Temperature-related Variables Associated with Yield of ‘Kerman’ Pistachio in the San Joaquin Valley of California

Information on how annual pistachio yield is affected by air temperature (Ta) during the winter and growing season is lacking. Timely advance knowledge of the magnitude of the yield of the California pistachio harvest would be beneficial for the pistachio industry for efficient allocation of harvest and postharvest resources, such as personnel, harvesting machinery, trucks, processing facility capacity, crop storage facilities, and for making marketing decisions. The objective of this study was to identify parameters, especially Ta variables and time periods, calculated from Ta data during the previous fall, winter, spring, and summer, that were associated most closely with fall nut-crop yield. The premise of this study was that sequential, historical yield records could be regressed against a number of Ta-derived variables to identify Ta thresholds and accumulations that have value in explaining past and predicting subsequent nut yield. Of the 27 regression variables examined in this study, the following, which were all negatively correlated with subsequent yield, explained the greatest proportion of the variability present in predicting yield of ‘Kerman’ pistachio: yield of the previous-year harvest, hourly Ta accumulations above 26.7 or 29.4 °C from the time period between 20 Mar. and 25 Apr., hourly Ta accumulations below 7.2 °C from 15 Nov. to 15 Feb., and hourly Ta accumulations above 18.3 °C from 15 Nov. to 15 Feb.

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Modelling of Soil Respiration in Hungary

Agrokémia és Talajtan ◽

10.1556/agrokem.55.2006.1.7 ◽

2006 ◽

Vol 55 (1) ◽

pp. 59-68 ◽

Cited By ~ 1

Author(s):

Ferenc Ács ◽

H. Breuer

Keyword(s):

Soil Respiration ◽

Water Balance ◽

Air Temperature ◽

Sandy Loam ◽

Growing Season ◽

Biogeochemical Model ◽

Clay Loam ◽

Water Balance Components ◽

Linear Relationships ◽

Time Periods

The climatology of soil respiration in Hungary is presented. Soil respiration is estimated by a Thornthwaite-based biogeochemical model using soil hydrophysical data and climatological fields of precipitation and air temperature. Soil respiration fields are analyzed for different soil textures (sand, sandy loam, loam, clay loam and clay) and time periods (year, growing season and months). Strong linear relationships were found between soil respiration and the actual evapotranspiration for annual and growing season time periods. In winter months soil respiration is well correlated with air temperature, while in summer months there is a quite variable relationship with water balance components. The strength of linear relationship between soil respiration and climatic variables is much better for coarser than for finer soil texture.

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Exploring seasonal and regional relationships between the Evaporative Stress Index and surface weather and soil moisture anomalies across the United States

Hydrology and Earth System Sciences ◽

10.5194/hess-22-5373-2018 ◽

2018 ◽

Vol 22 (10) ◽

pp. 5373-5386 ◽

Cited By ~ 5

Author(s):

Jason A. Otkin ◽

Yafang Zhong ◽

David Lorenz ◽

Martha C. Anderson ◽

Christopher Hain

Keyword(s):

Soil Moisture ◽

Vapor Pressure ◽

Air Temperature ◽

Vapor Pressure Deficit ◽

Growing Season ◽

The United States ◽

Dew Point ◽

Stress Index ◽

The Us ◽

Time Periods

Abstract. This study uses correlation analyses to explore relationships between the satellite-derived Evaporative Stress Index (ESI) – which depicts standardized anomalies in an actual to reference evapotranspiration (ET) fraction – and various land and atmospheric variables that impact ET. Correlations between the ESI and forcing variable anomalies calculated over sub-seasonal timescales were computed at weekly and monthly intervals during the growing season. Overall, the results revealed that the ESI is most strongly correlated to anomalies in soil moisture and 2 m dew point depression. Correlations between the ESI and precipitation were also large across most of the US; however, they were typically smaller than those associated with soil moisture and vapor pressure deficit. In contrast, correlations were much weaker for air temperature, wind speed, and radiation across most of the US, with the exception of the south-central US where correlations were large for all variables at some point during the growing season. Together, these results indicate that changes in soil moisture and near-surface atmospheric vapor pressure deficit are better predictors of the ESI than precipitation and air temperature anomalies are by themselves. Large regional and seasonal dependencies were also observed for each forcing variable. Each of the regional and seasonal correlation patterns were similar for ESI anomalies computed over 2-, 4-, and 8-week time periods; however, the maximum correlations increased as the ESI anomalies were computed over longer time periods and also shifted toward longer averaging periods for the forcing variables.

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Environment and weather influence on quality and market value of hops

Plant Soil and Environment ◽

10.17221/499/2011-pse ◽

2012 ◽

Vol 58 (No. 4) ◽

pp. 155-160 ◽

Cited By ~ 5

Author(s):

V. Pavlovic ◽

M. Pavlovic ◽

A. Cerenak ◽

I.J. Kosir ◽

B. Ceh ◽

...

Keyword(s):

Relative Humidity ◽

Acid Content ◽

Correlation Coefficients ◽

Market Value ◽

Weather Conditions ◽

Growing Season ◽

Time Period ◽

Weather Parameters ◽

Time Periods ◽

Sum Of Active Temperatures

The paper analyses the influence of four main weather parameters on alpha-acid contents for the main hop variety Aurora (Super Styrian Aurora) in Slovenian production for the time period 1994–2009. Through inspection of correlation coefficients, it tries to find specific times of the year when the weather conditions affect the alpha-acid content with a view to prediction in Slovenia. The most significant time periods of weather that influenced the alpha-acid contents of the Aurora variety during the growing season are identified as attributes of temperatures calculated from the interval from 25th to 30th week (T2530, r = –0.88, P < 0.01), as attributes of rainfall and sunshine from the interval from 25th to 29th week (R2529, r = 0.85, P < 0.01 and S2529, r = –0.75, P < 0.01) and attributes of relative humidity from the interval from 27th to 32nd week (RH2732, r = 0.71, P < 0.01). The attribute T2530 represents the sum of active temperatures from June 18 to July 29 of that year. Similarly, the attribute R2529 corresponds to the rainfall (in mm or L/m2) that fell during the June 18 to July 22 etc.

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Exploring seasonal and regional relationships between the Evaporative Stress Index and surface weather and soil moisture anomalies across the United States

10.5194/hess-2018-108 ◽

2018 ◽

Author(s):

Jason A. Otkin ◽

Yafang Zhong ◽

David Lorenz ◽

Martha C. Anderson ◽

Christopher Hain

Keyword(s):

Soil Moisture ◽

Vapor Pressure ◽

Air Temperature ◽

Vapor Pressure Deficit ◽

Growing Season ◽

The United States ◽

Dew Point ◽

Stress Index ◽

Time Periods ◽

The U.S

Abstract. This study uses correlation analyses to explore relationships between the satellite-derived Evaporative Stress Index (ESI) – which depicts standardized anomalies in an actual to reference evapotranspiration fraction – and various land and atmospheric variables that impact evapotranspiration. Correlations between the ESI and forcing variable anomalies calculated over sub-seasonal time scales were computed at weekly and monthly intervals during the growing season. Overall, the results revealed that the ESI is most strongly correlated to anomalies in soil moisture and 2-m dew point depression. Correlations between the ESI and precipitation were also large across most of the U.S.; however, they were typically smaller than those associated with soil moisture and vapor pressure deficit. In contrast, correlations were much weaker for air temperature, wind speed, and radiation across most of the U.S., with the exception of the south-central U.S. where correlations were large for all variables at some point during the growing season. Together, these results indicate that changes in soil moisture and near-surface atmospheric vapor pressure deficit are better predictors of the ESI than precipitation and air temperature anomalies are by themselves. Large regional and seasonal dependencies were also observed for each forcing variable. Each of the regional and seasonal correlation patterns were similar for ESI anomalies computed over 2-, 4-, and 8-wk time periods; however, the maximum correlations increased as the ESI anomalies were computed over longer time periods and also shifted toward longer averaging periods for the forcing variables.

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THEORETICAL AND PRACTICAL ASPECTS OF POSSIBILITIES OF VISUALIZATION AND RECOVERY OF PAPILLAE PATTERN PRINTS FROM BIOLOGICAL SURFACES

Administrative and Criminal Justice ◽

10.17770/acj.v4i77.2873 ◽

2016 ◽

Vol 4 (77) ◽

pp. 3

Author(s):

Raivo Sīda ◽

Aelita Zīle

Keyword(s):

Air Temperature ◽

Fruits And Vegetables ◽

Weather Conditions ◽

Meteorological Conditions ◽

Plant Leaves ◽

Person Identification ◽

Time Period ◽

Time Periods ◽

Slow Wind

The aim of the authors’ experiment conducted was to find out whether it is possible to find, visualise and recover papillae pattern prints from the surfaces of fruits, vegetables and plant leaves. The experiment was performed in four stages. The first stage was performed in the room where the temperature varied from 21°C to 25°C and the time periods were as follows: prints were visualised and copied immediately after leaving them, in 1 hour after leaving them, as well as in 24 hours, in 48 hours, in 72 hours and in 120 hours after leaving the prints. 217 papillae pattern prints were left on the surfaces of fruits and vegetables. 119 of them were recognised as valid for person identification. The second stage was performed under natural weather conditions with the air temperature from 14°C to –20°C. The fruits and vegetables were not covered so that they could not be affected by the meteorological conditions. The time periods were as follows: prints were visualised and copied immediately after leaving them, in 12 hours, in 24 hours and in 36 hours after leaving the experimental prints. As the result 176 papillae pattern prints were left on the surfaces if fruits and vegetables. 43 of them were recognised as valid for person identification. The third stage was performed in the room where the temperature varied from 21°C to 25°C. Experimental papillae pattern prints were left on the leaves of dandelion, apple tree, birch, plantain, clematis and bent-grass. Immediately after leaving the prints they were processed with black fingerprint powder and copied by white Mikrosil silicon casting material. As the result 13 papillae pattern prints were left on the surfaces of plant leaves. All of them were recognised as valid for person identification. Whereas, in the fourth stage plant leaves were exposed to the influence of meteorological conditions (air temperature varied from 28°C to 34°C, it was almost sunny, the slow wind, a bit rain) for time periods of 24 hours and 48 hours. As the result 65 papillae pattern prints were left on the surfaces of plant leaves. 11 of them were recognised as valid for person identification. The summary of the results obtained during the experiment and the analysis let to conclude that: it is possible to find, visualise and recover papillae pattern prints from the surfaces of fruits, vegetables and plant leaves by using powder method which can be used both on scene and under laboratory conditions; there is no set proportionality between number of prints left and prints valid for person identification; quality of prints is not always influenced by preservation time period of prints; meteorological conditions have essential influence on the quality of prints in the preservation time period of prints.

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Analogy-Based Crop Yield Forecasts Based on Temporal Similarity of Leaf Area Index

Remote Sensing ◽

10.3390/rs13163069 ◽

2021 ◽

Vol 13 (16) ◽

pp. 3069

Author(s):

Yadong Liu ◽

Junhwan Kim ◽

David H. Fleisher ◽

Kwang Soo Kim

Keyword(s):

Time Series ◽

Leaf Area Index ◽

Leaf Area ◽

Crop Yield ◽

Satellite Data ◽

Growing Season ◽

Environmental Data ◽

Area Index ◽

Current Season ◽

Wide Range

Seasonal forecasts of crop yield are important components for agricultural policy decisions and farmer planning. A wide range of input data are often needed to forecast crop yield in a region where sophisticated approaches such as machine learning and process-based models are used. This requires considerable effort for data preparation in addition to identifying data sources. Here, we propose a simpler approach called the Analogy Based Crop-yield (ABC) forecast scheme to make timely and accurate prediction of regional crop yield using a minimum set of inputs. In the ABC method, a growing season from a prior long-term period, e.g., 10 years, is first identified as analogous to the current season by the use of a similarity index based on the time series leaf area index (LAI) patterns. Crop yield in the given growing season is then forecasted using the weighted yield average reported in the analogous seasons for the area of interest. The ABC approach was used to predict corn and soybean yields in the Midwestern U.S. at the county level for the period of 2017–2019. The MOD15A2H, which is a satellite data product for LAI, was used to compile inputs. The mean absolute percentage error (MAPE) of crop yield forecasts was <10% for corn and soybean in each growing season when the time series of LAI from the day of year 89 to 209 was used as inputs to the ABC approach. The prediction error for the ABC approach was comparable to results from a deep neural network model that relied on soil and weather data as well as satellite data in a previous study. These results indicate that the ABC approach allowed for crop yield forecast with a lead-time of at least two months before harvest. In particular, the ABC scheme would be useful for regions where crop yield forecasts are limited by availability of reliable environmental data.

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Longitudinal birth cohort study finds that life-course frailty associates with later-life heart size and function

Scientific Reports ◽

10.1038/s41598-021-85435-8 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Constantin-Cristian Topriceanu ◽

James C. Moon ◽

Rebecca Hardy ◽

Nishi Chaturvedi ◽

Alun D. Hughes ◽

...

Keyword(s):

Life Course ◽

Birth Cohort ◽

Left Ventricular ◽

Step Change ◽

Deficit Accumulation ◽

Cardiac Phenotype ◽

Time Period ◽

Time Periods ◽

The Life Course ◽

Health Deficit

AbstractA frailty index (FI) counts health deficit accumulation. Besides traditional risk factors, it is unknown whether the health deficit burden is related to the appearance of cardiovascular disease. In order to answer this question, the same multidimensional FI looking at 45-health deficits was serially calculated per participant at 4 time periods (0–16, 19–44, 45–54 and 60–64 years) using data from the 1946 Medical Research Council (MRC) British National Survey of Health and Development (NSHD)—the world’s longest running longitudinal birth cohort with continuous follow-up. From these the mean and total FI for the life-course, and the step change in deficit accumulation from one time period to another was derived. Echocardiographic data at 60–64 years provided: ejection fraction (EF), left ventricular mass indexed to body surface area (LVmassi, BSA), myocardial contraction fraction indexed to BSA (MCFi) and E/e′. Generalized linear models assessed the association between FIs and echocardiographic parameters after adjustment for relevant covariates. 1375 participants were included. For each single new deficit accumulated at any one of the 4 time periods, LVmassi increased by 0.91–1.44% (p < 0.013), while MCFi decreased by 0.6–1.02% (p < 0.05). A unit increase in FI at age 45–54 and 60–64, decreased EF by 11–12% (p < 0.013). A single health deficit step change occurring between 60 and 64 years and one of the earlier time periods, translated into higher odds (2.1–78.5, p < 0.020) of elevated LV filling pressure. Thus, the accumulation of health deficits at any time period of the life-course associates with a maladaptive cardiac phenotype in older age, dominated by myocardial hypertrophy and poorer function.

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Comorbid disease burden among MS patients 1968–2012: A Swedish register–based cohort study

Multiple Sclerosis Journal ◽

10.1177/1352458520910497 ◽

2020 ◽

pp. 135245852091049 ◽

Cited By ~ 1

Author(s):

Kelsi A Smith ◽

Sarah Burkill ◽

Ayako Hiyoshi ◽

Tomas Olsson ◽

Shahram Bahmanyar ◽

...

Keyword(s):

General Population ◽

Age Groups ◽

Comorbid Disease ◽

Hazard Ratios ◽

Time Period ◽

Younger Age ◽

Cardiovascular Depression ◽

Prevalence Prevalence ◽

Time Periods ◽

Prevalence Ratios

Background: People with multiple sclerosis (pwMS) have increased comorbid disease (CMD) risk. Most previous studies have not considered overall CMD burden. Objective: To describe lifetime CMD burden among pwMS. Methods: PwMS identified using Swedish registers between 1968 and 2012 ( n = 25,476) were matched by sex, age, and county of residence with general-population comparators ( n = 251,170). Prevalence, prevalence ratios (PRs), survival functions, and hazard ratios by MS status, age, and time period compared seven CMD: autoimmune, cardiovascular, depression, diabetes, respiratory, renal, and seizures. Results: The magnitude of the PRs for each CMD and age group decreased across time, with higher PRs in earlier time periods. Before 1990, younger age groups had higher PRs, and after 1990, older age groups had higher PRs. Male pwMS had higher burden compared with females. Overall, renal, respiratory, and seizures had the highest PRs. Before 2001, 50% of pwMS received a first/additional CMD diagnosis 20 years prior to people without MS, which reduced to 4 years after 2001. PwMS had four times higher rates of first/additional diagnoses in earlier time periods, which reduced to less than two times higher in recent time periods compared to people without MS. Conclusion: Swedish pwMS have increased CMD burden compared with the general population, but this has reduced over time.

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Modeling the Impact of Climate Changes on Crop Yield: Irrigated vs. Non-Irrigated Zones in Mississippi

Remote Sensing ◽

10.3390/rs13122249 ◽

2021 ◽

Vol 13 (12) ◽

pp. 2249

Author(s):

Sadia Alam Shammi ◽

Qingmin Meng

Keyword(s):

Climate Change ◽

Crop Yield ◽

Crop Yields ◽

Negative Impact ◽

Positive Impact ◽

Information Criterion ◽

Growing Season ◽

Maximum Temperature ◽

Linear Regression Models ◽

The Impact

Climate change and its impact on agriculture are challenging issues regarding food production and food security. Many researchers have been trying to show the direct and indirect impacts of climate change on agriculture using different methods. In this study, we used linear regression models to assess the impact of climate on crop yield spatially and temporally by managing irrigated and non-irrigated crop fields. The climate data used in this study are Tmax (maximum temperature), Tmean (mean temperature), Tmin (minimum temperature), precipitation, and soybean annual yields, at county scale for Mississippi, USA, from 1980 to 2019. We fit a series of linear models that were evaluated based on statistical measurements of adjusted R-square, Akaike Information Criterion (AIC), and Bayesian Information Criterion (BIC). According to the statistical model evaluation, the 1980–1992 model Y[Tmax,Tmin,Precipitation]92i (BIC = 120.2) for irrigated zones and the 1993–2002 model Y[Tmax,Tmean,Precipitation]02ni (BIC = 1128.9) for non-irrigated zones showed the best fit for the 10-year period of climatic impacts on crop yields. These models showed about 2 to 7% significant negative impact of Tmax increase on the crop yield for irrigated and non-irrigated regions. Besides, the models for different agricultural districts also explained the changes of Tmax, Tmean, Tmin, and precipitation in the irrigated (adjusted R-square: 13–28%) and non-irrigated zones (adjusted R-square: 8–73%). About 2–10% negative impact of Tmax was estimated across different agricultural districts, whereas about −2 to +17% impacts of precipitation were observed for different districts. The modeling of 40-year periods of the whole state of Mississippi estimated a negative impact of Tmax (about 2.7 to 8.34%) but a positive impact of Tmean (+8.9%) on crop yield during the crop growing season, for both irrigated and non-irrigated regions. Overall, we assessed that crop yields were negatively affected (about 2–8%) by the increase of Tmax during the growing season, for both irrigated and non-irrigated zones. Both positive and negative impacts on crop yields were observed for the increases of Tmean, Tmin, and precipitation, respectively, for irrigated and non-irrigated zones. This study showed the pattern and extent of Tmax, Tmean, Tmin, and precipitation and their impacts on soybean yield at local and regional scales. The methods and the models proposed in this study could be helpful to quantify the climate change impacts on crop yields by considering irrigation conditions for different regions and periods.

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Visualizing Belief in Meritocracy, 1930–2010

Socius Sociological Research for a Dynamic World ◽

10.1177/2378023118811805 ◽

2018 ◽

Vol 4 ◽

pp. 237802311881180 ◽

Cited By ~ 1

Author(s):

Jonathan J. B. Mijs

Keyword(s):

Survey Data ◽

Representative Sample ◽

Western World ◽

Birth Cohorts ◽

Popular Belief ◽

Time Period ◽

Level Data ◽

Two Measures ◽

Time Periods ◽

Over Time

In this figure I describe the long trend in popular belief in meritocracy across the Western world between 1930 and 2010. Studying trends in attitudes is limited by the paucity of survey data that can be compared across countries and over time. Here, I show how to complement survey waves with cohort-level data. Repeated surveys draw on a representative sample of the population to describe the typical beliefs held by citizens in a given country and period. Leveraging the fact that citizens surveyed in a given year were born in different time-periods allows for a comparison of beliefs across birth cohorts. The latter overlaps with the former, but considerably extends the time period covered by the data. Taken together, the two measures give a “triangulated” longitudinal record of popular belief in meritocracy. I find that in most countries, popular belief in meritocracy is (much) stronger for more recent periods and cohorts.

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