Spatiotemporal distribution of Ascochyta pinodes and Ascochyta pinodella during the winter growing season in France

2018 ◽  
Vol 67 (5) ◽  
pp. 1031-1045 ◽  
Author(s):  
C. Le May ◽  
M. I. Chilvers ◽  
A. L. Saucereau ◽  
M. Guibert ◽  
T. L. Peever
Keyword(s):  
Growing Season ◽  
Spatiotemporal Distribution ◽  
Ascochyta Pinodes

scholarly journals A Machine Learning Method for Predicting Vegetation Indices in China

2021 ◽  
Vol 13 (6) ◽  
pp. 1147
Author(s):  
Xiangqian Li ◽  
Wenping Yuan ◽  
Wenjie Dong
Keyword(s):  
Machine Learning ◽  
Growing Season ◽  
Crop Growth ◽  
Spatiotemporal Distribution ◽  
Coefficient Of Determination ◽  
Gradient Boosting ◽  
Severe Drought ◽  
Vegetation Growth ◽  
Extreme Gradient Boosting ◽  
Boosting Method

To forecast the terrestrial carbon cycle and monitor food security, vegetation growth must be accurately predicted; however, current process-based ecosystem and crop-growth models are limited in their effectiveness. This study developed a machine learning model using the extreme gradient boosting method to predict vegetation growth throughout the growing season in China from 2001 to 2018. The model used satellite-derived vegetation data for the first month of each growing season, CO2 concentration, and several meteorological factors as data sources for the explanatory variables. Results showed that the model could reproduce the spatiotemporal distribution of vegetation growth as represented by the satellite-derived normalized difference vegetation index (NDVI). The predictive error for the growing season NDVI was less than 5% for more than 98% of vegetated areas in China; the model represented seasonal variations in NDVI well. The coefficient of determination (R2) between the monthly observed and predicted NDVI was 0.83, and more than 69% of vegetated areas had an R2 > 0.8. The effectiveness of the model was examined for a severe drought year (2009), and results showed that the model could reproduce the spatiotemporal distribution of NDVI even under extreme conditions. This model provides an alternative method for predicting vegetation growth and has great potential for monitoring vegetation dynamics and crop growth.

Random isn't real: How the patchy distribution of ecological rewards may generate “incentive hope”

2019 ◽  
Vol 42 ◽  
Author(s):  
Laurel Symes ◽  
Thalia Wheatley
Keyword(s):  
Natural Environment ◽  
Random Distribution ◽  
Spatiotemporal Distribution ◽  
Patchy Distribution ◽  
Distribution Of Resources

AbstractAnselme & Güntürkün generate exciting new insights by integrating two disparate fields to explain why uncertain rewards produce strong motivational effects. Their conclusions are developed in a framework that assumes a random distribution of resources, uncommon in the natural environment. We argue that, by considering a realistically clumped spatiotemporal distribution of resources, their conclusions will be stronger and more complete.

Growing season

1992 ◽  
Author(s):  
Nicholas Wellington
Keyword(s):  
Growing Season

Irrigation regime and water consumption of potatoes in the Republic of Bashkortostan, depending on the reclamation condition of lands

2020 ◽  
Vol 0 (6) ◽  
pp. 13-19
Author(s):  
Guzel Gumerova ◽  
Georgiy Gulyuk ◽  
Dmitry Kucher ◽  
Anatoly Shuravilin ◽  
Elena Piven
Keyword(s):  
Water Consumption ◽  
Weather Conditions ◽  
Growing Season ◽  
Vegetation Period ◽  
Forest Steppe ◽  
Total Water ◽  
Total Water Consumption ◽  
Republic Of Bashkortostan ◽  
Irrigated Lands ◽  
The Republic

Data of long-term researches (2015–2018) in southern forest-steppe zone of the Republic of Bashkortostan, is justified theoretically and experimentally the mode of irrigation of potatoes on leached chernozems of unsatisfactory, satisfactory and good ameliorative condition of irrigated lands. For the growing periods of potatoes with different heat and moisture supply, the number of watering, the timing of their implementation, irrigation and irrigation norms are established. On lands with unsatisfactory meliorative state the number of irrigation depending on weather conditions of potato vegetation period varied from 0 to 3 (1.5 on average) with average irrigation norm – 990 m3/ha. With satisfactory meliorative state of lands the number of irrigation on average increased from 0 to 4 (2.3 on average) with irrigation norm – 1305 m3/ha. On lands with good meliorative state the number of irrigation was the highest – from 1 to 5 (3 on average) with average irrigation irrigation norm is 1653 m3/ha. It was noted that in the dry periods of potato vegetation the greatest number of watering was carried out (3–5 watering), and in the wet periods (2017) watering was not carried out except for the area with a good reclamation state, where only one irrigation was carried out by the norm of 550 m3/ha. Water consumption of potato was studied in dynamics as a whole during the growing season and the months of the growing season depending on weather conditions of vegetation period and land reclamation condition of irrigated lands, as well as in the control (without irrigation). The lowest total water consumption was in the area without irrigation and averaged 226.8 mm. In irrigated areas, its values increased to 319-353.4 mm. The average daily water consumption varied from 2.12 to 3.3 mm. The highest rates of potato water consumption were observed in June and July, and the lowest – in May and August. In the total water consumption of potatoes on the site without irrigation, the largest share was occupied by atmospheric precipitation and in addition to them the arrival of moisture from the soil. Irrigation water was used in irrigated areas along with precipitation, the share of which was 30.2–46.1 %.

Spatiotemporal distribution of foraging in a marine predator: behavioural drivers of hotspot formation

2020 ◽  
Vol 635 ◽  
pp. 187-202
Author(s):  
T Brough ◽  
W Rayment ◽  
E Slooten ◽  
S Dawson
Keyword(s):  
Time Of Day ◽  
Spatiotemporal Distribution ◽  
Temporal Effects ◽  
Marine Predator ◽  
Marine Predators ◽  
Additive Mixed Models ◽  
Density Analysis ◽  
The Times ◽  
Passive Acoustic ◽  
Spatial Locations

Many species of marine predators display defined hotspots in their distribution, although the reasons why this happens are not well understood in some species. Understanding whether hotspots are used for certain behaviours provides insights into the importance of these areas for the predators’ ecology and population viability. In this study, we investigated the spatiotemporal distribution of foraging behaviour in Hector’s dolphin Cephalorhynchus hectori, a small, endangered species from New Zealand. Passive acoustic monitoring of foraging ‘buzzes’ was carried out at 4 hotspots and 6 lower-use, ‘reference areas’, chosen randomly based on a previous density analysis of visual sightings. The distribution of buzzes was modelled among spatial locations and on 3 temporal scales (season, time of day, tidal state) with generalised additive mixed models using 82000 h of monitoring data. Foraging rates were significantly influenced by all 3 temporal effects, with substantial variation in the importance and nature of each effect among locations. The complexity of the temporal effects on foraging is likely due to the patchy nature of prey distributions and shows how foraging is highly variable at fine scales. Foraging rates were highest at the hotspots, suggesting that feeding opportunities shape fine-scale distribution in Hector’s dolphin. Foraging can be disrupted by anthropogenic influences. Thus, information from this study can be used to manage threats to this vital behaviour in the locations and at the times where it is most prevalent.

Dynamics of CO2 emission from chernozems under agricultural use

2017 ◽  
Vol 4 (3) ◽  
pp. 43-49
Author(s):  
M. Miroshnychenko ◽  
O. Siabruk
Keyword(s):  
Carbon Dioxide ◽  
Agricultural Practices ◽  
Growing Season ◽  
Warm Period ◽  
Direct Seeding ◽  
Soil Tillage ◽  
Plant Residues ◽  
Hydrothermal Conditions ◽  
Organic Mineral ◽  
Mineral System

Aim. The comparison of the effect of hydrothermal conditions and various agricultural practices on the emission of CO 2 from chernozems in the Left-Bank Forest-Steppe of Ukraine. Methods. The dynamics of the intensity of carbon dioxide emissions from chernozem calcic (typical chernozem – in Ukrainian classifi cation) was studied during the growing season of 2011–2012. The observations were based on two fi eld experiments with various methods of soil till- age (6–7 years from the beginning of the experiment) and fertilization systems (21–22 years from the beginning of the experiment). Particularly, plowing at 20–22 cm, disking at 10–12 cm, cultivation at 6–8 cm and direct seeding using Great Plains drill were studied among the soil tillage methods. Mineral system (N 45 P 50 K 45 ), organic system (manure 8 t/ha) and combined organic-mineral system (manure 8 t/ha + N 45 P 50 K 45 ) were studied among fertilization systems. The intensity of CO 2 fl ux was determined using the non-stationary respiratory chambers by the alkaline absorption method, with averaging of the results during the day and the frequency of once a month. Results. During the warm period, the emission of carbon dioxide from the soil changes dynamically depending on temperature and humidity. The maximum of emission coincides with the periods of warm summer showers in June-July, the minimum values are characteristic for the late autumn period. The total emission losses of carbon in chernozems over the vegetation period ranged from 480 to 910 kg/ha and varied depending on the methods of tillage ± (4.0–6.0) % and fertilization systems ± (3.8–7.1) %. The changes in the intensity of CO 2 emission from the soil under different methods of soil tillage are associated with hydrothermal regime and the depth of crop residues location. The biggest difference is observed im- mediately after tillage, but in the spring period the differences are only 12–25 %, and after drying of the top layer of soil become even less. Direct seeding technology provides the greatest emission of CO 2 from chernozem, which is fa- cilitated by better water regime and more complete mineralization of plant residues on the soil surface. Annual losses of carbon are the least under disking of soil at 10–12 cm. The changes in the intensity of CO 2 emission from the soil under different fertilization systems are associated with the involvement of the additional organic matter from plant residues and manure to the microbiological decomposition. The greatest emission was observed under the organic- mineral fertilization system, which increased the loss of carbon by 7–8 % in comparison with the mineral system in the unfavorable hydrothermal year and by 11–15 % in the more favorable year. These differences are observed mainly during the fi rst half of the growing season when there is a clear tendency to increase the intensity of soil respiration. Conclusions. The hydrothermal conditions of the warm period of the year are decisive in the formation of the CO 2 emission fl ow from chernozems. Due to the improvement of agricultural practices, emissions might be reduced but not more that by 15 % of natural factor contribution.

Irrigation scheduling and water requirements for cowpea using evaporation pan at middle of Iraq

1970 ◽  
pp. 13-17
Author(s):  
Saifuldeen A. Salim ◽  
Isam Kudhier Hamza ◽  
Laith Farhan Jar
Keyword(s):  
Water Productivity ◽  
Irrigation Treatment ◽  
Growing Season ◽  
Irrigation Scheduling ◽  
Water Requirements ◽  
Applied Water ◽  
Fresh Seed ◽  
Irrigation Interval ◽  
Biological Yield ◽  
Evaporation Pan

The present study was conducted to find out the water requirements and most suitable irrigation frequencies for cowpea (Vigna unguiculata L.) var grown under drip irrigation. The treatments were based on the IW:CPE ratio at different empirical pan factors 0.6 , 0.8, 1.0, 1.,1.4 , and 1.6 Ef (where Ef = IW/CPE). It was observed that the irrigation interval was variable values decreased by increasing Ef value and with the progress of the growing season. The 1.2 and 1.0 IW: CPE treatments with approximately 4 days irrigation interval were achieved the best results. The total amount of applied water during Cowpea growing season was varied between 247.7 and 266.5mm with 254.8mm as a mean. Irrigation treatment with Ef1.2 was superior over the rest of other treatments in fresh seed yield (5.13 ton.hec.-1), crop water productivity (2.14 kg.m-3), biological yield (6.88 ton.hec.-1) , fresh pod yield (7.33 ton.hec.-1), weight of 100 seed (31.28gm), number of seed/pod (9.34) and netting percentage (37.1). The lowest values of the most parameters used in this study were obtained by Ef 0.6 irrigation treatment.  

Improvement of separate elements of the techno-logy of cultivation of white cabbage in the conditions of the of the central region of the non-chernozem zone

2020 ◽  
Author(s):  
A.V. Konstantinovich ◽  
◽  
A.S. Kuracheva ◽  
E.D. Binkevich
Keyword(s):  
Seed Treatment ◽  
Unit Area ◽  
Growing Season ◽  
Agricultural Products ◽  
Stress Factors ◽  
High Quality ◽  
Temperature And Precipitation ◽  
White Cabbage ◽  
Sowing Seed

In conditions of climate change, when temperature and precipitation fluctuations occur more and more frequently during the growing season, it is necessary to obtain high quality seedlings with "immunity" to various stress factors, including high weediness, the damage from which is associated with a decrease in yield (by 25 -35%) and with a deterioration in the quality of agricultural products. Due to the imbalance in production technology, seedlings are often weakened, overgrown, with a low yield per unit area and survival rate in the field. One of the solutions to this problem is the use of PP for pre-sowing seed treatment to increase the competitiveness of seedlings in the field.

Experience of soybean cultivation in the Kaluga Department of Agricultural Machinery SC.

2020 ◽  
Author(s):  
N.V. Sergeev ◽  
◽  
A.Yu. Pivkin
Keyword(s):  
Seed Yield ◽  
Growing Season ◽  
Climatic Conditions ◽  
High Yield ◽  
Soybean Variety ◽  
Agricultural Machinery ◽  
Kaluga Region ◽  
High Seed Yield

The experience of cultivation of soybeans in SC "Agricultural machinery" of the Kaluga region on an area of 190 hectares shows that the soybean variety Alaska is sufficiently adapted to the soil and climatic conditions of this region, provides a high seed yield (up to 32 c / ha) and a high yield (up to 1344 kg / ha) relatively inexpensive protein. However, this variety has a long growing season (95-105 days) and therefore desiccation of crops is required for harvesting for seeds.

CULTIVATION TECHNOLOGY ELEMENTS INFLUENCE ON NEW SPRING BARLEY BREWING VARIETIES YIELDS

1970 ◽  
pp. 21-25
Author(s):  
O. A. Artyukhova ◽  
O. V. Gladysheva ◽  
V. A. Svirina
Keyword(s):  
Growth And Development ◽  
Spring Barley ◽  
Photosynthetic Apparatus ◽  
Growing Season ◽  
Biological Indicators ◽  
Mineral Fertilizers ◽  
Mass Growth ◽  
Green Mass ◽  
Yield Structure ◽  
Cultivation Technology

The effect of applying various norms of mineral fertilizers on the biological indicators of crop plants during their growth and development in the Central non-black earth region in 2017-2019 was studied on the varieties of spring barley Vladimir, Reliable and Yaromir.such indicators as plant height, photosynthetic apparatus area, green mass growth, and elements of the yield structure were Studied. It was revealed that on average during the growing season, when the norms of mineral fertilizers were increased, the area of leaf plates increased and, as a result, the increase in green mass growth relative to the control variants increased by 56.3 % at (NРК)30, 82.3 % at (NРК)60, and 126.7 % at (NРК)90. The introduction of mineral fertilizers also influenced the formation of the crop structure. There was an increase in the tillering coefficient of varieties by 15.7%, 5.7 % and 21.3 % (Vladimir, Reliable and Yaromir, respectively) relative to the control, an increase in the number of grains in the ear from 15.1 to 22.4 PCs., the weight of 1000 grains from 48.0 to 55.7 g. and the weight of grain per ear from 0.7 to 1.2 g. There was a strong correlation between the doses of mineral fertilizers and the grain yield from + 0.80 to +1.0, and the variability was calculated.      

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