Estimating Key Phenological Dates of Multiple Rice Accessions Using Unmanned Aerial Vehicle-Based Plant Height Dynamics for Breeding

Efficient and high-quality estimation of key phenological dates in rice is of great significance in breeding work. Plant height(PH) dynamics are valuable for estimating phenological dates. However, research on estimating the key phenological dates of multiple rice accessions based on PH dynamics has been limited. In 2022, field traits were collected using unmanned aerial vehicle(UAV)-based images across 435 plots, including 364 rice varieties. PH, dates of initial heading(IH) and full heading(FH), and panicle initiation(PI), and growth period after transplanting(GPAT) were collected during the rice growth stage. PHs were extracted using a digital surface model(DSM) and fitted using Fourier and logistic models. Machine learning algorithms, including multiple linear regression, random forest(RF), support vector regression, least absolute shrinkage and selection operator, and elastic net regression, were employed to estimate phenological dates. Results indicated that the optimal percentile of the DSM for extracting rice PH was the 95th(R^(2) = 0.934, RMSE = 0.056 m). The Fourier model provided a better fit for PH dynamics compared with the logistic models. Additionally, curve features(CF) and GPAT were significantly associated with PI, IH, and FH. The combination of CF and GPAT outperformed the use of CF alone, with RF demonstrating the best performance among the algorithms. Specifically, the combination of CF extracted from the logistic models, GPAT, and RF yielded the best performance for estimating PI(R^(2) = 0.834, RMSE = 4.344 d), IH(R^(2) = 0.877, RMSE = 2.721 d), and FH(R^(2) = 0.883, RMSE = 2.694 d). Overall, UAV-based rice PH dynamics combined with machine learning effectively estimated the key phenological dates of multiple rice accessions, providing a novel approach for investigating key phenological dates in breeding work.

Study on Fruit Quality, Phenological Phases and Shoot Histomorphology of a New Bud Mutant Line, ‘Chuanzao Loquat’

[Objective] This study was to explore the growth characteristics and fruit quality of a new bud mutant line, ＇Chuanzao Loquat＇. [Method] Paraffin section technique combined with field investigation method were adopted to conduct com- parative analysis of shoot histomorphology and phenological phases between two Io- quat varieties, ＇Chuanzao Loquat＇ and ＇Zaozhong 6＇. [Result] ＇Chuanzao Loquat＇ branched out and unfolded leaves about half to a month earlier than ＇Zaozhong 6＇; both the flowering and fruiting phases of ＇Chuanzao Loquat＇ were three months earlier than a precocious variety, ＇Zaozhong 6＇; the proportions of epidermis, cortex parenchyma, vascular tissue and medulla were 3.7%, 14.5%, 15.9% and 65.9%, re- spectively, in spdng shoots of ＇Chuanzao Loquat＇, and 3.1%, 42.5%, 6.9% and 47.5%, respectively, in ＇Zaozhong 6＇. [Conclusion] In terms of phenological phases, ＇Chuanzao Loqua＇ is earlier than ＇Zaozhong 6＇, a currently widely planted precocious variety, and thus is an important germplasm resource of Ioquats.

Study on Phenological Character in Seedling Period of Introduced Populus deltoids Clones

In order to provide directionally genetically improved breeding materials of poplar by exploring the phenological traits genetic variation level and its develop- ment potential of Populus deltoides and the resource evaluation was carried out; 8 phenological phases in seedling period were observed and analyzed of 60 Populus deltoids clones introduced from America. The results showed that： （1） there was obvious difference in phonological character among clones, especially in leaf-spread- ing peak stage and the end term of leaf-falling stage, with the largest variation co- efficient of 14.97% and the minimum of 3.83% respectively. （2） Leaf-spreading peak stage scattered but the end term of leaf-falling stage concentrated the most. The phonological character in early stage of seedling growth was the main factor influ- encing the length of growing season. （3） By principal component analysis, pheno- logical phases were classified into 3 typical periods, including germination stage, leaf-spreading peak stage and leaf-falling stage. （4） Totaling 60 clones were classi- fied into 4 types by using clustering analysis in phenological time variables of clones.

Phenological observations on Larix principis-rupprechtii Mayr. in primary seed orchard

Through 5 years of phenological observations on Larix principis-rupprechtii Mayr. in primary seed orchard and studies on population and individuals of clones, the annual periodic phenological laws were revealed and the annual phe-nological periodic table was drawn up. The correlation between various phenophases, the air temperature and active accumu-lated temperature were analyzed and expounded. The authors also analyzed the similarities and differences of phenophases among clonal individuals as well as the blooming properties of male and female flowers at the same time. This study could pro-vide theoretical reference for working out the production plan of improved varieties and other management measures in seed orchard of Larix principis-rupprechtii.

Mapping winter wheat using phenological feature of peak before winter on the North China Plain based on time-series MODIS data

By employing the unique phenological feature of winter wheat extracted from peak before winter （PBW） and the advantages of moderate resolution imaging spectroradiometer （MODIS） data with high temporal resolution and intermediate spatial resolution, a remote sensing-based model for mapping winter wheat on the North China Plain was built through integration with Landsat images and land-use data. First, a phenological window, PBW was drawn from time-series MODIS data. Next, feature extraction was performed for the PBW to reduce feature dimension and enhance its information. Finally, a regression model was built to model the relationship of the phenological feature and the sample data. The amount of information of the PBW was evaluated and compared with that of the main peak （MP）. The relative precision of the mapping reached up to 92% in comparison to the Landsat sample data, and ranged between 87 and 96% in comparison to the statistical data. These results were sufficient to satisfy the accuracy requirements for winter wheat mapping at a large scale. Moreover, the proposed method has the ability to obtain the distribution information for winter wheat in an earlier period than previous studies. This study could throw light on the monitoring of winter wheat in China by using unique phenological feature of winter wheat.

Remote Sensing Monitoring of Tobacco Field Based on Phenological Characteristics and Time Series Image―A Case Study of Chengjiang County, Yunnan Province, China

Using three-phase remote sensing images of China-Brazil Earth Resources Satellite 02B (CBERS02B) and Landsat-5 TM, tobacco field was extracted by the analysis of time series image based on the different phenological characteristics between tobacco and other crops. The spectral characteristics of tobacco and corn in luxuriant growth stage are very similar, which makes them difficult to be distinguished using a single-phase remote sensing image. Field film after tobacco seedlings transplanting can be used as significant sign to identify tobacco. Remote sensing interpre- tation map based on the fusion image of TM and CBERS02B's High-Resolution (HR) camera image was used as stan- dard reference material to evaluate the classification accuracy of Spectral Angle Mapper (SAM) and Maximum Like- lihood Classifier (MLC) for time series image based on full samples test method. SAM has higher classification accu- racy and stability than MLC in dealing with time series image. The accuracy and Kappa of tobacco coverage extracted by SAM are 83.4% and 0.692 respectively, which can achieve the accuracy required by tobacco coverage measurement in a large area.

Should phenological information be applied to predict agronomic traits across growth stages of winter wheat?

Most existing agronomic trait models of winter wheat vary across growing seasons, and it is an open question whether a unified statistical model can be developed to predict agronomic traits using a vegetation index(VI) across multiple growing seasons. In this study, we constructed a hierarchical linear model(HLM) to automatically adapt the relationship between VIs and agronomic traits across growing seasons and tested the model’s performance by sensitivity analysis. Results demonstrated that(1) optical VIs give poor performance in predicting AGB and PNC across all growth stages, whereas VIs perform well for LAI, LGB, LNC, and SPAD.(2) The sensitivity indices of the phenological information in the AGB and PNC prediction models were 0.81–0.86 and 0.66–0.73, whereas LAI, LGB, LNC, and SPAD prediction models produced sensitivity indexes of 0.01–0.02, 0.01–0.02, 0.01–0.02, and 0.02–0.08, respectively.(3) The AGB and PNC prediction models considering ZS were more accurate than the prediction models based on VI. Whether or not phenological information is used, there was no difference in model accuracy for LGB,LNC, SPAD, and LAI. This study may provide a guideline for deciding whether phenological correction is required for estimation of agronomic traits across multiple growing seasons.

Physiological and Biochemical Responses of Wheat Subjected to Water Deficit Stress at Different Phenological Stages of Development

Proline has been proposed to be an osmoprotector and scavenger of reactive oxygen species in plants subjected to water deficit. The aim of this work was to study the effects of drought on each wheat phenological stage （tillering, booting, heading, flowering and grain-filling） using stress parameters such as the relative water content （RWC）, membrane stability index （MSI）, lipid peroxidation through malondialdehyde levels （MDA） and determination of proline content （PRO）. The Brazilian commercial elite cultivar Triticum aestivum cv. CD 200126 was submitted to eight days of water deficit stress at each stage. The perception of stress was low at tillering and high at the final stages of growth, as verified by the reduction in the MSI and RWC. However, an increase in the MDA was clearly observed. We observed a high proline accumulation when stress was applied, although it was not sufficient to prevent damages. These results indicate that the relevant stages to evaluate the effect of water shortage during wheat plant development are booting, heading and flowering.

Detecting winter canola(Brassica napus) phenological stages using an improved shape-model method based on time-series UAV spectral data

Accurate information about phenological stages is essential for canola field management practices such as irrigation, fertilization, and harvesting. Previous studies in canola phenology monitoring focused mainly on the flowering stage, using its apparent structure features and colors. Additional phenological stages have been largely overlooked. The objective of this study was to improve a shape-model method(SMM) for extracting winter canola phenological stages from time-series top-of-canopy reflectance images collected by an unmanned aerial vehicle(UAV). The transformation equation of the SMM was refined to account for the multi-peak features of the temporal dynamics of three vegetation indices(VIs)(NDVI, EVI, and CI). An experiment with various seeding scenarios was conducted, including four different seeding dates and three seeding densities. Three mathematical functions: asymmetric Gaussian function(AGF), Fourier function, and double logistic function, were employed to fit timeseries vegetation indices to extract information about phenological stages. The refined SMM effectively estimated the phenological stages of canola, with a minimum root mean square error(RMSE) of 3.7 days for all phenological stages. The AGF function provided the best fitting performance, as it captured multiple peaks in the growth dynamics characteristics for all seeding date scenarios using four scaling parameters. For the three selected VIs, CIred-edgeachieved the greatest accuracy in estimating the phenological stage dates. This study demonstrates the high potential of the refined SMM for estimating winter canola phenology.

Exploration of Genetic Pattern of Phenological Traits in Wheat (Triticum aestivum L.) under Drought Stress

Drought is the major detrimental environmental factor for wheat(Triticum aestivum L.)production.The exploration of genetic patterns underlying drought tolerance is of great significance.Here we report the gene actions controlling the phenological traits using the line×tester model studying 27 crosses and 12 parents under normal irrigation and drought conditions.The results interpreted via multiple analysis(mean performance,correlations,principal component,genetic analysis,heterotic and heterobeltiotic potential)disclosed highly significant differences among germplasm.The phenological waxiness traits(glume,boom,and sheath)were strongly interlinked.Flag leaf area exhibits a positive association with peduncle and spike length under drought.The growing degree days(heat-units)greatly influence spikelets and grains per spike,however,the grain yield/plant was significantly reduced(17.44 g to 13.25 g)under drought.The principal components based on eigenvalue indicated significant PCs(first-seven)accounted for 79.9%and 73.9%of total variability under normal irrigation and drought,respectively.The investigated yield traits showed complex genetic behaviour.The genetic advance confronted a moderate to high heritability for spikelets/spike and grain yield/plant.The traits conditioned by dominant genetic effects in normal irrigation were inversely controlled by additive genetic effects under drought and vice versa.The magnitude of dominance effects for phenological and yield traits,i.e.,leaf twist,auricle hairiness,grain yield/plant,spikelets,and grains/spike suggests that selection by the pedigree method is appropriate for improving these traits under normal irrigation conditions and could serve as an indirect selection index for improving yield-oriented traits in wheat populations for drought tolerance.However,the phenotypic selection could be more than effective for traits conditioned by additive genetic effects under drought.We suggest five significant cross combinations based on heterotic and heterobeltiotic potential of wheat genotypes for improved yield and enhanced biological production of wheat in advanced generations under drought.

Effect of various combinations of temperature during different phenological periods on indica rice yield and quality in the Yangtze River Basin in China

Rice grain yield and quality declines are due to unsuitable temperatures from wide regions and various sowing dates.This study aimed to evaluate the effects of temperature on rice yield and quality at different phenological periods and obtain suitable temperatures for phenological periods in the Yangtze River Basin,China.This study conducted experiments on different sowing dates under different areas in the Yangtze River Basin to observe and compare the differences in rice growth,yield,and quality,controlling for regional varieties.The results showed significant differences in rice growth,yield,and quality among sowing dates and areas,which were related to the average daily temperature during the vegetative period(VT)and the first 20 days of the grain-filling period(GT20).In addition,there was a smaller variation in the average daily temperature in the reproductive period(RT)than in the two phenological periods.Therefore,according to the VT and GT20 thresholds of different yields and qualities,the experimental results were divided into four scenarios(Ⅰ,Ⅱ,Ⅲ,andⅣ)in this study.In Scenario I,high head rice production(rice grain yield multiplied by head rice rate)and rice quality could be obtained.The head rice production of ScenariosⅢandⅣwas lower than that of ScenarioⅠ,by 30.1 and 27.6%,respectively.In Scenario II,the head rice production increased insignificantly while the chalky grain rate and chalkiness were 50.6 and 56.3%higher than those of Scenario I.In conclusion,the Scenario I combination with VT ranges of 22.8-23.9℃and GT20 ranges of 24.2-27.0℃or the combination with VT ranges of 23.9-25.3℃and GT20 ranges of 24.2-24.9℃,which can be obtained by adjusting sowing date and selecting rice varieties with suitable growth periods,is recommended to achieve high levels of rice grain yield and quality in the Yangtze River Basin.

Grapevine Phenological Quantitative Trait SSR Genotyping Using High-Throughput HRM-PCR Analysis

Discrimination among grapevine varieties based on quantitative traits,such as flowering,veraison and ripening dates is crucial for variety selection in the context of climate change and in breeding programs.These traits are under complex genetic control for which 6 linked SSR loci(VVS2,VVIn16,VMC7G3,VrZAG29,VMC5G7,and VVIB23)have been identified.Using these markers in HRM-PCR analysis,we assessed genetic diversity among a large collection of 192 grapevine varieties.The grapevine germplasm used encompasses the majority of Greek vineyard with 181 varieties,3 prominent foreign varieties and 11 varieties of Palestinian origin.The SSR markers used were highly polymorphic,displaying unique melting curves for unusually higher number of samples than generally observed in SSR analysis.This prompted us to examine sequence composition for selected samples and found that variation present as SNPs in the flanking sequences of SSR motifs was responsible for the observed polymorphism.Hence,HRM-PCR proved to be a tool of higher analytical power to distinguish genotypes surpassing the discrimination power of conventional gel-based SSR analysis.The study provides a better understanding of genetic variation of SSR marker loci associated to phenological traits in grapevine varieties,signifying an analytical methodology that may be of higher discrimination power in detection of polymorphism for utilization in breeding programs.

Morphological Characterization and Phenological Modeling of <i>Jatropha platyphylla</i>(Euphorbiaceae) Muell. Arg. Genotypes

Morphological characterization and phenological modeling were carried out on genotypes of Jatropha platyphylla collected from the states of Sinaloa and Durango, Mexico. The morphological characterization evidenced the existence of monoecious plants, finding individuals with male and female flowers in the same inflorescence. Fruit with four seeds was also found. The phenological study was divided into two phases and calculated in thermal requirement (°D): Vegetative [seedtime (0), germination (24), emergence (98), cotyledons (87), second (302) and fourth (524) true leaves, end of vegetative growth (302)] and reproductive [flowering (303), fructification (342), maturation (126), defoliation and senescence (450)]. The thermal constant (2558) was similar in all eight genotypes. The phenological stages and the accumulated degree days were adjusted with a third-degree polynomial (Stage = -0.0041x3 + 0.7446x2 - 8.6808x + 6.2448) (R2 = 0.99%) stage. The development of phenological models facilitates the prediction of the flowering date for the selection of varieties with high oil and protein content.

The Phenological Stages of Apple Tree in the North Eastern of Iran

The main objective of this study was to evaluate the process of parameters such as mean temperature;total precipitation on phenology and phenological stages of apple golden type in Razavi Khorasan. For this reason, long-term data of absolute minimum daily temperature, precipitation, humidity, as well as Digital Elevation Model (DEM) was used. After collecting data on phenology and Growing Degree Days (GDD) for golden apple, to pass each phenological stage at different growth stages, the start and end dates, phenological stages of the locations were identified. Then, regression equations with variable longitude, latitude and altitude on SPSS software at level of 50% and 95%, respectively were used, and finally phenological stages and spatial distribution maps of temperature and precipitation variables based on these equations were drawn in ARC GIS software. The analysis of the phenological stages showed that Torbate Heydarieh station has a decreasing trend which is significant at 1% in all stages of phenology and Ghoochan station does not show any significant increase or decrease trend at all stages of phenology.

Study on Phenological Phase of Three Wild Plants in Limestone Mountainous Area of Chongqing City in China

The paper had studied phenological phase of three wild plants in Haishi Park at limestone mountainous area of Chongqing which were Berchemia polyphylla var.leioclada,Caesalpinia decapetala and Bauhinia glauca subsp.hupehana.Samples were selected based on terrain,and it had selected 30 plants of Berchemia polyphylla var.leioclada and Caesalpinia decapetala and 7 plants of Bauhinia glauca subsp.hupehana which were different in shape but similar in size.Fixed point observation was conducted on them and observation results were recorded.It had explored ornamental value of the three wild plants and identified their corresponding ornamental periods,so as to provide scientific reference and suggestions for gardening and application of the three wild plants.

Effects of Climate Warming on Phenological Characteristics of Urban Forest in Shenyang City,China

Change in plant phenology is one of the most sensitive ecological responses to climate warming. Little information is known about the effects of climate warming on phenology of urban tree species in the northern forest of China. In this study, we investigated the phenological characteristics of the main tree species in the urban forest of Shengyang City in China and the correlation between phenology and atmospheric temperature from the discontinuous data during past 42 years over three time periods(from 1962 to 1965, 1977 to 1978, and 2000 to 2005). The results showed that the annual average temperature in Shenyang City showed an increasing trend and increased by 0.96℃ from 1962 to 2005 due to climate warming. The germination phenology of the urban trees was negatively correlated with the temperature in winter and early spring. The leafing phenology was mainly influenced by the temperature in spring before leafing. Influenced by climate warming, the germination, leafing, and flowering phenologies of this urban forest in 2005 were 14, 13, and 10 days earlier than those in 1962, respectively. We inferred that further warming in winter might prolong the growing season of urban trees in the northern forest of China.

Effects of temperature on flowering phenological traits of Populus euphratica Oliv. and Populus pruinosa Schrenk populations, Xinjiang, China

The aims of this study were to explore the interspecific differences of Populus euphratica Oliv.and Populus pruinosa Schrenk populations and the intraspecific differences of males and females within the same species in flowering phenological traits,and the effects of temperatures on flowering phenological traits in different growth years(2001–2003 and 2013–2015).The results showed that P.euphratica population flowered earlier than P.pruinosa population.Moreover,flowering phenological period of population,number of days of flowering phenological period per population,number of days of flowering phenological period per plant and average number of days of flowering period per plant of P.euphratica population were less than those of P.pruinosa population.The differences between male and female within the same species indicated that the flowering periods of males P.euphratica and P.pruinosa populations were earlier than those of female plants.For both species,flowering phenological traits were significantly and negatively correlated with the average temperatures in previous ten days,previous one month and previous three months of flowering.Both species are sensitive to temperature changes and adjust to the changes by advancing the start of flowering and prolonging the duration of flowering.

Seasonal Responses of Net Primary Productivity of Vegetation to Phenological Dynamics in the Loess Plateau, China

With global warming, the great changes in the patterns of plant growth have occurred. The conditions in early spring and late autumn have changed the process of vegetation photosynthesis, which are expected to have a significant impact on net primary productivity(NPP) and affect the global carbon cycle. Currently, the seasonal response characteristics of NPP to phenological changes in dryland ecosystems are still not well defined. This article calibrated and analyzed the normalized difference vegetation index(NDVI)time series of Advanced Very-High-Resolution Radiometer(AVHRR) data from 1982 to 2015 in the Loess Plateau, China. The spatial and temporal distributions of vegetation phenology and NPP in the Loess Plateau under semihumid and semiarid conditions were investigated. The seasonal variation in the NPP response to vegetation phenology under the climate change was also analyzed. The results showed that, different from the northern forest, there was distinct spatial heterogeneity in the effect of climate change on the dynamic change in vegetation growth in the Loess Plateau: 1) an advance of the start of the growing season(SOS) and a delay of the end of the growing season(EOS) significantly increased the NPP in spring and autumn, respectively, in the humid southeast;2) in the arid northwest, the NPP did not significantly increase in spring and autumn but significantly decreased in summer.

Monitoring of winter wheat distribution and phenological phases based on MODIS time-series： A case study in the Yellow River Delta, China

Accurate winter wheat identification and phenology extraction are essential for field management and agricultural policy making. Here, we present mechanisms of winter wheat discrimination and phenological detection in the Yellow River Delta（YRD） region using moderate resolution imaging spectroradiometer（MODIS） time-series data. The normalized difference vegetation index（NDVI） was obtained by calculating the surface reflectance in red and infrared. We used the Savitzky-Golay filter to smooth time series NDVI curves. We adopted a two-step classification to identify winter wheat. The first step was designed to mask out non-vegetation classes, and the second step aimed to identify winter wheat from other vegetation based on its phenological features. We used the double Gaussian model and the maximum curvature method to extract phenology. Due to the characteristics of the time-series profiles for winter wheat, a double Gaussian function method was selected to fit the temporal profile. A maximum curvature method was performed to extract phenological phases. Phenological phases such as the green-up, heading and harvesting phases were detected when the NDVI curvature exhibited local maximum values. The extracted phenological dates then were validated with records of the ground observations. The spatial patterns of phenological phases were investigated. This study concluded that, for winter wheat, the accuracy of classification is 87.07%, and the accuracy of planting acreage is 90.09%. The phenological result was comparable to the ground observation at the municipal level. The average green-up date for the whole region occurred on March 5, the average heading date occurred on May 9, and the average harvesting date occurred on June 5. The spatial distribution of the phenology for winter wheat showed a significant gradual delay from the southwest to the northeast. This study demonstrates the effectiveness of our proposed method for winter wheat classification and phenology detection.

Forest phenological patterns of Northeast China inferred from MODIS data

The role of remote sensing in phenological studies is increasingly regarded as a key to understand large area seasonal phenomena. This paper describes the application of Moderate Resolution Imaging Spectroradiometer (MODIS) time series data for forest phenological patterns. The forest phenological phase of Northeast China (NE China) and its spatial characteristics were inferred using 1-km 10-day MODIS normalized difference vegetation index (NDVI) datasets of 2002. The threshold-based method was used to estimate three key forest phenological variables, which are the start of growing season (SOS), the end of growing season (EOS) and growing season length (GSL). Then the spatial patterns of forest phenological variables of NE China were mapped and analyzed. The derived phenological variables were validated by the field observed data from published papers in the same study area. Results indicate that forest phenological phase from MODIS data is comparable with the observed data. As the derived forest phenological pattern is related to forest type distribution, it is helpful to discriminate between forest types.