 and 35.4 °C were observed at the moderately sodic site, and between 36.2 and 41.0 °C at the highly sodic site from 9:30 to 15:00 hrs. Canopy temperature was consistently higher than corresponding ambient air temperatures indicating plant water stress at both sites. While the air temperature was not significantly different (p > 0.05) between the two sites, canopy temperature was significantly higher (p < 0.01) on highly sodic soil compared to moderately sodic soil, indicating greater water stress at the highly sodic site. This difference was most likely due to the adverse impacts of sodic soil constraints and not primarily due to environmental variations. Hence, our study revealed that sodic soil constraints can intensify plant water stress. Statistical analysis between canopy temperature (9:30, 12:00, and 15:00 hrs) and crop biophysical parameters showed close negative correlations at both moderately sodic (R2 = 0.54 to 0.83) and highly sodic (R2 = 0.30 to 0.89) sites. A closer correlation was observed at 15:00 hrs for both sites. Thus, high-resolution UAV-thermal imaging has potential to detect water-stressed plants on sodic soil. Agglomerative hierarchical clustering was used as an unsupervised machine learning tool for ranking of physiological performance of wheat genotypes. Results suggest that UAV-thermal imaging and AHC techniques can discriminate cultivars tolerant to sodicity. The study improves our understanding of crop physiological behaviour and can assist farmers in selection of water stress tolerant genotypes to sustain food security in sodic soil under water-limited environments. [ABSTRACT FROM AUTHOR]

This study was conducted to identify physiological and biochemical attributes of wheat genotypes in response to heat stress. In this respect eight wheat genotypes viz., Pavon-76, Prodip, BARI Gom-25, BARI Gom-26, BAW-1143, BAW-1146, BAW-1147 and BAW-118 were used as study materials. The experiment was conducted during 2011-12 and 2012-13. In this experiment, physiological changes of wheat genotypes were evaluated in relation to heat tolerance in field condition by seeding them at November 27 (normal), December 17 (late) and January 7 (very late growing condition) over two successive years. HT genotypes showed higher canopy temperature depression (CTD) in each growing conditions than the MHT and HS genotypes. At late and very late growing heat stress conditions, HS genotypes exhibited larger increase in flag leaf proline at 8 days after anthesis (DAA) than the MHT and HT genotypes. At normal growing condition, the variation of total chlorophyll content in flag leaf among the HT, MHT and HS genotypes were lower compared to late and very late growing condition. The chlorophyll reduction at late growing heat stress condition was clearly distinguishable between the HT and HS genotypes.

To evaluate the effect of sowing density (300, 400, 500, 600 and 700 plants/m²) on the growth of wheat under deficit irrigation (100, 75 and 50% crop water requirement, I100, I75 and I50, respectively), an experiment was carried out during 2009 and 2010. In both years, deficit irrigation resulted in a considerable reduction in yield, yield components, leaf area index (LAI) and leaf water potential (Ψw). In contrast, the canopy temperature (CT) significantly increased under deficit irrigation. Furthermore, increasing of sowing density from 300 to 600 plants/m² resulted in a significant increase in grain yield under I100 and I75. Maximum grain yield as 525.9 and 564.2 g/m² was obtained in the first and the second years, respectively in sowing density of 600 plants/m² and I100. This sowing density was also the proper density in I75 and I50 irrigation regimes. Increasing of sowing density reduced 1000-grain weight and grain number per spike and increased spike number per square meter. In the first year, increasing of sowing density from 300 to 600 plants/m² caused a significant increase in LAI in all irrigation regimes, while in the second year, maximum LAI was observed in 700 plants/m² sowing density. It was found that increasing of sowing density significantly reduced the Ψw and the CT in both well-watered and deficit irrigation. In conclusion, the results suggest that 600 plants/m² would be the optimal sowing density under different water conditions. Alleviation of water stress by the increasing sowing density was found to be associated partly with enhanced LAI and reduced CT. [ABSTRACT FROM AUTHOR]

The development of high-throughput genotyping and phenotyping has provided access to many tools to accelerate plant breeding programs. Unmanned Aerial Systems (UAS)-based remote sensing is being broadly implemented for field-based high-throughput phenotyping due to its low cost and the capacity to rapidly cover large breeding populations. The Structure-from-Motion photogrammetry processes aerial images taken from multiple perspectives over a field to an orthomosaic photo of a complete field experiment, allowing spectral or morphological trait extraction from the canopy surface for each individual field plot. However, some phenotypic information observable in each raw aerial image seems to be lost to the orthomosaic photo, probably due to photogrammetry processes such as pixel merging and blending. To formally assess this, we introduced a set of image processing methods to extract phenotypes from orthorectified raw aerial images and compared them to the negative control of extracting the same traits from processed orthomosaic images. We predict that standard measures of accuracy in terms of the broad-sense heritability of the remote sensing spectral traits will be higher using the orthorectified photos than with the orthomosaic image. Using three case studies, we therefore compared the broad-sense heritability of phenotypes in wheat breeding nurseries including, (1) canopy temperature from thermal imaging, (2) canopy normalized difference vegetation index (NDVI), and (3) early-stage ground cover from multispectral imaging. We evaluated heritability estimates of these phenotypes extracted from multiple orthorectified aerial images via four statistical models and compared the results with heritability estimates of these phenotypes extracted from a single orthomosaic image. Our results indicate that extracting traits directly from multiple orthorectified aerial images yielded increased estimates of heritability for all three phenotypes through proper modeling, compared to estimation using traits extracted from the orthomosaic image. In summary, the image processing methods demonstrated in this study have the potential to improve the quality of the plant trait extracted from high-throughput imaging. This, in turn, can enable breeders to utilize phenomics technologies more effectively for improved selection.

The development of high-throughput genotyping and phenotyping has provided access to many tools to accelerate plant breeding programs. Unmanned Aerial Systems (UAS)-based remote sensing is being broadly implemented for field-based high-throughput phenotyping due to its low cost and the capacity to rapidly cover large breeding populations. The Structure-from-Motion photogrammetry processes aerial images taken from multiple perspectives over a field to an orthomosaic photo of a complete field experiment, allowing spectral or morphological trait extraction from the canopy surface for each individual field plot. However, some phenotypic information observable in each raw aerial image seems to be lost to the orthomosaic photo, probably due to photogrammetry processes such as pixel merging and blending. To formally assess this, we introduced a set of image processing methods to extract phenotypes from orthorectified raw aerial images and compared them to the negative control of extracting the same traits from processed orthomosaic images. We predict that standard measures of accuracy in terms of the broad-sense heritability of the remote sensing spectral traits will be higher using the orthorectified photos than with the orthomosaic image. Using three case studies, we therefore compared the broad-sense heritability of phenotypes in wheat breeding nurseries including, (1) canopy temperature from thermal imaging, (2) canopy normalized difference vegetation index (NDVI), and (3) early-stage ground cover from multispectral imaging. We evaluated heritability estimates of these phenotypes extracted from multiple orthorectified aerial images via four statistical models and compared the results with heritability estimates of these phenotypes extracted from a single orthomosaic image. Our results indicate that extracting traits directly from multiple orthorectified aerial images yielded increased estimates of heritability for all three phenotypes through proper modeling, compared to estimation using traits extracted from the orthomosaic image. In summary, the image processing methods demonstrated in this study have the potential to improve the quality of the plant trait extracted from high-throughput imaging. This, in turn, can enable breeders to utilize phenomics technologies more effectively for improved selection. [ABSTRACT FROM AUTHOR]

The purpose of the study was to assess the relationships between physiological parameters and grain yield of different bread wheat genotypes. In the present research a total of 25 bread wheat genotypes were tested during the 2016-2017 seasons under rainfed conditions. The experiment was conducted in a randomized complete blocks design with four replications. Grain yield, days of heading, plant height, biomass (NDVI) from GS25 up to GS85 growth stage, chlorophyll content (SPAD) during the heading stage, canopy temperature (CT) at GS60 and GS75 growth stages, and glaucousness were investigated. The results of variance analyses showed that there were significant differences (p<0.01) among genotypes for yield. The mean grain yield was 7948 kg ha-1 and yield ranged from 7033 kg ha-1 to 8759 kg ha-1, the highest grain yield performed by TE6744-16 line. According to the results, significant differences among cultivars in terms of plant height, days of heading, biomass, chlorophyll content, canopy temperature, glaucousness were found. TE6627-6 line had the highest chlorophyll content and also, chlorophyll content positively affected grain yield. Canopy temperature is generally related to yield under drought stress condition in bread wheat. In the study early maturing (days of heading) genotypes had lower canopy temperature. An increase in biomass after the heading phase has positively affected grain yield. In the study, no correlation was found between grain yield and biomass at GS25 and GS45 growth phase. There was a negative correlation between glaucousness with biomass at GS60, GS75 and GS85 growth phase. These results showed that physiological parameters such as biomass (at GS75 and GS85), canopy temperature (at GS60 and GS75), and chlorophyll content (at GS60), and glaucousness could be used for selection parameters under rainfed conditions for yield in bread wheat. [ABSTRACT FROM AUTHOR]

Drought stress is a serious threat limiting global wheat production. Adaptability of wheat genotypes to drought stress is an important objective in wheat breeding. This study was carried out to understand the effect of drought stress on growth and development, and to identify drought tolerant wheat genotypes. Thirty wheat genotypes of diverse genetic makeup were assessed in transparent polythene bags (6 x 27 inches), and filled them with sterile, homogenized mixture of loam, sand and compost soil. Two factorial Completely Randomized Design was followed with three replications and two treatments. The experiment was conducted during 2015-16 in the experimental site of the Department of Plant Breeding and Genetics, PMAS Arid Agriculture University Rawalpindi, Pakistan. Data were recorded on drought-related physiological traits viz. proline content, osmotic adjustment, excised leaf water retention (ELWR), relative water content (RWC), cell membrane stability (CMS), chlorophyll content and canopy temperature. Mean squares for all traits revealed significant differences among genotypes under moisture stress and normal environmental conditions. High variations were recorded for cell membrane stability, relative water content and osmotic adjustment which indicated the suitability of these traits as selection criterion for drought tolerance. Significant association was observed between chlorophyll and proline content. Osmotic adjustment was significantly correlated with relative water content and cell membrane stability. According to obtained results, genotypes NARC-09, AUR-10, SA-75, Mexipak and AUR-09 were identified as drought-tolerant, hence can serve as a good source in wheat breeding programs to develop high yielding varieties for arid, drought and rainfed areas. [ABSTRACT FROM AUTHOR]

This research was carried out in the experimental fields of Department of Field Crops, Faculty of Agriculture, the University of Namık Kemal in 2014-2015. In the study, totally 30 bread wheat (Triticum aestivum L.) genotypes (15 cultivars; early, medium-early and late-maturing; 10 lines are tolerant to the heat-temperature stress which were provided by CIMMYT-International Maize and Wheat Improvement Center), 5 lines (were taken from the same university's wheat breeding program which was collaborated by the CIMMYT) were used as an experimental material. The experiment was adjusted in a split-plot design with 3 replicates. Sowing dates (Normal (NS November 09, 2014) and Late sowing (LS January 09, 2015)) were constituted the main plots, and the genotypes constituted the sub-plots. These physiological traits ((membrane thermostability (MT), canopy temperature (CT), leaf chlorophyll content (LCC) and stomatal conductance (SC)) were measured at the LS stage due to giving much more correct, logical and meaningful results, but grain yield (GY) was fixed for all the sowing dates. Obtained findings are: The GY was varied between (4.35- 6.34 t ha-1) for genotypes; the MT was changed between (10.58-66.25%); the CT was realized between (17.67-22.00 oC); the LCC was varied between (38.30-53.30 SPAD) and the SC was changed between (25.20-166.80 mmol m-2 s-1). It was observed that most of the CIMMYT originated genotypes are tolerant to high-temperature stress and most of the wheats that are grown in Thrace Region are negatively affected by the high-temperature stress. [ABSTRACT FROM AUTHOR]

Simple and repeatable methods are needed to select for deep roots under field conditions. A large-scale field experiment was conducted to assess the association between canopy temperature (CT) measured by airborne thermography and rooting depth determined by the core-break method. Three wheat populations, C306×Westonia (CW), Hartog×Drysdale (HD), and Sundor×Songlen (SS), were grown on stored soil water in NSW Australia in 2017 (n =196–252). Cool and warm CT extremes ('tails') were cored after harvest (13–32% of each population). Rooting depth was significantly correlated with CT at late flowering (r = –0.25, –0.52, and –0.23 for CW, HD, and SS, respectively, P <0.05 hereafter), with normalized difference vegetation index (NDVI) at early grain filling (r =0.30–0.39), and with canopy height (r =0.23–0.48). The cool tails showed significantly deeper roots than the respective warm tails by 8.1 cm and 6.2 cm in CW and HD, and correspondingly, greater yields by an average 19% and 7%, respectively. This study highlighted that CT measured rapidly by airborne thermography or NDVI at early grain filling could be used to guide selection of lines with deeper roots to increase wheat yields. The remote measurement methods in this study were repeatable and high throughput, making them well suited to use in breeding programmes. [ABSTRACT FROM AUTHOR]

Summary: Plant phenotyping forms the core of crop breeding, allowing breeders to build on physiological traits and mechanistic science to inform their selection of material for crossing and genetic gain. Recent rapid progress in high‐throughput techniques based on machine vision, robotics, and computing (plant phenomics) enables crop physiologists and breeders to quantitatively measure complex and previously intractable traits. By combining these techniques with affordable genomic sequencing and genotyping, machine learning, and genome selection approaches, breeders have an opportunity to make rapid genetic progress. This review focuses on how field‐based plant phenomics can enable next‐generation physiological breeding in cereal crops for traits related to radiation use efficiency, photosynthesis, and crop biomass. These traits have previously been regarded as difficult and laborious to measure but have recently become a focus as cereal breeders find genetic progress from 'Green Revolution' traits such as harvest index become exhausted. Application of LiDAR, thermal imaging, leaf and canopy spectral reflectance, Chl fluorescence, and machine learning are discussed using wheat and sorghum phenotyping as case studies. A vision of how crop genomics and high‐throughput phenotyping could enable the next generation of crop research and breeding is presented. [ABSTRACT FROM AUTHOR]

The field experiments were conducted in rabi seasons of 2014-15 and 2015-16 at research farm, Ludhiana, Punjab. Wheat variety (WH 1105) was sown in two row directions viz, east-west (E-W) and north-south (N-S) with three row spacing as S1 (15 cm), S2 (22.5 cm) and S3 (30 cm), and two mulching levels viz., Mo (No mulch) and M1 (mulch at the rate of 5t ha-1). PAR interception, canopy temperature, soil temperature and soil moisture were recorded periodically during the crop season in all the treatments. The results revealed that the intercepted photosynthetically active radiation (PAR) was 4- 5 per cent higher in E-W than N-S row direction which contributed 1.67 q ha-1 higher grain yield. Better utilization of solar radiation was observed in 15.0 cm row spacing and the canopy temperature was 0.5°C higher in unmulched crop as compared to mulched crop during both years. Straw mulching @ 5t ha-1 improved soil moisture and regulated soil temperature. Mean soil temperature was higher (1.0 ºC) under mulched crop as compared to unmulched crop. The soil moisture was 4-5 per cent higher under mulched crop as compared to unmulched crop which ultimately resulted in higher soil temperature during early growth stages. Significantly higher grain yield was recorded in mulched crop as compared to unmulched.

The field experiments were conducted in rabi seasons of 2014-15 and 2015-16 at research farm, Ludhiana, Punjab. Wheat variety (WH 1105) was sown in two row directions viz, east-west (E-W) and north-south (N-S) with three row spacing as S1 (15 cm), S2 (22.5 cm) and S3 (30 cm), and two mulching levels viz., Mo (No mulch) and M1 (mulch at the rate of 5t ha-1). PAR interception, canopy temperature, soil temperature and soil moisture were recorded periodically during the crop season in all the treatments. The results revealed that the intercepted photosynthetically active radiation (PAR) was 4-5 per cent higher in E-W than N-S row direction which contributed 1.67 q ha-1 higher grain yield. Better utilization of solar radiation was observed in 15.0 cm row spacing and the canopy temperature was 0.5°C higher in unmulched crop as compared to mulched crop during both years. Straw mulching @ 5t ha-1 improved soil moisture and regulated soil temperature. Mean soil temperature was higher (1.0 °C) under mulched crop as compared to unmulched crop. The soil moisture was 4-5 per cent higher under mulched crop as compared to unmulched crop which ultimately resulted in higher soil temperature during early growth stages. Significantly higher grain yield was recorded in mulched crop as compared to unmulched. [ABSTRACT FROM AUTHOR]

Many late-season physiological traits affect grain yield in wheat, either directly or indirectly. However, information on the genetic control of yield-related traits is still limited. In this study, we aimed to identify quantitative trait loci (QTL) for canopy temperature and chlorophyll content index during anthesis (CTa and CCIa, respectively), the mid grain-filling stage (CTg1 and CCIg1, respectively), and the late grain-filling stage (CTg2 and CCIg2, respectively) as well as for plant height (PH), thousand kernels weight (TKW), and grain yield (GY) using genome-wide linkage mapping. To this end, a double haploid population derived from a cross between two high yielding wheat cultivars, UI Platinum and SY Capstone, was phenotyped in four irrigated environments and genotyped using the wheat 90K iSelect platform and simple sequence repeats. The genotypic data were used to construct a high-density genetic map of 43 linkage groups (LGs) with a total length of 3594.0 cm and a marker density of 0.37 cm. A total of 116 QTL for all nine traits was detected on 33 LGs, spreading to all wheat chromosomes, except for Chr. 7D. Of these, six QTL (CTa.ui-4B.1, Q.CTg1.ui-5B-2.1, Q.CTg2.ui-6B.1, Q.PH.ui-6A-2.1, Q.TKW.ui-2D-1, and Q.GY.ui-6B) were consistently detected in more than three irrigated environments, called as stable QTL. Additionally, we identified 26 QTL clusters for more than two traits, of which the top four were located on Chromosomes 4A-1, 1B-1, 5B-2, and 2D-1. Overall, the stable QTL significantly related with grain yield, QTL clusters, and linked molecular markers identified in this study, may be useful in marker-assisted selection in early generation and early growth stage for grain yield improvement. [ABSTRACT FROM AUTHOR]

Despite widespread application in studying climate change impacts, most crop models ignore complex interactions among air temperature, crop and soil water status, CO 2 concentration and atmospheric conditions that influence crop canopy temperature. The current study extended previous studies by evaluating T c simulations from nine crop models at six locations across environmental and production conditions. Each crop model implemented one of an empirical (EMP), an energy balance assuming neutral stability (EBN) or an energy balance correcting for atmospheric stability conditions (EBSC) approach to simulate T c . Model performance in predicting T c was evaluated for two experiments in continental North America with various water, nitrogen and CO2 treatments. An empirical model fit to one dataset had the best performance, followed by the EBSC models. Stability conditions explained much of the differences between modeling approaches. More accurate simulation of heat stress will likely require use of energy balance approaches that consider atmospheric stability conditions. [ABSTRACT FROM AUTHOR]

A number of physiological traits have been proposed as selection criteria for late drought resistance and grain yield improvement in wheat. To characterize them in terms of late drought resistance, 64 bread wheat genotypes were evaluated for canopy temperature difference (CTD), leaf senescence rate (LSR), SPAD chlorophyll value, initial fluorescence (Fo), maximum fluorescence (Fm), variable fluorescence (Fv), maximum quantum efficiency of PSII (Fv/Fm), leaf ash content, and grain ash content in two field experiments conducted in irrigated and late drought conditions during the 2011-12 and 2012-13 seasons in Erzurum, Turkey. The experiments were conducted in an 8 × 8 lattice design with two replicates. Significant variation was observed among the genotypes for all the traits. Late drought decreased the grain yield, CTD, SPAD, Fm, Fv, Fv/Fm, and leaf ash content but increased LSR and grain ash content. The drought sensitivity of the genotypes was determined by a ranking method based on 25 traits measured in the late drought conditions. According to the rank-sum (RS) values of the genotypes, four genotypes were defined as resistant, 15 genotypes as medium resistant, 34 genotypes as medium sensitive, and 11 genotypes as sensitive. Resistant genotypes Müfitbey and Dağdaş 94 produced the highest grain yields in late drought conditions and appeared to be promising parents for the breeding of resistant cultivars. RS was negatively correlated with CTD, SPAD, Fm, Fv, and Fv/Fm, while it was positively correlated with LSR. For screening late droughtresistant genotypes, 15 days post anthesis (15DPA) is the optimum time for Fv, CTD, and SPAD measurements. The stepwise multiple linear regression analysis indicated that the Fv15DPA, Fv25DPA, CTD15DPA, and SPAD15DPA could explain 75.2% of the total variation in RS. Therefore, the Fv15DPA, Fv25DPA, CTD15DPA, and SPAD15DPA traits can be used as selection criteria as a combination for the classifying of wheat genotypes in terms of late drought resistance. [ABSTRACT FROM AUTHOR]

Plant breeding trials are extensive (100s to 1000s of plots) and are difficult and expensive to monitor by conventional means, especially where measurements are time-sensitive. For example, in a land-based measure of canopy temperature (hand-held infrared thermometer at two to 10 plots per minute), the atmospheric conditions may change greatly during the time of measurement. Such sensors measure small spot samples (2 to 50 cm2), whereas image-based methods allow the sampling of entire plots (2 to 30 m2). A higher aerial position allows the rapid measurement of large numbers of plots if the altitude is low (10 to 40 m) and the flight control is sufficiently precise to collect high-resolution images. This paper outlines the implementation of a customized robotic helicopter (gas-powered, 1.78-m rotor diameter) with autonomous flight control and software to plan flights over experiments that were 0.5 to 3 ha in area and, then, to extract, straighten and characterize multiple experimental field plots from images taken by three cameras. With a capacity to carry 1.5 kg for 30 min or 1.1 kg for 60 min, the system successfully completed >150 flights for a total duration of 40 h. Example applications presented here are estimations of the variation in: ground cover in sorghum (early season); canopy temperature in sugarcane (mid-season); and three-dimensional measures of crop lodging in wheat (late season). Together with this hardware platform, improved software to automate the production of ortho-mosaics and digital elevation models and to extract plot data would further benefit the development of high-throughput field-based phenotyping systems.

Developing cultivars with improved adaptation to drought and heat stressed environments is a priority for plant breeders. Canopy temperature (CT) is a useful tool for phenotypic selection of tolerant genotypes, as it integrates many physiological responses into a single low-cost measurement. The objective of this study was to determine the ability of CT to predict grain yield within the flow of a wheat breeding program and assess its utility as a tool for indirect selection. CT was measured in both heat and drought stressed field experiments in northwest Mexico on 18 breeding trials totaling 504 spring wheat lines from the International Maize and Wheat Improvement Center (CIMMYT) Irrigated Bread Wheat program. In the heat treatment, CT was significantly correlated with yield (r = −0.26) across all trials, with a maximum coefficient of determination within the individual trials of R2 = 0.36. In the drought treatment, a significant correlation across all trials was only observed when days to heading or plant height was used as a covariate. However, the coefficient of determination within individual trials had a maximum of R2 = 0.54, indicating that genetic background may impact the ability of CT to predict yield. Overall a negative slope in the heat treatment indicated that a cooler canopy provided a yield benefit under stress, and implementing selection strategies for CT may have potential for breeding tolerant genotypes.

Canopy temperature is an important factor for irrigation scheduling. This is because canopy temperature is depend plant water status. This research evaluated usefulness of Modis sensor for estimating wheat canopy temperature. Relationship between temperature and values of digital satellite images were determined on different levels of plant height and then models were evaluated. Based on the results, the best correlation between the temperature of the green cover were with band 34&25, band 3 and band 2 in the special resolution of 1000 m, 500m and 250m respectively, and RMSE was equal to 3.6, 3.6 and 5.3 in the special resolution of 1000 m, 500m and 250m respectively. Lowest error was observed at the top of canopy and maximum error was at the bottom of plant. Result showed that measuring canopy temperature by using remote sensing is possible but magnitude of error showed that models need some modification.

Climate change is one of the primary culprits behind the restraint in the increase of cereal crop yields. In order to address its effects, effort has been focused on understanding the interaction between genotypic performance and the environment. Recent advances in unmanned aerial vehicles (UAV) have enabled the assembly of imaging sensors into precision aerial phenotyping platforms, so that a large number of plots can be screened effectively and rapidly. However, ground evaluations may still be an alternative in terms of cost and resolution. We compared the performance of red−green−blue (RGB), multispectral, and thermal data of individual plots captured from the ground and taken from a UAV, to assess genotypic differences in yield. Our results showed that crop vigor, together with the quantity and duration of green biomass that contributed to grain filling, were critical phenotypic traits for the selection of germplasm that is better adapted to present and future Mediterranean conditions. In this sense, the use of RGB images is presented as a powerful and low-cost approach for assessing crop performance. For example, broad sense heritability for some RGB indices was clearly higher than that of grain yield in the support irrigation (four times), rainfed (by 50%), and late planting (10%). Moreover, there wasn’t any significant effect from platform proximity (distance between the sensor and crop canopy) on the vegetation indexes, and both ground and aerial measurements performed similarly in assessing yield.

Background: Grain yield of wheat is primarily determined by both grain number and grain weight, which often influence each other in response to environmental stimuli. Some of the genotypes are capable of maintaining high single grain weight (SGW) across the environments. Understanding mechanisms and factors associated with the superiority of such genotypes over others is necessary to enhance productivity of wheat. Results: Experiments were conducted to elucidate the physiological basis of high SGW of LOK-1, a wheat cultivar grown in dry and hot environments in the central and peninsular zones of India. SGW of LOK-1 was least affected by removal of spikelets indicating little competition between the grains within the spike for assimilates. Reduction in SGW due to defoliation was less and the contribution of stem reserves to the grain development was high in LOK-1 relative to other cultivars. It seems that high level of expression of genes such as expansin (TaExpA6) contributes to the high SGW of LOK-1. Conclusions: Source was not a limiting factor for grain growth of LOK-1 in contrast to other cultivars, whereas sink appeared to be a limiting factor in recently released/identified cultivars. Differences in the amounts of water soluble stem carbohydrate reserves translocated to grain could be one of the factors contributing to higher grain weight in LOK-1. High level expression of TaExpA6, one of the genes contributing to the elongation of endosperm, seems to be crucial for grain growth in wheat. [ABSTRACT FROM AUTHOR]

Even brief periods of high temperatures occurring around flowering and during grain filling can severely reduce grain yield in cereals. Recently, ecophysiological and crop models have begun to represent such phenomena. Most models use air temperature ( T air ) in their heat stress responses despite evidence that crop canopy temperature ( T c ) better explains grain yield losses. T c can deviate significantly from T air based on climatic factors and the crop water status. The broad objective of this study was to evaluate whether simulation of T c improves the ability of crop models to simulate heat stress impacts on wheat under irrigated conditions. Nine process-based models, each using one of three broad approaches (empirical, EMP; energy balance assuming neutral atmospheric stability, EBN; and energy balance correcting for the atmospheric stability conditions, EBSC) to simulate T c , simulated grain yield under a range of temperature conditions. The models varied widely in their ability to reproduce the measured T c with the commonly used EBN models performing much worse than either EMP or EBSC. Use of T c to account for heat stress effects did improve simulations compared to using only T air to a relatively minor extent, but the models that additionally use T c on various other processes as well did not have better yield simulations. Models that simulated yield well under heat stress had varying skill in simulating T c . For example, the EBN models had very poor simulations of T c but performed very well in simulating grain yield. These results highlight the need to more systematically understand and model heat stress events in wheat. [ABSTRACT FROM AUTHOR]

Wheat crop is influenced by different microclimatic parameters like solar radiation, canopy temperature etc. Agronomic manipulation like change in row spacing and row direction can be used as a strategy to modify the microclimate of crop. Keeping these facts in view, field trials were conducted during rabi 2012-13 and 2013-14 under two experiments in first experiment wheat varieties HD 2967, PBW 550 and PBW 343 were sown under three row spacing viz. 15 cm, 22.5 cm and 30 cm. In second experiment, wheat varieties HD 2967, PBW 550 and PBW 343 were sown under two row direction viz. North-South (N-S) and East-West (E-W). Short wave radiation interception and canopy temperature was recorded under different treatments at 15 days interval. Among different row spacing, short wave radiation interception and canopy temperature was maximum at 30 cm row spacing (77.7% and 25.1°C) followed by 22.5 cm (75.7% and 24.2°C) and 15 cm row spacing (73.9% and 23.2°C), whereas under row directions short wave radiation interception and canopy temperature was more (76.5% and 23.9°C) in E-W row direction as compared to N-S row direction (75% and 23.2°C). Relationships were developed between dry matter accumulation and canopy temperature. Polynomial relationships gave significant R² value (0.66 & 0.69) under different treatments. This two year study indicated that agronomic manipulations play an important role in microclimate modification and canopy temperature significantly influence dry matter accumulation under different crop geometry. [ABSTRACT FROM AUTHOR]

The field experiment was conducted during rabi seasons of 2012-13 and 2013-14 at the Research Farm, School of Climate Change and Agricultural Meteorology, PAU, Ludhiana. Wheat (Triticum aestivum L.) varieties HD 2967, PBW 550 and PBW 343 were sown under two row direction, viz. North-South (N-S) and East-West (E-W). Yellow rust (Puccinia striformis f sp tritci) severity and incidence was recorded at weekly intervals. Disease severity index was higher (100%) during rabi 2012-13 as compared to 2013-14 (91%). Among different row direction the disease severity was higher under N-S row direction as compared to E-W row direction during both the years. Area under disease progress curve (AUDPC) was maximum in PBW 343 sown under N-S row direction as compared to other treatments. Among three varieties HD 2967 was highly resistant to yellow rust as it showed zero AUDPC. Highly significant value of R2 (0.91 and 0.90) was found when maximum meteorological parameters were combined in PBW 343 and PBW 550, respectively. Relationships were developed between microclimatic parameters, viz. canopy temperature and relative humidity. Analysis of these relationships indicated that disease and microclimatic parameters were interrelated. Higher R2 values of Humid Thermal Ratio (HTR), Special Humid Thermal Ratio (SHTR) and disease severity indicated that HTR and SHTR can be used as a disease predictor.

The changing climatic condition of the world significantly affecting the average grain yield of wheat crop. In the present study, fifty-six wheat genotypes including checks (Akbar-2019 and Barani-2017) were tested under drought stress. The crop was grown under rainfed conditions (only pre-sowing irrigation was applied at the time of land preparation) following alpha lattice design with two replications at Wheat Research Institute, Faisalabad, Punjab, Pakistan during 2020–21. Several yield and yield contributing traits were examined under drought stress. The analysis of variance (ANOVA) depicted significant differences among all traits which showed existence of great variation among them. Pearson's correlation studies showed significant positive correlation of yield (kg ha−1) with spike length (0.98**), flag leaf area (0.97**), normalized difference vegetation index (NDVI) at booting (0.87**) and grain filling stage (0.97**). Similarly, bi-plot analysis also revealed association of yield (kg ha−1) with spike length (cm), flag leaf area (cm2), NDVI at booting and NDVI at grain filling stage under drought stress condition. Estimation of canopy temperature at grain filling stage expressed negative relationship with yield (−0.11) under drought stress. Genotypes V-19274 (4536.2 kg ha−1) and V-19177 (4450.5 kg ha−1) were found best regarding yield and its contributing traits (spike length and flag leaf area) under drought stress. Cluster analysis separated the wheat genotypes in to four groups. Among all clusters the group four expressed high magnitude of yield (5163.4 kg ha−1). The genotypes in this cluster expressed high magnitudes of spike length (15.18 cm), flag leaf area (64.03 cm2), grain filling period (40.5 days), NDVI at booting (0.81) and NDVI at grain filling stage (0.72), while showed lower magnitude regarding plant height (97 cm), days to 50% maturity (141.5), days to 50% heading (101) and canopy temperature at grain filling stage (21.55) as compared to other three clusters. The identified wheat genotypes can be further used in different wheat breeding programs for water deficient conditions in changing climate scenario of the region to develop drought tolerant wheat cultivars. • Forty-six wheat genotypes were tested under drought stress for yield and its related traits. • The yield showed significant positive correlation with spike length, flag leaf area, and NDVI at booting and grain filling stage, and the bio-plot analysis also confirmed this association. • Canopy temperature at grain filling showed negative relationship with yield under drought stress. • Genotype V-19274 and V-19177 were found best regarding yield and its contributing traits under drought stress. [ABSTRACT FROM AUTHOR]

Vegetation indices and canopy temperature are the most usual remote-sensing approaches to assess cereal performance under Mediterranean conditions. However wide differences exist in the costs of the different equipment deployed to measure vegetation indices (e.g. spectroradiometers versus conventional red/green/blue cameras) or canopy temperature (infrared thermometers versus thermal cameras). In this study we compared different methodological approaches measuring vegetation indices and canopy temperature in durum wheat ( Triticum turgidum L. ssp . durum (Desf.) Husn.) and bread wheat ( Triticum aestivum L.) under different water conditions. These two categories of indices were correlated against grain yield during two consecutive years and with total biomass as well as water status (evaluated as carbon isotope composition, δ 13 C, and stomatal conductance) and nitrogen status (nitrogen and chlorophyll content) of the flag leaf during the first year. For the two crop species, and regardless of the device used, vegetation indices (the green area and the greener area) obtained with conventional cameras and the normalized difference vegetation index (NDVI) measured with a spectroradiometer were significantly correlated with grain yield, δ 13 C and stomatal conductance. Moreover, while canopy temperature measured with a thermal camera was better related to grain yield and δ 13 C than when measured with a low cost device such as an infrared thermometer, the latter approach still performs reasonably well when assessing yield and water status. This study highlights the usefulness of low-cost approaches to assess crop growth and water status in wheat under Mediterranean conditions. [ABSTRACT FROM AUTHOR]

In the extensive rice–wheat system of north-west (NW) India, harvesting is by large combines and the rice residues are normally burnt after harvest, followed by irrigation and intensive tillage prior to sowing wheat. While in-field retention of crop residues can play an important role in replenishing soil quality and reducing environmental pollution from stubble burning, until recently, there has been no suitable technology for seeding wheat in rice residues. To address this need, a series of machines (‘Happy Seeders’) was developed over the past 10 years, culminating in the development of version 2 of the 9-row Turbo Happy Seeder (v.2). The 9-row Turbo Happy Seeder(v.2) has a weight of 506 kg and can be operated by a 33.6 kW tractor at a work rate of 0.3 ha h −1 . Numerous on-farm trials show that yield of wheat sown into rice residues with the 9-row Turbo Happy Seeder is similar to or higher than yield with straw burning and conventional tillage prior to sowing, while providing many benefits to the farmer. These include greatly reduced fuel consumption and cost of crop establishment, and the ability to sow as soon as desired after harvest, ensuring the possibility of sowing at the optimum time and reducing the need for irrigation. However, adoption has been low to date, despite a 50% price subsidy. Constraints to adoption include the low window of operation of the machine (25 days per year), the low machine capacity compared with conventional seed drills, the inability to operate in wet straw, and the lack of straw spreaders on combine harvesters. Removal of subsidies for diesel and electricity (for pumping groundwater) and implementation of the policy banning in-field straw burning would help to accelerate adoption of technology for direct drilling wheat into rice residues. [ABSTRACT FROM AUTHOR]

Crop system models are generally parametrized with daily air temperatures recorded at 1.5 or 2 m height. These data are not able to represent temperatures at the canopy level, which control crop growth, and the impact of heat stress on crop yield, which are modified by canopy characteristics and plant physiological processes Since such data are often not available and current simulation approaches are complex and/or based on unrealistic assumptions, new methods for integrating canopy temperatures in the framework of crop system models are needed. Based on a forward stepwise-based model selection procedure and quantile regression analyses, we developed empirical regression models to predict winter wheat canopy temperatures obtained from thermal infrared observations performed during four growing seasons for three irrigation levels. We used daily meteorological variables and the daily output data of a crop system model as covariates. The standard cross validation revealed a root mean square error (RMSE) of ~0.8 °C, 1.5–2 °C and 0.8–1.2 °C for estimating mean, maximum and minimum canopy temperature, respectively. Canopy temperature of both water-deficit and fully irrigated wheat plots significantly differed from air temperature. We suggest using locally calibrated empirical regression models of canopy temperature as a simple approach for including potentially amplifying or mitigating microclimatic effects on plant response to temperature stress in crop system models.

High temperature stress during grain filling stages is one of the main wheat yield limiting factors under rainfed conditions of Pakistan. A field experiment was carried out to evaluate physio-agronomic traits of different wheat genotypes for better yield and heat tolerance under rainfed conditions. Variable growing conditions during grain filling period were created by sowing crop on normal (November 15) and late sowing dates (December 15). Crop planted on normal sowing date had significant affect (p<0.05) and produced 29% higher grain yield as compared to late planting. Significant variation (p<0.05) was also noticed among genotypes in terms of physiological and agronomic traits under both under both normal and late sowing dates, as advance line NR-397 and NARC-09 produced significantly higher (p<0.05) grain yields as compared to NR-400 and NR-379. Higher grain yields of these two cultivars were associated with their more number of days to maturity, higher spikes m2 and heavier grains as compared to other two genotypes. At the same time, grain yields of wheat genotypes showed a strong correlation to their leaf chlorophyll (+0.98) and canopy temperature (-0.99) measurements. Higher grain yields of NR-397 and NARC-09 were directly correlated to their better leaf chlorophyll retention and maintenance of low canopy temperature during grain filling periods. [ABSTRACT FROM AUTHOR]

Temperature change with concomitant change in canopy temperature influences crop growth and productivity. A three year (2005-06 to 2007-08) experiment was carried on wheat varieties PBW 343, HD 2733, HW 2045, PB 533 and K9107 in subplot treatments sown on three dates of 18th November, 3rd and 18th December in main-plot treatments in a split-plot design with three replications. Canopy temperature was measured at CRI, tillering, flowering and milking and stress degree day index was computed. Late sown crop experienced highest canopy temperature, varieties of K 9107 and HW 2045 recorded lowest and highest respectively. Canopy temperature and stress degree day index significantly and negatively correlated to dry matter accumulation in leaf, stem and ear at different phenophases. Grain yield reduce significantly with the delay in sowing. Canopy temperature at 11.30h during CRI, tillering or flowering stages significantly and negatively affected grain yield. [ABSTRACT FROM AUTHOR]