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While increasing numbers of studies report wide variations of leaf silicon (Si) accumulation among plant species, within-species variations of leaf Si accumulation have scarcely been examined for tree species. As in crop plants, environmental factors that affect transpiration rates may influence passive transpiration-dependent transport of Si uptake in trees. Here, we tested a hypothesis that leaf Si accumulation rate should be higher in shoots that receive more light and thus achieve faster growth, using Broussonetia papyrifera, a pioneer tree species with successive leaf production and Si accumulation with leaf age. We marked individual leaves weekly throughout the growing season (June–September), and measured Si concentration and light availability in relation to the chronosequence of leaf age in September. In shoots that continued growing and successively produced leaves throughout the growing season, leaf Si content increased linearly with leaf age. In support of our hypothesis, leaf Si accumulation rate varied widely among shoots with positive correlations with shoot growth and light availability. In conclusion, both leaf age and microenvironment affect within-species variations in leaf Si concentration of this species, a moderate Si accumulator. [ABSTRACT FROM AUTHOR]

This paper explores whether it is feasible to use the RGB color information in images of wheat canopies that were exposed to low temperatures during the growth season to achieve fast, non-destructive, and accurate determination of the severity of any freeze injury it may have incurred. For the study presented in this paper, we compared the accuracy of a number of algorithmic classification models using either meteorological data reported by weather services or the color gradation skewness-distribution from high-definition digital canopy images acquired in situ as inputs against a reference obtained by manually assessing the severity of the freeze injury inflicted upon wheat populations at three experimental stations in Shandong, China. The algorithms we used to construct the models included in our study were based on either K-means clustering, systematic clustering, or naïve Bayesian classification. When analyzing the reliability of our models, we found that, at more than 85%, the accuracy of the Bayesian model, which used the color information as inputs and involved the use of prior data in the form of the reference data we had obtained through manual classification, was significantly higher than that of the models based on systematic or the K-means clustering, which did not involve the use of prior data. It was interesting to note that the determination accuracy of algorithms using meteorological factors as inputs was significantly lower than that of those using color information. We also noted that the determination accuracy of the Bayesian model had some potential for optimization, which prompted us to subject the inputs of the model to a factor analysis in order to identify the key independent leaf color distribution parameters characterizing wheat freeze injury severity. This optimization allowed us to improve the determination accuracy of the model to over 90%, even in environments comprising several different ecological zones, as was the case at one of our experimental sites. In conclusion, our naïve Bayesian classification algorithm, which uses six key color gradation skewness-distribution parameters as inputs and involves the use of prior data in the form of manual assessments, qualifies as a contender for the development of commercial-grade wheat freeze injury severity monitoring systems supporting post-freeze management measures aimed at ensuring food security. [ABSTRACT FROM AUTHOR]

The Aral Sea is an indispensable component of the socio-economic progress of Central Asia but has undergone substantial ecological transformations over the last few decades, primarily due to global warming and human activities. Among these changes, the basin area has decreased, and water levels have dropped. This paper focuses on a comprehensive analysis of the spatial variation of key climate parameters, such as temperature, precipitation, and potential evapotranspiration over the Aral Sea. Moreover, we examined the transformation of seasonal water areas in the Aral Sea during the growing and non-growing seasons between 2002 and 2017 and the influence of climate and human factors on these changes using Landsat satellite data. Our results indicate that the western section of the Aral Sea has experienced a reduction in water area by 2.41 km2 and 1.83 km2 during the warm (R2 = 0.789) and cold (R2 = 0.744) seasons, respectively, over the investigated period. The decrease in lake water volume during the warm season can be attributed to local climate variations, as a strong negative correlation exists between seasonal water storage change and temperature (potential evapotranspiration). The correlation analysis shows that the water change in the northern part of the Aral Sea during the growing season has a significant positive correlation with temperature (R = 0.52) and an insignificant negative correlation with precipitation (R = −0.22). On the contrary, in the west and east parts of the Aral Sea, there is a significant negative correlation with temperature (R = −0.71 and −0.62) and a high positive correlation with precipitation (R = 0.71 and 0.55) during the growing season. [ABSTRACT FROM AUTHOR]

Roundup is the most widely used herbicide in agriculture. It contains glyphosate as the 'active ingredient', together with formulants. There are various versions of Roundup, with somewhat different effects depending on the formulants. Most genetically-modified crops are designed to tolerate Roundup, thus allowing spraying against weeds during the growing season of the crop without destroying it. Having been so heavily used, this herbicide is now found in the soil, water, air, and even in humans worldwide. Roundup may also remain as a residue on edible crops. Many studies have found harm to the environment and to health, making it imperative to regulate the use of Roundup and to ensure that its various formulations pose no danger when used in the long-term. Unfortunately, regulators may only assess the 'active ingredient', glyphosate, and ignore the toxicity of the formulants, which can be far more toxic than the active ingredient. This omission is in violation of a ruling by the Court of Justice of the European Union. There are close ties between the regulators and the industry they are supposed to regulate. Objectionable practices include 'revolving doors' between the regulators and the industry, heavy reliance on unpublished papers produced by the industry while dismissing papers published by independent scientists, and strong covert influence on the regulatory process by industry. Although this paper focuses on the European Union (EU), the situation is much the same in the United States. [ABSTRACT FROM AUTHOR]

This paper reports the results of a seven-year study of a phytoremediation system consisting of 349 hybrid poplars (Populous deltoids x Populus nigra 'DN-21') that were emplaced to reduce the migration of impacted groundwater toward a nearby stream. For the relatively small tree stand, the achievement of hydraulic containment was challenged by several factors, including topographic constraints on tree placement, spatial heterogeneity in depth-to-groundwater, and lack of controls on surface runoff. However, the interpretation of measured diurnal water table fluctuations indicated substantial and increasing levels of groundwater extraction, consistent with poplar sap flow measurements collected during two growing seasons. The project also provided unique educational experiences for undergraduate and graduate students from multiple academic disciplines who participated in monitoring, site maintenance, and data interpretation. Novelty statement The paper adds to the limited literature on poplar-based phytoextraction of contaminated groundwater by describing a seven-year case study with detailed hydrologic measurements. Novel elements include (1) a very large data set of poplar sap flow measurements that provides insight into potential spatial and temporal variability, and (2) a detailed application of an under-utilized analytical tool (water table fluctuations) to evaluate hydraulic capture. [ABSTRACT FROM AUTHOR]

Coastal cliffs erode in response to short- and long-term environmental changes, but predicting these changes continues to be a challenge. In addition to a chronic lack of data on the cliff face, vegetation presence and growth can bias our erosion measurements and limit our ability to detect geomorphic erosion by obscuring the cliff face. This paper builds on past research segmenting vegetation in three-band red, green, blue (RGB) imagery and presents two approaches to segmenting and filtering vegetation from the bare cliff face in dense point clouds constructed from RGB images and structure-from-motion (SfM) software. Vegetation indices were computed from previously published research and their utility in segmenting vegetation from bare cliff face was compared against machine learning (ML) models for point cloud segmentation. Results demonstrate that, while existing vegetation indices and ML models are both capable of segmenting vegetation and bare cliff face sediments, ML models can be more efficient and robust across different growing seasons. ML model accuracy quickly reached an asymptote with only two layers and RGB images only (i.e., no vegetation indices), suggesting that these more parsimonious models may be more robust to a range of environmental conditions than existing vegetation indices which vary substantially from one growing season to another with changes in vegetation phenology. [ABSTRACT FROM AUTHOR]

Introduction: Vegetation is the main factor of ecological stability, but the construction of largescale corridor projects will bring some damage to vegetation. Methods: Based on the NDVI, temperature and precipitation data of the growing season from 1990–2021 (June to September), this paper uses the maximum synthesis method, trend analysis method, correlation analysis method and coefficient of variation method to study the spatial-temporal changes and driving factors of NDVI in the past 32 years, taking the 30 km belt buffer zone along the Lan-Xin Railway as the research area. The influence range of railway construction on NDVI in different climatic conditions is analyzed. Results: The results showed that: (1) From 1990–2021, the average annual temperature of the growing season in the study area showed an increasing trend, the average annual precipitation showed a decreasing trend, and the average annual NDVI showed an increasing trend; NDVI was positively correlated with temperature in 54.04%, and positively correlated with precipitation in 62.88%. Precipitation had a greater effect on NDVI than temperature. (2) Under the same climatic conditions, the NDVI variability coefficient in the study area fluctuates significantly within 3,000–21,000m along the railway line, stabilizing beyond 21,000 m; the impact range of railway construction on NDVI gradually increases with increasing precipitation within the same temperature range, and increases gradually with rising temperatures within the same precipitation range. (3) During the growing season (June to September) in the study area, when the temperature is below 25°C, NDVI increases initially with increasing precipitation before decreasing, showing an overall upward trend; when the temperature is above 25°C, NDVI initially increases with increasing precipitation before decreasing. High temperature and high precipitation will inhibit vegetation growth and reduce NDVI. The NDVI of the core area before the railway construction is larger than that of the background area, while the NDVI of the core area after the railway construction is smaller than that of the background area. Discussion: In short, the construction of Lan-Xin Railway has a certain influence on NDVI along the line. When studying the impact of large-scale engineering projects on vegetation in the future, higher resolution imagery can be used along with the incorporation of human activities’ influence. These factors will enable more accurate and comprehensive research. [ABSTRACT FROM AUTHOR]

To investigate the spatial and temporal changes in fractional vegetation coverage (FVC) and their driving forces in different regions of the Inner Mongolia section of the Yellow River Basin, this paper observed the spatial trends and stability of FVC in these regions based on the MOD13Q1 information regarding the 2000–2020 period as a data source. It used the dimidiate pixel model to invert FVC, and based on the centre of gravity migration model, the coefficient of variation and the Mann–Kendall and Sen's slope estimator test, it studied the spatial variation trend and stability of FVC in the four relevant areas of the Inner Mongolia section; an attribution analysis using a geodetector was also conducted. The following results were found: (1) in terms of temporal FVC change in the relevant areas, from 2000 to 2020, the overall FVC showed an increasing trend, indicating an obvious hierarchy of change as per different seasonal scales (summer > growing season > fall > spring). There is a mutation point in FVC in different areas, and the FVC sequence is random. (2) Regarding spatial change, the overall FVC showed a trend of being high in the eastern regions and low in the western regions and low–high–low from the north to the south; the stability of the Hetao Irrigation District–Wuliangsuhai Area changed more significantly with the successive seasons, and the degraded areas of FVC were mainly distributed in the city centre of the Kundulun River–Daheihe River Area and in the Hetao Irrigation District in the summer. (3) In terms of driving factors, soil type had a relatively higher explanatory power regarding the Hetao Irrigation District–Wuliangsuhai Area, rainfall had a relatively higher explanatory power regarding the Morin River–Wuding River Area and the Kundulun River–Daheihe River Area, and land use had a relatively higher explanatory power regarding the Ten Kongtui–Heidaigou Area. [ABSTRACT FROM AUTHOR]

The fast and accurate provision of within-season data of green area index (GAI) and total N uptake (total N) is the basis for crop modeling and precision agriculture. However, due to rapid advancements in multispectral sensors and the high sampling effort, there is currently no existing reference work for the calibration of one UAV (unmanned aerial vehicle)-based multispectral sensor to GAI and total N for silage maize, winter barley, winter oilseed rape, and winter wheat. In this paper, a practicable calibration framework is presented. On the basis of a multi-year dataset, crop-specific models are calibrated for the UAV-based estimation of GAI throughout the entire growing season and of total N until flowering. These models demonstrate high accuracies in an independent evaluation over multiple growing seasons and trial sites (mean absolute error of 0.19–0.48 m2 m−2 for GAI and of 0.80–1.21 g m−2 for total N). The calibration of a uniform GAI model does not provide convincing results. Near infrared-based ratios are identified as the most important component for all calibrations. To account for the significant changes in the GAI/ total N ratio during the vegetative phase of winter barley and winter oilseed rape, their calibrations for total N must include a corresponding factor. The effectiveness of the calibrations is demonstrated using three years of data from an extensive field trial. High correlation of the derived total N uptake until flowering and the whole-season radiation uptake with yield data underline the applicability of UAV-based crop monitoring for agricultural applications. [ABSTRACT FROM AUTHOR]

Introduction: The paper analyzes the results of 26 years (1996-2021) of phenological observations of the vegetative organs of European beech (Fagus sylvatica L.) in the Western Carpathians. It evaluates the influence of the heterogeneity of this territory, including relief and elevation, based on climaticgeographical types. Methods: Phenological stages, including leaf unfolding, full leaves, leaf coloring, and leaf fall, were monitored at 40 phenological stations across eight elevation zones. The study assesses trends in the occurrence of phenological stages, the length of the growing season, and phenological elevation gradients. Results: The results indicate a statistically significant earlier onset of spring phenological phases and delay in autumn phases, resulting in an average extension of the beech growing season by 12 days. Our findings confirm that the lengthening of the growing season due to warming, as an expression of climate change, is predominantly attributed to the warming in the spring months. The detected delayed onset of autumn phenophases was not due to warming in the autumn months, but other environmental factors influence it. The trend of elongation of the growing season (p<0.01) is observed in all elevation zones, with a less significant trend observed only in zones around 400 and 600 m a.s.l, signaling changes in environmental conditions across most of the elevation spectrum. Moreover, the heterogeneity of climatic-geographical types within each elevation zone increases the variability in the duration of the growing season for sites with similar elevations. By extending the growing season, it is assumed that the beech area will be changed to locations with optimal environmental conditions, especially in terms of adverse climatic events (late spring frosts, drought) during the growing season. The phenological elevation gradients reveal an earlier onset of 2.2 days per 100 m for spring phenophases and a delay of 1.1-2.9 days per 100 m for autumn phenophases. Discussion: These findings highlight the specific environmental conditions of European beech in the Western Carpathians and their potential for anticipating changes in its original area. Additionally, these observations can aid in forecasting the further development of phenological manifestations related to climate change. [ABSTRACT FROM AUTHOR]

NASA's Soil Moisture Active Passive (SMAP) was originally designed to combine high-resolution active (radar) and coarse-resolution but highly sensitive passive (radiometer) L-band observations to achieve unprecedented spatial resolution and accuracy for soil moisture retrievals. However, shortly after SMAP was put into orbit, the radar component failed, and the high-resolution capability was lost. In this paper, the integration of an alternative radar sensor with the SMAP radiometer is proposed to enhance soil moisture retrieval capabilities over vegetated areas in the absence of the original high-resolution radar in the SMAP mission. ESA's Sentinel-1A C-band radar was used in this study to enhance the spatial resolution of the SMAP L-band radiometer and to improve soil moisture retrieval accuracy. To achieve this purpose, we downscaled the 9 km radiometer data of the SMAP to 1 km utilizing the Smoothing Filter-based Intensity Modulation (SFIM) method. An Artificial Neural Network (ANN) was then trained to exploit the synergy between the Sentinel-1A radar, SMAP radiometer, and the in situ-measured soil moisture. An analysis of the data obtained for a plant growing season over the Mississippi Delta showed that the VH-polarized Sentinel-1A radar data can yield a coefficient of correlation of 0.81 and serve as a complimentary source to the SMAP radiometer for more accurate and enhanced soil moisture prediction over agricultural fields. [ABSTRACT FROM AUTHOR]

Copyright of Field & Vegetable Crops Research / Ratarstvo i povrtarstvo is the property of Institute of Field & Vegetable Crops and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In Poland, the mountainous and hilly regions until recently were territories with unbalanced and poor diet quality, especially in early spring. Wild edible plants were or remain influential in supplementing a human diet. One of the earliest wild edible plants to appear in the growing season, characteristic of a broad swath of Europe from Ukraine to Germany, remains wild (ramsons) garlic (Allium ursinum L.). This paper assesses the impact of the vegetation site and preservation methods on the content of chlorophylls, β-carotene, vitamin C, total polyphenols, and antioxidant activity (ABTS, DPPH, and FRAP) of wild garlic leaves. In addition, the connection between its genome pattern and chemical composition was assessed. The plants were collected in three locations in the Carpathian foothills, and the reference sample was plants collected in the lowlands. The site from which the raw material was harvested has a statistically significant effect on the chemical composition of the preserved leaves of wild garlic. The profiles of the analysed components differed in the material from a different site. Wild garlic leaves from mountainous areas (400–600 m above sea level) were characterized by a higher content of the analysed ingredients than leaves obtained from lowland sites (200 m above sea level). Moreover, the material from the lowlands had a different genetic pattern from the leaves from the mountainous areas. [ABSTRACT FROM AUTHOR]

Floral phenology as a special indicator of climate change and vegetation dynamics is drawing more attention. The long-term observations of flowering events collected at scattered ground sites have accumulated valuable priority on the understanding of floral phenology, but with insufficient investigation on the spatio-temporal dynamics at regional scale, which is mainly induced by the lack of effective ways to capture the pixel-based flower events from remote sensing images. The existing yellowness indices are constructed for rape (Brassica napus L.) with less suppression to the bright background and dark green vegetation, and further with inadequate consideration on physiological characteristics and the temporal spectral signature of investigated vegetation. In this paper, we examined rape and several other representative vegetation types to determine spectral features of yellow-flower period within the growing season, then selected the visible and near-infrared bands to construct a Novel Yellowness Index (NYI) with an enhancement on the physiological mechanism of plants. The proposed NYI were discussed on the variation of mathematical properties with representative instances, cross-compared with three typical yellowness indices—Ratio Yellowness Index (RYI), Normalized Difference Yellowness Index (NDYI), and Ashourloo Canola Index (ACI) —over various yellow-flowering vegetation species at multiple scales, and validated with ground observations of three available PhenoCam network stations and field phenological observations at Görlitz, Sachsen, and Germany. In addition, we applied NYI to detect the rape field using Sentinel-2 image at Görlitz with typical rape area as a case study. Results show that the proposed NYI exhibits the potential to capture yellow-flowering events with increased sensitivity to the variation of flower density, and reduction of noise introduced by bright background or dark green vegetation of multiple vegetation species at different scales. As the flower density increases from 33% to 78%, the relative differences of NYI captured can reach up to 74%, compared with other three indices which have the relative differences no more than 57%. The cross-comparison indicates NYI performs better with higher consistent with PhenoCam observation and Deutscher Wetterdienst phenological station than other yellowness indices in capturing the variation of yellow flower density. The case study of NYI application in the identification of rape field exhibits good accuracy with the overall accuracy up to 97.5%, the Kappa coefficient of 0.94, and F score of 0.96. Consequently, the satellite-derived yellowness index will be a potential means to investigate the flowering dynamics and planting range of yellow-flowering vegetation such as rape. [ABSTRACT FROM AUTHOR]

Simulation modeling of perennial fruit tree growth, structure, and physiology over multiple years is particularly difficult and has lagged behind modeling of other crops because fruit trees are indeterminate organisms that grow over several growing seasons, vary widely among individuals, and have their structures modified by variable pruning practices. Nearly 30 yr of research have been devoted to developing a mechanistic, virtual tree model to simulate peach [Prunus persica (L.) Batsch] fruit tree growth, structure, and physiology. Details of much of this work have been published in several research papers in a variety of journals over a couple decades. The goal of this review is to report on the entire project and provide an overview of the approach we took in such an endeavor. This review contains excerpts of numerous previously published papers and some comments and conclusions about the value of the modeling that has occurred. Core Ideas: Modeling tree crops is especially difficult because they are long‐lived and highly variable.L‐systems are ideally suited to deal with the complexity of tree structure and function.Carbon partitioning in trees can be modelled as collections of semi‐autonomous organs.Similar processes can be used to model water relations of trees.Estimates of woody biomass of trees can be used to model annual dynamics of tree carbohydrate storage. [ABSTRACT FROM AUTHOR]

Tillage is one of the major threats to soil health which often results into soil physical degradation if not properly manage. Zero tillage was an alternative option from both economic point of view and environmental protection of our invaluable soil resources. The goal of the present scientific paper is to evaluate the response of different tillage systems and evapotranspiration on productivity of cowpea (Vignaunguiculata)in Nigeria. The research was conducted in Obafemi Awolowo University, Ile-Ife Osun State, Nigeria. The research used replicated randomized complete block design with treatments consisting of Zero-tillage (ZT), Reduced tillage (RT), Conventional tillage + Mulch (CT + ML) and Conventional tillage (CT). Exchangeable cations (Ca2+, Mg2+, K+ and Na+ ) were extracted with neutral solution of 1.0 M NH4OAC. The K+ and Na+ concentrations in the extract were determined using the flame photometer while Mg2+ and Ca2+ were determined using the atomic absorption. Actual evapotranspiration (ETa) was estimated using the soil water balance approach. Cowpea production on sandy loam top-soil can be optimally produced on Zero tillage system. Considering the profit over two years and the relative energy requirements, ZT system resulted in recording $ 573 profit, which was the highest profit margin among the treatments considered over the two growing seasons, RT ($ 89) had the least value. [ABSTRACT FROM AUTHOR]

The mining area in the Muli region, Qinghai Province, China, is an important source of water and an ecological security barrier in the Qilian Mountains region and has a very important ecological status. A series of ecological problems such as vegetation degradation and loss of biodiversity caused by mining have attracted widespread attention. In this paper, we used Landsat secondary data from 2000 to 2021 from the Muli region to obtain the spatial and temporal distribution characteristics of the vegetation in the Muli region by inversion of the fractional vegetation cover, above-ground biomass and the land surface phenology to comprehensively analyze the ecological changes in the vegetation in the Muli region. The results showed the following: (1) the above-ground biomass and cover of grassland in the Muli region showed a decreasing trend between 2000 and 2021, with a particularly pronounced decrease in grassland cover between 2009 and 2016; (2) the start of the vegetation growth cycle, i.e., the beginning of the vegetation growing season (SOG) became more advanced, the end of the vegetation growing season (EOG) was delayed, and the length of the growing cycle (LOG) became longer for most of the vegetation in the Muli region; (3) the results of this comprehensive analysis showed that the grassland in the Muli region showed dynamic changes with complex characteristics from 2000 to 2021, and anthropogenic disturbances had some influence on ecological indicators such as fractional vegetation cover and biomass. The extension of the vegetation growing season might be related to climate change. Based on the results of this paper, it is recommended to utilize biomass and fractional vegetation cover as indicators to assess the grass growth status of mining sites. This study analyzed the spatial and temporal characteristics of grasslands in the Muli area with several indicators, which will help relevant departments continue to improve and optimize ecological restoration measures. In addition, this study provides a reference for achieving comprehensive restoration of the ecological environment and ecological functions in mining areas. [ABSTRACT FROM AUTHOR]

Meteorological drought (MDr) causes considerable economic losses in many countries, including in relation to agriculture. To examine the diversity of seasonal meteorological drought in Poland, the study uses monthly precipitation sums in the period from March to November, collected from 74 ground-based meteorological stations in 1951–2020. The paper defines meteorological drought on the basis of the standardized precipitation index in three seasons (SPI-3) and differentiates three degrees of drought intensity: extreme, severe and moderate. The study also calculates the size of Poland's area affected by meteorological drought (AAMDr) and determines the relationship between AAMDr and SPI-3. MDr in Poland occurred more frequently in spring and autumn (every 4–5 years) than in summer (every 7 years). In the areas affected by extreme drought, precipitation was below the average, mainly ≤50% of the climatic norm, and air temperature values were below or above the average of the climatic norm, mainly ranging from −1.0 to 1.0 °C. A significant negative correlation between AAMDr and SPI-3 indices was found. The obtained results could be useful for managing climatic risk and developing regional and local agriculture adaptation plans aimed at mitigating the effects of climate change. [ABSTRACT FROM AUTHOR]

Summary: Reaction wood formation (tension wood) in trees such as poplar is a response to stress and environmental factors. Tension wood is a rich source of cellulose that can be used for products including paper or biofuels and is thus a target product in forestry. This study aimed to evaluate the formation of tension wood in two-year-old saplings of Populus alba by using alternate bending, nitrogen fertilization, and gibberellin hormone. Saplings were bent alternately in one or another direction every month during the growing season, fertilized twice at the beginning and in the middle of the growing season, and treated with gibberellin early in the growing season. The physical and anatomical characteristics of the wood were studied after the end of the growing season. Evaluation of transverse sections of specimens stained with safranin/Astra-blue showed that, compared with straight saplings, alternate bending saplings had a wider tension wood area in the growth ring and clear formation of a gelatinous layer. The wood of alternate bending saplings with nitrogen fertilization and gibberellin hormone had a higher wood density, greater longitudinal shrinkage, and less radial and tangential shrinkage than saplings with other treatments. Moreover, the alternate bending saplings treated with nitrogen fertilization and gibberellin hormone had tension wood with the largest vessels, the lowest vessel density, and the smallest total vessel lumen area than saplings with other treatments. Wood fibers of treated saplings also had the thickest wall with the smallest fiber and lumen diameters. Overall, the bending treatment with the addition of nitrogen fertilization and gibberellin hormone was the most effective for the stimulation of tension wood formation in terms of volume and intensity. [ABSTRACT FROM AUTHOR]

In Canada, the length of the frost-free season necessitates planting crops as early as possible to ensure that the plants have enough time to reach full maturity before they are harvested. Early planting carries inherent risks of cold water imbibition (specifically less than 4°C) affecting seed germination. A marker dataset developed for a previously identified Canadian soybean GWAS panel was leveraged to investigate the effect of cold water imbibition on germination. Seed from a panel of 137 soybean elite cultivars, grown in the field at Ottawa, ON, over three years, were placed on filter paper in petri dishes and allowed to imbibe water for 16 hours at either 4°C or 20°C prior to being transferred to a constant 20°C. Observations on seed germination, defined as the presence of a 1 cm radicle, were done from day two to seven. A three-parameter exponential rise to a maximum equation (3PERM) was fitted to estimate germination, time to the one-half maximum germination, and germination uniformity for each cultivar. Genotype-by-sequencing was used to identify SNPs in 137 soybean lines, and using genome-wide association studies (GWAS - rMVP R package, with GLM, MLM, and FarmCPU as methods), haplotype block analysis, and assumed linkage blocks of ±100 kbp, a threshold for significance was established using the qvalue package in R, and five significant SNPs were identified on chromosomes 1, 3, 4, 6, and 13 for maximum germination after cold water imbibition. Percent of phenotypic variance explained (PVE) and allele substitution effect (ASE) eliminated two of the five candidate SNPs, leaving three QTL regions on chromosomes 3, 6, and 13 (Chr3-3419152, Chr6-5098454, and Chr13-29649544). Based on the gene ontology (GO) enrichment analysis, 14 candidate genes whose function is predicted to include germination and cold tolerance related pathways were identified as candidate genes. The identified QTLs can be used to select future soybean cultivars tolerant to cold water imbibition and mitigate risks associated with early soybean planting. [ABSTRACT FROM AUTHOR]

The spatial and temporal variability of the main climatic indicators on the territory of the Volga Federal District in the 20th–21st centuries is considered. A general increasing trend in air temperature is revealed, and a heterogeneous pattern of precipitation changes is shown. The temperature variations until the end of the 21st century are analyzed on the example of Kazan using 40 CMIP6 climate models for four anthropogenic scenarios. In the paper, there is an assessment of the dynamics of agroclimatic resources on the territory of the Volga Federal District: the duration of the growing season, the sum of positive temperatures, total precipitation, and photosynthetic radiation. A correlation has been found between the temperature fluctuations in the region and the atmospheric circulation indices (NAO, AO, SCAND, and EAWR). For the territory of Tatarstan, a degree of aridity and waterlogging is evaluated using the agroclimatic indices: the Budyko's dryness index, the Selyaninov's hydrothermal coefficient, the Sapozhnikova's moisture index. It is shown that there is a tendency toward an increase in the duration of the growing season, its heat supply and aridity in the region in summer. A statistical estimation of the dependence of spring wheat yield on the agroclimatic indices on the territory of the Republic of Tatarstan is given. [ABSTRACT FROM AUTHOR]

Three species belonging to the fern genus Ochotopteris E. Lebedev, including the new species O. lebedevii Herman et Domogatskaya, are revised, described and illustrated in this paper. The fossils come from Albian, Cenomanian, Turonian and Coniacian beds exposed at seven sites in North-Eastern Asia and Northern Alaska. These sites are located in the Cretaceous Arctic, with their palaeolatitudes ranging from 60° N to 80° N. The high endemism characteristic of the mid-Cretaceous Arctic flora is most probably due to adaptations in the globally distinctive Arctic conditions: the unique combination of temperatures, precipitation and the highly seasonal polar light regime. Being an endemic plant of the mid-Cretaceous Arctic, Ochotopteris ferns were adapted to a regional wet temperate to a wet warm temperate palaeoclimate accompanied by marked sunlight seasonality with a prolonged—up to several weeks—winter darkness and continuous summer daylight, also lasting for several weeks. The majority of the mid-Cretaceous Arctic plants were deciduous. Their predominant deciduousness was most probably due to the polar light seasonality: at the end of the growing season, some plants dropped their leaves or leafy shoots, whereas others—including Ochotopteris ferns—died back to rhizome systems. [ABSTRACT FROM AUTHOR]

Northeast China plays a pivotal role in producing commodity grains. The precipitation and temperature distribution during the growth season is impacted by geographical and climate factors, rendering the region vulnerable to drought. However, relying on a single index does not reflect the severity and extent of drought in different regions. This research utilised the random forest (RF) model for screening remote sensing indices. Relative soil moisture (RSM) was employed to compare seven commonly used indices: the temperature vegetation dryness index (TVDI), vegetation supply water index (VSWI), vegetation condition index (VCI), temperature condition index (TCI), vegetation health index (VHI), multi-band drought index (MBDI), and normalised difference drought index (NDDI). The effectiveness of these indices for monitoring drought during different developmental stages of spring maize was evaluated. Trend rates were employed to investigate the temporal changes in drought patterns of spring maize from 2003 to 2020, and the Sen + Mann–Kendall test was used to analyse spatial variations. The results showed the following: (1) The seven remote sensing indices could accurately track drought during critical growth stages with the TVDI demonstrating higher applicability than the other six indices. (2) The application periods of two TVDIs with different parameters differed for the drought monitoring of spring maize in different developmental periods. The consistency and accuracy of the normalised difference vegetation index (NDVI)-based TVDI (TVDIN) were 5.77% and 34.62% higher than those of the enhanced vegetation index (EVI)-based TVDI (TVDIE), respectively, in the early stage. In contrast, the TVDIE exhibited 13.46% higher consistency than the TVDIN in the middle stage, and the accuracy was the same. During the later stage, the TVDIE showed significantly higher consistency and accuracy than the TVDIN with consistency increases of 9.61% and 38.64%, respectively. (3) The drought trend in northeast China increased from 2003 to 2020, exhibiting severe spring drought and a weakening of the drought in summer. The southern, southwestern, and northwestern parts of northeast China showed an upward drought trend; the drought-affected areas accounted for 37.91% of the study area. This paper identified the most suitable remote sensing indices for monitoring drought in different developmental stages of spring maize. The results provide a comprehensive understanding of the spatial–temporal patterns of drought during the past 18 years. These findings can be used to develop a dynamic agricultural drought monitoring model to ensure food security. [ABSTRACT FROM AUTHOR]

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

Copyright of Journal of Agricultural Science & Technology (1008-0864) is the property of Journal of Agricultural Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Worldwide abiotic stress factors such as excessive temperature, precipitation, drought, salinity, soil pH, greenhouse gases, ultraviolet (UVB) radiation, and air pollution pose a persistent threat to both diseases and plants affecting hostpathogen relationship depending on geographical and temporal distribution of inoculum amount and cultivars susceptibility. Leaf rust of rye, which is caused by Puccinia recondita f. sp. secalis (Roberge ex. Desmaz) has become one of the most important limiting factors for rye production in Central and Eastern Europe. During 2020-2021 growing season, a plant-pathogen interaction profile was observed on four rye genotypes in a randomized complete block design with three replications in dry area from Research and Development Station for Plant Culture on Sands Dăbuleni in south of Romania. Adult plant partial resistance was assessed through host response and epidemiological parameters as final rust severity (FRS), area under the disease progress curve (AUDPC), relative area under the disease progress curve (rAUDPC), coefficient of infection (CI) and infection rate (IR). The response of rye genotypes to leaf rust included different variation in resistance reaction ranging from moderately resistant to very susceptible. A negative and highly significant correlation of AUDPC with grain yield (r = -0.9222***) was found during 2020-2021 cropping season. [ABSTRACT FROM AUTHOR]

SAR parameters have been used many times to characterize crops. However, it was found that the scattering mechanisms derived from quad-pol SAR were different from that of the dual-pol SAR data. The objective of this study is to better understand the scattering mechanism of the maize field to dual-pol (VV, VH) SAR data and propose a new radar vegetation index to improve the inversion accuracy of the crop height. We first analyzed the temporal variation of SAR parameters before the maize height stopped increasing. It showed that the sensitivity of SAR parameters to the plant height was strong in the early stage, but the correlation became weak later. Then, according to the scattering mechanism of the maize field to the dual pol (VV, VH) SAR data, we combined use of the backscattering coefficient of σ0VH and the depolarization parameter proposed the mPRVI index. In this paper, the simple linear regression model was used to fit the six parameters separately to estimation the plant height, including σ0VH (R = 0.84), VIRatio (R = 0.82), RVI (R = 0.83), DOD+RVI (R = 0.85), PRVI (R = 0.86) and mPRVI (R = 0.88), which showed a relatively high Pearson correlation coefficient (R) with the plant height. According to adjusted coefficient of determination R2 (0.70, 0.70, 0.71, 0.74, 0.76, 0.80) and RMSE (62.8 cm, 62.7 cm, 61.8 cm, 57.5 cm, 56.3 cm, 51.2 cm) for σ0VH, VIRatio, RVI, DOD+RVI, PRVI, mPRVI, respectively, the mPRVI index outperforms other parameters throughout the maize growing season. And this outperformance is not only manifested in the early growth stage of the maize, but also in the later stage before the plant height stopped increasing. [ABSTRACT FROM AUTHOR]

Analyses of climate change based on point observations indicate an extension of the plant growing season, which may have an impact on plant production and functioning of natural ecosystems. Analyses involving remote sensing methods, which have added more detail to results obtained in the traditional way, have been carried out only since the 1980s. The paper presents the results of a bibliometric analysis of papers related to the growing season published from 2000–2021 included in the Web of Science database. Through filtering, 285 publications were selected and subjected to statistical processing and analysis of their content. This resulted in the identification of author teams that mostly focused their research on vegetation growth and in the selection of the most common keywords describing the beginning, end, and duration of the growing season. It was found that most studies on the growing season were reported from Asia, Europe, and North America (i.e., 32%, 28%, and 28%, respectively). The analyzed articles show the advantage of satellite data over low-altitude and ground-based data in providing information on plant vegetation. Over three quarters of the analyzed publications focused on natural plant communities. In the case of crops, wheat and rice were the most frequently studied plants (i.e., they were analyzed in over 30% and over 20% of publications, respectively). [ABSTRACT FROM AUTHOR]

The relevance of this study is determined by the need to optimize the production process of agrocenoses of spring rapeseed and establish the regularities of the dynamics of macroelements in the soil under the influence of different rates of mineral fertilisers. In this regard, the purpose of this paper was to cover the regularities of changes in the content of macroelements in typical low-humus chernozems at different stages of spring rapeseed culture development in the conditions of the Right Bank Forest Steppe of Ukraine. Field, laboratory, analytical, and statistical research methods were used in the study. It was established that the highest content of macroelements in the soil at all levels of mineral fertiliser is in the phase of leaf rosette formation by spring rapeseed plants (BBCH 15-18). As plants grow through the phases, it decreases and reaches minimum values in the ripening phase (BBCH 85-88). The highest content of nitrogen mineral compounds was noted in BBCH 15-18: 52.0-60.2 mg/kg of soil depending on the fertiliser variant, the content in the variant without fertiliser application - 49.8 mg/kg of soil. It was found that the maximum content of mobile phosphorus compounds in the soil was recorded in the first half of the growing season. It was found that the content of mobile potassium in the soil is dictated by the amount of applied mineral fertilisers. The highest content was noted at the beginning of the vegetation of spring rapeseed, with a gradual decrease until the seed ripening phase (BBCH 85-88). A close correlation was established between the accumulation of dry matter in the BBCH 55-58 period and the yield level (r=0.91). The materials of this paper are of practical value for the improvement of processes related to the development of the productivity of spring rapeseed crops in the conditions of the Forest Steppe of Ukraine, as well as the rational use of mineral fertilisers on typical low-humus chernozems. [ABSTRACT FROM AUTHOR]

Bean germplasm collection of Vegetable Research and Development Station Buzău, Romania, contain over 450 accessions. The maintenance of this collection must accomplish the following requirements: maintaining the variability of this species (Phaseolus vulgaris L.), creating new varieties and adaptability to the climate changes in what it concerns these accessions. In 2020, this collection was cultivated in green - house covered with polyethylene. This paper presents the comparative study of 10 climbing bean seeds accessions. The seeds of each accession were evaluated in what it concerns quantitative (100 seed weight, length, thickness and width) and qualitative characteristics (seed colour, brilliance, veining and shape). The seeds weight varied between 57.57 g (V5) and 28.88 g (V3). More than half of the seeds variants taken into study, presented white colour, except: V1 and V3 - different beige and V5 presents 2 colours (half white, half dark red). The highest values regarding seeds length and width were registered at V10 (17.03 and 9.11 mm). All accessions presented are stabile and it presented stability during the last growing seasons. [ABSTRACT FROM AUTHOR]

The paper considers the peculiarities of the climate change influence on the dynamics of drought development in Ukraine. The analysis was performed for average long-term climatic conditions during the growing season (1981-2020) and under climate change scenarios RCP 4.5 and RCP 8.5 for the period of 2021-2050 (for the period as a whole and by the decades: 2021-2030, 2031-2040, 2041-2050). The drought development was studied over relatively short periods of time (ten days) at the main agroclimatic regions of Ukraine (Polissia, Forest-Steppe, Northern and Southern Steppe). The assessment of the aridity of ten-day periods was accomplished by means of a set of aridity indicators by Selyaninov, Shashko, Budagovskiy and Bova, which corrects and supplements each other; this made it possible to consider in detail the genesis of climate-induced drought in the agroclimatic regions of Ukraine. Analysis of the study results showed that the development of drought conditions in all agroclimatic regions is expected as early as in the first decade (2021-2030). According to both scenarios, from 4-6 in Polissia to 16-17 severe and very severe droughts in the Southern Steppe are expected. In the second decade (2031-2040), under RCP4.5, improvement in moistening conditions is expected in Polissia and Forest-Steppe and under RCP8.5, an increase in the level of aridity is expected in these agroclimatic regions. In the Northern Steppe and Southern Steppe the number of moderately, very and extremely dry ten-day periods will increase (from 9 to 17). In the third decade (2041-2050), under the RCP4.5 scenario, very severe aridity conditions are assumed in all agroclimatic regions. Under RCP8.5, good moistening conditions and, according to both criteria, a small number of dry ten-day periods are expected in Polissia and Forest-Steppe. As for the conditions at the Northern and Southern Steppes very severe drought conditions are expected (from 8 to 17 ten-day periods with moderate, severe and very severe drought). For 2021-2050 on the whole, there will be an increase in aridity during the growing season in all agroclimatic regions of Ukraine. [ABSTRACT FROM AUTHOR]

The susceptibility of 14 pear cultivars to the bacterium Pseudomonas syringae pv. syringae, the causal agent of bacterial blast, was evaluated using three different methods of in vivo inoculation detached shoots inoculation in a growth chamber, and terminal shoot and blossom inoculation of potted trees in a net house in the period 2020-2022. The 20-week assessment of infection symptoms in the net house showed different dynamics of disease development depending on the inoculation method, the weather during the growing season and the susceptibility of the pear cultivars. Most of the cultivars were during the study low susceptible to pathogen and were classified in blossom, terminal as well as detached shoot susceptibility class 2. The European cultivar Kiefer was the least susceptible (susceptibility class 1) to blossom infection, the Asian cultivars Chojuro and Ya Li to terminal shoot infection, and Ya Li to detached shoot infection. The European cultivar William's was the most susceptible to all types of infection, being classified in class 3, moderately susceptible cultivars to infection of terminal shoots, and class 4, highly susceptible cultivars to infection of blossoms and detached shoots. The assessment of susceptibility of pear cultivars to Pseudomonas syringae pv. syringae in the net house approximated conditions as close as possible to the condition in orchards and should thus be consistent in plantings with similar environmental and weather conditions. [ABSTRACT FROM AUTHOR]

Drought seriously endangers the development of agro‐pastoral ecotone in arid and semi‐arid regions. However, drought evolution characteristics of semi‐arid sandy grassland and its drivers are not well understood in the complex climate change context. Thus, in this paper, the revised standardized precipitation evaporation indices on one‐month (SPEI‐1) and growing‐season (SPEI‐6) scale, flash drought and dry spells (DS) were calculated as drought indicators, and the temporal variabilities and meteorological drivers of drought in Horqin Sandy Land during the growing period (April–September) from 2007 to 2021 were studied. The results showed that SPEI‐1 and SPEI‐6 exhibited negative trends and periodic change. This drought aggravation was manifested in increased grades and numbers of drought months. Flash droughts can occur every month during the growing season. And its occurrence was not only positively correlated with all drought events in frequency but also synchronized in time. The increased number of DS showed an asymmetrical shift towards 7‐day‐and‐longer DS. SPEI sensitivity to precipitation (P) was noticeably higher than to atmospheric evapotranspiration demand (AED) at both monthly and growing season scales. SPEI sensitivity to AED was modulated by P amounts, which was higher during low P period. Apart from the amounts of P and AED, their temporal variability also strongly determined how they affect the drought severity. P was also the main driver for flash drought and long DS, but AED with larger amount and higher variability is the reason for their aggravation. Our results demonstrate the complexity of drought intensification in semi‐arid sandy grasslands and highlight the important role of AED anomalies in it. [ABSTRACT FROM AUTHOR]

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

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

Purpose: To evaluate the effects of enhanced nitrogen (N) load on turnover of phosphorus (P) in Suaeda salsa marsh in the Yellow River estuary, the variation and allocation of P in the plant-soil system were investigated in the growing season. Methods: This study was explored by field N addition experiment which included four load levels: NNL (no N load treatment, 0 gN m−2 yr−1), LNL (low N load treatment, 3.0 gN m−2 yr−1), MNL (medium N load treatment, 6 gN m−2 yr−1), and HNL (high N load treatment, 12 gN m−2 yr−1). Results: In most sampling periods, the TP contents in soils in the LNL, MNL, and HNL treatments showed a decreasing trend compared to the NNL treatment. With increasing N load levels, the contents of non-available decomposed P in soils decreased by 3.08 ~ 5.22%, while those of easily available and moderately available P increased by 0.36 ~ 8.92% and 1.21 ~ 24.24%, respectively. The variations of NaOH-Po, Resin-Pi, and NaHCO3-Po contents primarily rested with the duration of N import, while those of NaOH-Pi, Residual-P, NaHCO3-Pi, and HCl-Pi contents mainly depended on the levels of N load. Dissimilar variations of TP contents in plant tissues in the growing season were observed among N load levels, which were dependent on the structure and function of organs and the nutrient function of P at distinct growth stages. The P absorption coefficients (PAC) of plants in N load treatments increased by 31.82 ~ 36.36%, while the P utilization coefficients (PUC) decreased by 4.96 ~ 13.33%. Conclusion: This paper found that the S. salsa was very likely to adjust its growth rhythm and P absorption/utilization capacity to adapt N load environment. Particularly, as N load reached medium level, the P supply relationships between aboveground and belowground tissues and the P transferences in the plant-soil system were greatly altered, indicating that the S. salsa might have a special response to the medium N enrichment. Thus, the potential impacts of medium N load level on S. salsa marsh should be emphasized in the future. [ABSTRACT FROM AUTHOR]

This paper provides new evidence on the validity of using expert ratings of wine as a measure of wine quality for predicting the effects of climate change on the wine industry. We used Bob Campbell's ratings of New Zealand wines to look for a relationship between the ratings and climatic variables that predicts a plausible optimal growing-season temperature for the main wine varieties and wine regions in New Zealand. Such a relationship can be used to forecast the effects of climate change on wine quality to better understand when wineries need to adapt to a warming climate. We used both individual wine ratings and overall vintage ratings, averaged by region and variety from the individual ratings, to compare in a controlled setting their success in predicting plausible optimal temperatures. We find that using the vintage ratings produces substantially more precise and plausible findings than using the individual ratings. We conclude that there is great potential in using vintage data constructed from expert ratings for individual wines for climate change research. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to evaluate the Dual Use (DU) Option – a crop insurance policy created by the 2018 Farm Bill – relative to other policies available to dual-purpose annual forage producers. The new policy combines existing rainfall-based policies for annual forage crops and multi-peril policies for grain, allowing coverage for multiple crop uses on the same acres during the same growing season. Design/methodology/approach: The paper uses a simulation model to examine crop insurance choices for a typical Texas dual-purpose wheat farm. The certainty equivalent (CE) of wealth is used to rank choices within and between three insurance plans and to analyze the effects of those choices over a range of producer risk aversion levels and for three cases of yield expectations. Findings: The DU Option is more preferred as risk aversion increases, but it is not universally preferred. Therefore, while the policy can be a viable risk management tool, certain restrictions may be limiting its effectiveness. Practical implications: The findings of this paper can help explain farm-level decision making related to dual-purpose annual forage crop insurance program choices. Originality/value: This paper contributes to the literature by documenting a new crop insurance program made available in the 2018 Farm Bill and provides insights into producers' possible choices by evaluating extensive scenarios. [ABSTRACT FROM AUTHOR]

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

The Soybean Free Air Concentration Enrichment (SoyFACE) facility is the longest running open-air carbon dioxide and ozone enrichment facility in the world. For over two decades, soybean, maize, and other crops have been exposed to the elevated carbon dioxide and ozone concentrations anticipated for late this century. The facility, located in East Central Illinois, USA, exposes crops to different atmospheric concentrations in replicated octagonal ~280 m2 Free Air Concentration Enrichment (FACE) treatment plots. Each FACE plot is paired with an untreated control (ambient) plot. The experiment provides important ground truth data for predicting future crop productivity. Fumigation data from SoyFACE were collected every four seconds throughout each growing season for over two decades. Here, we organize, quality control, and collate 20 years of data to facilitate trend analysis and crop modeling efforts. This paper provides the rationale for and a description of the SoyFACE experiments, along with a summary of the fumigation data and collation process, weather and ambient data collection procedures, and explanations of air pollution metrics and calculations. [ABSTRACT FROM AUTHOR]

The WINDS (Water-Use, Irrigation, Nitrogen, Drainage, and Salinity) model was developed to provide decision support for irrigated-crop management in the U.S. Southwest. The model uses a daily time-step soil water balance (SWB) to simulate the dynamics of water content in the soil profile and evapotranspiration. The model employs a tipping bucket approach during infiltration events and Richards' equation between infiltration events. This research demonstrates WINDS simulation of a furrow-irrigated cotton experiment, conducted in 2007 in central Arizona, U.S. Calibration procedures for WINDS include the crop coefficient curve or segmented crop coefficient curve, rate of root growth, and root activity during the growing season. In this research, field capacity and wilting point were measured in the laboratory at each location and in each layer. Field measurements included water contents in layers by neutron moisture meter (NMM), irrigation, crop growth, final yield, and actual ETc derived by SWB. The calibrated WINDS model was compared to the neutron probe moisture contents. The average coefficient of determination was 0.92, and average root mean squared error (RMSE) was 0.027 m3 m−3. The study also demonstrated WINDS ability to reproduce measured crop evapotranspiration (ETc actual) during the growing season. This paper introduces the online WINDS model. [ABSTRACT FROM AUTHOR]

[Objective] Nitrification inhibitors have been increasingly used over the last decades to reduce nitrogen loss from soil. The objective of this paper is to investigate the combined influence of irrigation and nitrification inhibitors on ammonia volatilization and enzymatic activity in soil. [Objective] The experiment was conducted in a summer maize field using 3,4-dimethylpyrazole phosphate (DMPP) as the nitrification inhibitor. There were four treatments: conventional subsurface drip irrigation with (DI+DMPP) and without (DI+NO) applying DMPP, alternate subsurface drip irrigation with (ADI+DMPP) and without (ADI+NO) applying DMPP. In each treatment, we measured the ammonia volatilization rate at different growing stages, accumulation of ammonia volatilization over the whole growth season, as well as enzymatic activities in the soil. [Result] Irrigation method and DMPP both affected NH3 volatilization, but the effect varied with growing stage. Applying DMPP increased ammonia volatilization rate significantly at jointing stage, heading stage, and filling stage, regardless of the irrigation method. It was found that the alternate drip irrigation reduced ammonia volatilization rate significantly but only at the booting stage. Compared to DI treatments, ADI treatments reduced ammonia volatilization accumulation by 12.70%~45.45%, but applying DMPP increased ammonia volatilization from both irrigation treatments significantly. At the heading stage, ADI treatments improved the activities of catalase, alkaline phosphatase and FDA hydrolase in the root zone, but had no significant effect on urease activity. Applying DMPP did not show a noticeable effect on enzymatic activity in the root zone. [Conclusion] Alternate surface drip irrigation without applying nitrification inhibitors can effectively reduce ammonia volatilization and nitrogen loss. It can be used as an improved agronomic method for sustainable production of maize in the studied area. [ABSTRACT FROM AUTHOR]

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

Arctic tundra consists of diverse habitats that differ in dominant vegetation, soil moisture regimes, and relative importance of organic vs. inorganic nutrient cycling. The Arctic is also the most rapidly warming global area, with winter warming dominating. This warming is expected to have dramatic effects on tundra carbon and nutrient dynamics. We completed a meta‐analysis of 166 experimental warming study papers to evaluate the hypotheses that warming changes tundra biogeochemical cycles in a habitat‐ and seasonally specific manner and that the carbon (C), nitrogen (N), and phosphorus (P) cycles will be differentially accelerated, leading to decoupling of elemental cycles. We found that nutrient availability and plant leaf stoichiometry responses to experimental warming were variable and overall weak, but that both gross primary productivity and the plant C pool tended to increase with growing season warming. The effects of winter warming on C fluxes did not extend into the growing season. Overall, although warming led to more consistent increases in C fluxes compared to N or P fluxes, evidence for decoupling of biogeochemical cycles is weak and any effect appears limited to heath habitats. However, data on many habitats are too sparse to be able to generalize how warming might decouple biogeochemical cycles, and too few year‐round warming studies exist to ascertain whether the season under which warming occurs alters how ecosystems respond to warming. Coordinated field campaigns are necessary to more robustly document tundra habitat‐specific responses to realistic climate warming scenarios in order to better understand the mechanisms driving this heterogeneity and identify the tundra habitats, communities, and soil pools most susceptible to warming. [ABSTRACT FROM AUTHOR]

In this paper, we propose an innovative approach for robust prediction of processing tomato yield using open-source AutoML techniques and statistical analysis. Sentinel-2 satellite imagery was deployed to obtain values of five (5) selected vegetation indices (VIs) during the growing season of 2021 (April to September) at 5-day intervals. Actual recorded yields were collected across 108 fields, corresponding to a total area of 410.10 ha of processing tomato in central Greece, to assess the performance of Vis at different temporal scales. In addition, VIs were connected with the crop phenology to establish the annual dynamics of the crop. The highest Pearson coefficient (r) values occurred during a period of 80 to 90 days, indicating the strong relationship between the VIs and the yield. Specifically, RVI presented the highest correlation values of the growing season at 80 (r = 0.72) and 90 days (r = 0.75), while NDVI performed better at 85 days (r = 0.72). This output was confirmed by the AutoML technique, which also indicated the highest performance of the VIs during the same period, with the values of the adjusted R2 ranging from 0.60 to 0.72. The most precise results were obtained with the combination of ARD regression and SVR, which was the most successful combination for building an ensemble (adj. R2 = 0.67 ± 0.02). [ABSTRACT FROM AUTHOR]