Yield Variability Research Articles

Large scale water yield assessment for sparsely monitored river basins: A case study for Afghanistan

This paper presents results from a study on water yield assessment across five major river basins of Afghanistan. The study was conducted using GR4J and GR4JSG precipitation-runoff models. The river basins were divided into 207 subcatchments and each subcatchment was divided into multiple functional units. The model was calibrated using observed streamflow data from 2008 to 2015 and validated over the 2016 to 2020 period. Model parameters were calibrated for an unregulated subcatchment in each basin and calibrated parameters from the best-performing subcatchment were transferred to other subcatchments. Results show that modelled water yield across the five basins varies from 0.3 mm in the Helmand basin to 248 mm in the Panj-Amu basin, with an average of 72.1 mm for the entire country. In the period of 2008 to 2020, area averaged water yield in the five basins varies from 36 to 174 mm. For the same period, mean annual precipitation for the entire country is 234.0 mm, indicating a water yield of 30.8%. The nation-wide average water yield of 72.1 mm is equivalent to 46.3 billion cubic meters (BCM) of surface water for the country. In addition, about 28.9 BCM generates annually in the neighbouring Tajikistan and Pakistan from snow and glaciers of the Hindu-Kush mountains. The elevated northern parts of Afghanistan, including parts of neighbouring Tajikistan are the primary water source. Water yield across the country varies between years but there is no consistent increasing or decreasing trends. About 60 to 70% of flow occurs between March to June. The study identified the high water yield areas and investigated variability at monthly, seasonal, and annual time scales. An importance finding is the large spatial and temporal variability of water yield across the basins. This information is crucial for long-term water resources planning and management for agricultural development.

Teff grass increases summer forage availability in the Rolling Plains of Texas

AbstractTeff [Eragrostis tef (Zucc.) Trotter] grass has gained popularity in the United States as an emergency summer forage for livestock due to its drought tolerance and rapid growth habit. An alternative forage would benefit Texas Rolling Plains growers due to the summer forage shortage caused by drought conditions. However, among the teff research conducted in the United States, there is great variability in the forage yields and nutritive values depending on the amount of nitrogen and available water. The objective of the study was to evaluate forage productivity and nutritive value of teff in the Texas Rolling Plains under irrigated and dryland conditions with two nitrogen rates and application timings. Nitrogen fertilizer treatments included single applications of either 50 or 100 lb a−1 applied at planting and a split application of either 50 or 100 lb a−1 applied both at planting and after the first harvest. No differences were observed among nitrogen rates and application methods in the irrigated trial (5286 lb a−1). The split application of 100 lb a−1 produced the greatest total yield in the dryland trial (3096 lb a−1) with no yield advantage of 100 lb N a−1 over 50 lb N a−1 at the first cutting. Forage nutritive values were similar to the warm‐season forage species utilized in the region. This study showed that teff can be an alternative forage species in the region. Future research will include planting dates, nitrogen application timing, cutting height, and the interaction of these factors on yield and nutritive values of teff.

Use of Eucalyptus Charcoal Waste in the Formulation of Substrate for the Cultivation of Two Strains (LED 20/11 and LED 20/12) of Lentinula edodes

The shiitake mushroom (Lentinula edodes) is globally valued for its nutrition and medicinal properties. New technologies aim to increase production with less environmental impact, considering materials such as charcoal for substrate enrichment. This manuscript evaluated the effect of fine charcoal (FC) on the substrate formulation of two L. edodes strains (LED 20/11 and LED 20/12). The substrate consisted of 72% eucalyptus sawdust, 12.5% rice bran, 12.5% wheat bran, and 3% calcium carbonate (control treatment without charcoal). Treatments with FC proportionally reduced the use of sawdust, with doses of 1%, 2%, 4%, 8%, and 16% (relative to the substrate material). Yield, mushroom number, and mushroom weight were evaluated. The concentration of FC significantly affected the parameters analyzed, especially at the 4% dose. A negative correlation between mushroom number and weight was observed. For yield, the control treatment and the lowest dose of FC (1%) had the highest yields for the first harvest. Strain LED 20/12 showed lower yield variability due to the percentage of FC applied to the substrate. The incorporation of FC into the substrate for shiitake cultivation demonstrates efficacy; however, both the concentration and strain used are limiting factors for its applicability.

Comparative analysis of thermal indices for modeling cold and heat stress in US dairy systems

Quantifying the impact of thermal stress on milk yields is essential to effectively manage present and future risks in dairy systems. Despite the existence of numerous heat indices designed to communicate stress thresholds, little information is available regarding the accuracy of different indices in estimating milk yield losses from both cold and heat stress at large spatio-temporal scales. To address this gap, we comparatively analyzed the performance of existing thermal indices in capturing US milk yield response to both cold and heat stress at the national scale. We selected four commonly used thermal indices: the Temperature and Humidity Index (THI), Black Globe Humidity Index (BGHI), Adjusted Temperature and Humidity Index (THIadj), and Comprehensive Climate Index (CCI). Using a statistical panel regression model with observational and reanalysis weather data from 1981-2020, we systematically compared the patterns of yield sensitivities and statistical performance of the four indices. We found that the US state-level milk yield variability was better explained by the THIadj and CCI, which combine the effects of temperature, humidity, wind, and solar radiation. Our analysis also reveals a continuous and nonlinear responses of milk yields to a range of cold to heat stress across all four indices. This implies that solely relying on fixed thresholds of these indices to model milk yield changes may be insufficient to capture cumulative thermal stress. Cold extremes reduced milk yields comparably to those impacted by heat extremes on the national scale. Additionally, we found large spatial variability in milk yield sensitivities, implying further limitations to the use of fixed thresholds across locations. Moreover, we found decreased yield sensitivity to thermal stress in the most recent two decades, suggesting adaptive changes in management to reduce weather-related risks.

Identification of Plant and Soil Characteristics Affecting Stability of Winter Wheat Cultivar in Temperate Climates

This study examines the significant variability in grain yield, thousand-grain weight, protein content, sedimentation value, and falling number among winter wheat cultivars across diverse trial locations, elucidating the profound influence of environmental factors on these traits. Employing Shukla’s stability variance and a multi-trait stability index (MTSI), cultivar stability is comprehensively assessed across multiple traits. Cultivars are ranked based on stability variance and cumulative ranking across all traits, with Bataja emerging as the most stable cultivar according to Shukla variance, while Apostel exhibits the lowest stability. Contrarily, MTSI rankings reveal distinct top performers, such as Medalistika and KWS Spencer. Canonical correspondence analysis (CCA) is utilized to discern relationships between stability and genotype characteristics, as well as trait values and soil properties/weather conditions. These findings contribute to the recommendation of stable cultivars for breeding programs and the optimization of crop management practices. Furthermore, this study underscores the need to explore causal relationships between accompanying variables, facilitating informed recommendations for plant breeders and advancing breeding progress amidst a changing climate. The use of multivariate statistical methods, including CCA, enhances our understanding of cultivar traits and stability, offering valuable insights for sustainable agriculture.

Dissecting Genotype by Environment Interactions in Moroccan Wheat: An Advanced Biplot and Heatmap Analysis Unveiling Agronomic, Quality Traits, and Genotypic Stability for Tailored Breeding Strategies.

This five-year study (2016-2021) across diverse Moroccan agro-climatic zones investigated genotype by environment (G × E) interactions in wheat, focusing on variations in agronomic traits and quality attributes such as protein and gluten content. Significant environmental effects were observed on key traits, like yield, thousand kernel weight (TKW), and spikes per square meter (Spk/m2), highlighting environmental factors' role in wheat yield variability. In the Tassaout (TST) location, notable genotypic effects emerged for traits like biomass, underscoring genetic factors' importance in specific contexts, while in Sidi El Aidi (SEA) and Marchouch (MCH), genotypic effects on yield and its components were predominantly absent, indicating a more substantial environmental influence. These findings illustrate the complexity of G × E interactions and the need for breeding strategies considering genetic potential and environmental adaptability, especially given the trade-offs between yield enhancement and quality maintenance. Insights from the biplot and heatmap analyses enhanced the understanding of genotypes' dynamic interactions with environmental factors, establishing a basis for strategic genotype selection and management to optimize wheat yield and quality. This research contributes to sustainable wheat breeding in Morocco, aligning with global efforts to adapt wheat breeding strategies to changing climatic conditions.

Growth and yield variability of wheat as effected by split application of potassium and nitrogen

Growth and yield variability of wheat as effected by split application of potassium and nitrogen

Environmental drivers of wheat yield variability across China's production regions: Insights from field experiments

AbstractWheat crops underpin contemporary global food security. Predominant wheat production zones in China include the Huang‐Huai‐Hai‐Plain and the Mid‐Lower Reaches of the Yangtze River, although climatic effects on productive potential across these regions vary markedly in space and time. Here, we conducted field experiments during the wheat season of 2015–2018 to examine environmental effects on growth, with fertilization and irrigation provided at levels ensuring that nutrient and water stress exposure was minimal. Yields in Huang‐Huai‐Hai‐Plain and the Mid‐Lower Reaches of the Yangtze River averaged 8950 and 4818 kg ha−1, respectively. Yield variation across regions was primarily related to spike number per unit area and grain number per spike. Maturity biomass was higher in Huang‐Huai‐Hai‐Plain; this translated into higher grain yields. Lower temperature and longer growing duration between emergence and jointing in Huang‐Huai‐Hai‐Plain afforded higher tillering and spike numbers, whereas higher growth rates from jointing to maturity resulted in higher biomass production in Huang‐Huai‐Hai‐Plain compare with the Mid‐Lower Reaches of Yangtze River. Growth rate, grain numbers and yield were positively correlated with the ratio of daily intercepted solar radiation to mean temperature during jointing to anthesis, termed photothermal quotient. Collectively, our results suggest that growth rate accounted for more variation in biomass production compared with growth duration, and the photothermal conditions in the Mid‐Lower Reaches of the Yangtze River were restrictive for spike development and yield formation. Our results help disentangle drivers of crop growth through the development of agro‐environmental conceptual frameworks, enabling a better understanding of yield variability in space and time.

An insight into variability and association among yield and its components under alkalinity and inland salinity stress in rice (Oryza sativa L.)

An experiment was conducted to study the variability, correlation, direct and indirect effects of yield and its attributing traits in 36 genotypes and to identify suitable parents for breeding of alkalinity and inland salinity stress tolerant lines at ARS, Kampasagar, Nalgonda during rabi, 2021-22. Analysis of variance revealed plenteous quantum of variation among the tested genotypes. Wide variation, high PCV, GCV, heritability and genetic advance were observed for seedling mortality, sterility percentage and number of filled grains per panicle. Number of productive tillers/hill and number of filled grains per panicle had a positive and significant correlation with yield whereas seedling mortality and sterility percentage had a negative and significant association with yield. Path analysis inferred that traits such as number of productive tillers/hill, number of grains per panicle and 1000 grain weight had a positive direct effect on yield. Hence,priority should be given to the above mentioned traits to develop alkalinity and inland saline tolerant rice cultivars. Lines CT118911, Sahel177, M202, and KPS10654 were found promising to be utilized as tolerant parents in the breeding programmes.

Screening for Heat and Rain Tolerant Cultivars of Cauliflower for Cultivation in Monsoon Season in the Subtropical Region of Bhutan

There is a shortage of cauliflower in the domestic market during monsoon and early autumn seasons in Bhutan due to the absence of suitable cultivars for cultivation in subtropical region during these seasons. This study was conducted to assess the genotypic variability in yield of different cultivars of cauliflower under heat and rain (flood) stresses in the subtropical region. Four F1 hybrid varieties of cauliflower from the Takii Seeds, Japan (KSB-12.179, KSB-12.180, KSB-18.297 and KSB-20.320) and three F1 hybrid varieties from Syngenta Seeds, India (C-6099, CFL-1522 and Monsoon Queen) were evaluated in August 2022 in open field at ARDC Samtenling. The experiment was laid out in a RCDB design with three replications using Snow Mystique as the check variety. The objective of the study was to identify short duration, rain and heat tolerant varieties of cauliflower for cultivation in the monsoon season (July-August) in the subtropical region of Bhutan. In addition, all the cultivars were further assessed in September, and five cultivars that performed well in monsoon planting were evaluated in November 2022 as the second and third staggered planting trials to find out their performance in late monsoon and main seasons (September-November) respectively. The results from three staggered trials showed that Monsoon Queen matured in 53 days after transplanting (DAT), 56 DAT and 35 DAT in the first, second and third staggered planting trials with the mean head of 462 g, 376 g and 211 g respectively. In comparison, the check variety matured in 142 DAT, 114 DAT and 77 DAT in the first, second and third staggered planting trials with the mean head of 658 g, 403 g and 767 g, respectively. Monsoon Queen was the earliest maturing variety with good head weight and curd quality among the eight cauliflower varieties when transplanted in August 2022. However, both the head yield and curd quality of this cultivar declined in later plantings, indicating that this variety is not suitable for main season (autumn) planting. With the identification of Monsoon Queen as the heat and rain tolerant cultivar in this study, cauliflower can now be grown even in the monsoon season in the subtropical region of Bhutan.

Climate drives of growth, yield and microclimate variability in multistoried coconut plantation in Konkan region of Maharashtra, India

Long term experiments (2013-14 to 2018-19) were conducted in Regional Coconut Research Station, Bhatye, a representative location of major coconut growing region of Maharashtra (Konkan region) to study the impact of changing weather parameters on growth and yield of 32 years old coconut plants (dwarf x tall, i.e., COD x WCT). Regression based trend analysis of weather parameters was conducted to check the variability of weather parameters over experimentation years. There was a decrease in maximum temperature (r2=0.034) and increase in minimum temperature (r2=0.017) and rainfall (r2=0.393), indicating change in weather parameters. Correlation studies were carried out to understand the interaction between weather parameters and coconut growth and yield. Maximum temperature had a negative impact on growth (-0.02 and -0.58 for number of leaves and annual leaf production) but had a positive impact on yield (0.41, 0.64 and 0.63 for number of bunches, number of buttons and nut yield). Minimum temperature had significant negative effect on annual leaf production (-0.88) and had a positive effect on nut yield per plant (0.95). The effect of relative humidity (morning and evening) was non-significant. Rainfall had its influence on the crop by negatively affecting the number of bunches (-0.10) and nut yield per plant (-0.48), a positively affecting number of buttons (0.08). Further, microclimate in the plantation was compared to an open field, which indicated lower maximum and minimum temperature (-3.4 and -3.1 %) and higher morning and evening relative humidity (1.6 and 1.9 %) in the coconut plantation as compared to the open field.

Seed Quantity and Quality Variation in European Beech (Fagus sylvatica L.)

European beech (Fagus sylvatica L.) is characterized by inter-annual cycles of seed production (masting), with synchronized high seed production between sites in some years. The importance of both seed quantity and quality monitoring stems from its role in sustaining the ecological balance, promoting biodiversity, and ensuring the long-term viability of forest ecosystems. This study aimed to (1) describe seed production from 2015 to 2022, (2) identify the potential factors that could affect the yield appearance and seed quantity, and (3) compare the quality of beechnuts from different crop years in Croatia. At each of the six forest seed objects located in the area of forest administrations Bjelovar, Karlovac, Ogulin, Požega, and Delnice, we selected 5 trees for seed collection. Seeds were collected with large PVC nets covering total projection area of the tree crowns. Seed quality testing was performed according to the International Rules for Seed Testing (ISTA Rules). Our results indicate a consistent biennial beechnut cycle. The crop was completely absent in 2015, 2017, 2019 and 2020, while 2016, 2018, 2020 and 2022 were fruitful years. Weather plays a key role in triggering masting. We found that beechnut production is influenced by summer weather conditions (from June to August) in the previous two years. Abundance of beechnut production varies on an annual level, population level and on individual trees. Factors that partially explain the variability in yield are tree height and crown size. No significant differences in viability were found across different years and sites, though the results should be approached with caution due to limited sample representation. The study identified a positive correlation between seed weight and viability, as well as the impact of precipitation on moisture content. The results emphasize the need for continued monitoring and further research to understand the factors influencing beechnut production and quality, crucial for sustainable forest management in the face of climate change.

Yield gap analysis and the relative importance of factors explaining yield variability in paddy fields

Closing the yield gap of strategic crops can facilitate achieving sustainable solutions to alleviate hunger, ensure food security, and enhance nutrition. This study aimed to quantify factors affecting rice yield gap in northern Iran using experimental and survey data on yields and management practices. The CERES-Rice model, calibrated with data (2011, 2016, 2019) from two regions, was used to estimate potential yield (Yp) of different rice cultivars. Yield gaps were calculated as the difference between economic yield potential and the average yield attained by farmers. The calibration process showed that cultivar coefficients varied across rice varieties. The simulated yields (2012–2021) showed that the mean potential yields were 13362 kg ha−1 and 8818 kg ha−1 for the late and early-maturing cultivars, respectively. High temperature was the most important yield defining factor across the rice growing areas. The yield gap was 3751 kg ha−1 and 2830 kg ha−1 in the late- and early-maturing cultivars, respectively. Nitrogen fertilizer rate, number of fertilizer applications, phosphorus fertilizer rate, transplanting date, potassium fertilizer rate, and seedling age were the top factors influencing the yield gap. Among the management factors, rice fertilizer management explained about 65% of the yield variability. Together, transplanting date and seedling age explained 15.3% of the variability in rice production, while pest, disease, and weed damage accounted for 9.6%. Breaking down the yield gap into affecting factors allows growers to improve the production system by providing the best crop management according to their facilities and capabilities. This approach is essential for optimizing agricultural productivity and achieving sustainable food production goals.

Comparative analysis of wheat and barley yield performance across temperate environments

ContextA comparative analysis of grain yield performance of wheat (Triticum aestivum L.) and barley (Hordeum vulgare L.) under different environments constitutes a way to identify restrictions in yield formation between both crop species. However, most of the previous studies on these field crops have been carried out in Mediterranean environments. ObjectiveThis study aims to compare the grain yield performance of wheat and barley across a wide range of temperate environmental conditions. MethodsWheat and barley yield databases from the national network of cultivar evaluation of Argentina were assembled. The database included 191 wheat cultivars (with early-, mid- and late-flowering length cycle), 140 barley cultivars, and 44 combinations of sites and years of the Argentine wheat and barley belt region. Average heading date variation among environments and crops was no more than 10 days. Crop grain yield comparisons were carried out using a regression analysis, benchmarking within each site-year the grain yield of each cultivar against the average grain yield of all crop cultivars (i.e., environmental index). ResultsThere were no differences in grain yield between wheat and barley for all data, but the behavior between crop species changed with the length of the wheat cycle (i.e., early-, mid-, or late-flowering cultivars). Barley portrayed a greater grain yield than early-flowering wheat under low-yielding environments (< 6060 kg ha−1), but this advantage vanished as the yield environment improved. Mid-flowering wheat showed a similar grain yield to barley across temperate environments. Lastly, late-flowering wheat outperformed barley mainly in high-yielding environments (> 6138 kg ha−1). Grain number m−2 was the main numerical component that explained variability in grain yield. The relative contribution of the yield numerical components differed between species, having barley lower grain number m−2 but a greater grain weight than wheat. ConclusionsThe comparison of the grain yield performance between species represents a strategy to adjust the rotation system, being a critical factor in considering the variability in the crop growth cycle.

Abstract 3613: Screening iPSC lines for optimal characteristics of differentiation into immune effector cells for clinical programs

Abstract Engineered Induced Pluripotent Stem Cells (iPSCs) are the core foundational technology for Century Therapeutics. In our constant effort to identify iPSC lines with diverse functional activity, we have derived a large panel of clinical-grade peripheral blood mononuclear cell (PBMC)-derived and gamma-delta T cell-derived IPSC lines (PiPSCs and TiPSCs, respectively) from multiple donors. These lines have been screened by multiple criteria to select the top lines for clinical development in our iPSC-derived NK (iNK) and T cell (iT) programs. Initial screening included in-depth genomic and transcriptomic analysis of PiPSC and TiPSC lines to eliminate those with any unwanted genetic abnormalities, as well as to build multi-omics datasets for correlating gene polymorphisms and transcript variation to function. Next, all lines were differentiated to iNK or iT effector cells, and phenotypically characterized throughout the differentiation process. In those studies, 86.5% of PiPSCs and 69.2% of TiPSCs lines were compatible with our protocols and able to be successfully differentiated and acquire NK cell and gamma delta T cell phenotypes respectively. Yield and lineage commitment (%CD56+ for NK cells and %CD3+ for T cells) variability was found to be higher across clones than donors in this initial analysis. Finally, we evaluated in vitro cytotoxicity, cytokine secretion, and persistence for all clones that met differentiation thresholds (&amp;gt;90% lineage commitment). As part of that evaluation, 39 PiPSCs lines were differentiated to iNK cells. Cytotoxicity against tumor lines was observed to be consistently between 85-100% at an effector to target ratio of 1:1. Although no trends in functionality were found to be associated with the PBMC donor, iPSC lines derived from CD34+ enriched PBMCs exhibited higher levels of innate killing as compared to those derived from bulk PBMCs. For this presentation, we will present genetic, transcriptomic, and phenotypic correlations with favorable differentiation and functional efficacy and illustrate how our screening process enables efficient selection of founder lines with the highest therapeutic potential for allogeneic cell therapies. Citation Format: Barry A. Morse, Amarin Cogburn, Alex Chialastri, Matthew S. Hall, Ohad Manor, Andriana Lebid, Dae Hwan Kim, Luis Cocka, Daniel J. Perry, Ciara Budd, Aarti Kolluri, Liam Campion, Toshinobu Nishimura, Michael Naso, Hyam Levitsky. Screening iPSC lines for optimal characteristics of differentiation into immune effector cells for clinical programs [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3613.

Historic corn yield, production, and economic value trends in Kansas

AbstractWorld corn (Zea mays L.) production has tripled since the 1960s. However, without new breakthrough innovations the trend is expected to plateau or decrease in the future. The objective of this study was to quantify Kansas corn production, economic value, productivity, annual production variation, yield gap trends, and in due course, identify future areas for research. Corn variety performance tests and United States Department of Agriculture (USDA) data were used for this study. Results showed that the area planted to corn in Kansas increased from 0.5 million in 1880s to over 2 million ha by 2022, with an increase of 0.05 million ha year−1 between 1984 and 2022. The value of corn produced in Kansas also increased significantly from below $1 billion annually prior to 1990s to the current value of approximately $3–$4 billion. The average corn yield gain from 1972 to 2000 was 132 kg ha−1 year−1, which declined to 12 kg ha−1 year−1 during 2000 to the early 2020s. Also, a relatively high yield variability occurred from 1970 to the early 2020s compared with earlier years (1866–1970), and a 42%–68% gap between the potential and actual corn yields was identified. We concluded that there is a decrease in the rate of corn yield increase and developing farmer awareness and their adoption of new corn production technology, increasing longevity of the Ogallala Aquifer, and integrated research should be priorities to avert the decreasing trend of corn productivity and further increase corn economic value.

Change and influence of agroclimatic conditions on oat yield in Yakutia

The results of the dynamics analysis of multi-year meteorological indicators and study of their influence on the yield of the released oat varieties in different agroclimatic zones of Yakutia are presented. It is shown that in the period from 1960 to 2021 the mean annual air temperature in Central Yakutia (Pokrovsk meteorological station) increased annually by 0.045 °C, from 1999 to 2021 – by 0.088 °C, the number of dry years in June increased from 67 to 92% due to a 21% increase in years with medium (HTC = 0.41-0.60) and very strong (HTC &lt; 0.21) drought. In July, drought was recorded in 50% of the years, in August – in 38%. In all agroclimatic zones in the period from 2014 to 2021 for June – August the average daily air temperature annually increased by 0.16...0.34 °С and their sum by 14...28 °С, with precipitation decreasing by 3-16 mm and HTC value by 0.04-0.12 units. Climate change from 2014 to 2021 was 3 to 8 times more intense than from 1999 to 2022. There was a strong variability of yields of the released oat varieties in each agroclimatic zone: Central – from 0.38 to 2.14 t/ha (V = 60–73%), Zarechnaya – from 0.31 to 3.55 t/ha (V = 41–49%), Srednelenskaya – from 1.51 to 4.66 t/ha (V = 30–36%). The greatest annual decrease in grain yield of oat varieties (by 0.25–0.26 t/ha) was observed in arid agroclimatic zones – Central (Yakutsk SCTS) and Zarechnaya (Megino-Kangalassky SCTS) – compared to the wetter Srednelenskaya zone (Olyokminsky SCTS – by 0.10 t/ha). More significant influence on the yield in the Central and Zarechnaya zones was made by precipitation and HTC of the growing season (r = 0.77...0.84), in the Srednelenskaya zone – by temperature (r = – 0.79). Negative effect of temperature on the yield in the Central zone was observed in June (r = – 0.83), Zarechnaya zone - in July (r = – 0.83), in the Srednelenskaya zone – in August (r = –0.86). Precipitation and HTC had the greatest influence on the yield in the Central zone in June and July (r = 0.56...0.59), Zarechnaya zone – July and August (r = 0.60...0.76). In the Srednelenskaya zone the relationship of the yield with precipitation and HTC in June and July was positive (r = 0.23...0.37), in August – negative (r = – 0.57...– 0.71). Significant variability in grain yields of the released oat varieties indicates the variability of weather conditions and the need to cultivate oat varieties that provide a more stable yield in different agroclimatic zones of Yakutia.

Machine learning approach for satellite-based subfield canola yield prediction using floral phenology metrics and soil parameters

Early monitoring of within-field yield variability and forecasting yield potential is critical for farmers and other key stakeholders such as policymakers. Remote sensing techniques are progressively being used in yield prediction studies due to easy access and affordability. Despite the increasing use of remote sensing techniques for yield prediction in agriculture, there is still a need for medium-resolution satellite imagery when predicting canola yield using a combination of crop and soil information. In this study, we investigated the utility of remotely sensed flowering information from PlanetScope (at 4 m) satellite imagery combined with derived soil and topography parameters to predict canola yield. Our yield prediction model was trained and validated using data from 21 fields managed under variable rate seed and fertilizer application, including cleaned harvester yield maps, soil, and topography maps. To quantify the flowering intensity of canola, 9 vegetation indices (VIs) were calculated using spectral bands from PlanetScope imagery acquired for the reproductive stages of canola. We created five random forest regression models using different subsets of covariates, including VIs, soil, and topography features, to predict canola yield within the season. Using a random forest regression algorithm, we recorded accuracies ranging from poor to best performing using coefficient of determination and root mean squared error (R2: 0.47 to 0.66, RMSE: 325 to 399 kg ha−1). The optimal subset of covariates identified electrical conductivity (EC), Normalized Difference Yellowness Index, and Canola Index as the key variables explaining within-spatial variability in canola yield. Our final model exhibited a validation R2 of 0.46 (RMSE = 730 kg ha−1), demonstrating the potential of medium-resolution satellite imagery during the flowering stage to detect and quantify sub-field spatial and temporal floral phenology changes when predicting canola yield.

Evaluation of crop model-based simplified marginal net return maximising nitrogen application rates on site-specific level in maize

AbstractCrop growth models such as DSSAT-CERES-Maize have proven to be useful for analysing plant growth and yield within homogenous land units. The paper presents results of newly developed model-based site-specific Soil Profile Optimisation (SPO) tools in combination with an updated version of an already published Nitrogen Prescription Model (NPM). Site-specific soil profiles were generated through an inverse modelling approach based on measured site-specific yield (point-based) and tops weight (above-ground biomass time-series) and evaluated. Site-specific soil profiles generated based only on measured yield variability were able to explain 72% (R2 0.72) of yield variability (dependent variable) based on selected soil profile input parameters (independent variable). Site-specific soil profiles generated based on measured yield and tops variability simultaneously (multiple target variable) explained 68% of yield variability (R2 0.68). The NPM uses the SPO generated site-specific soil profiles for economic evaluation of site-specific N application rates. NPM simulated N application rates, aiming at the maximisation of marginal net return (MNR) were 25% lower compared to the uniform N application rates with an assumed grain and N price of 0.17 and 0.3 Euro kg−1 respectively, under rainfed conditions over three years based on soil profiles generated via an inverse modelling approach only from measured yield variability (one target variable). N application rates were 28% lower when based on soil profiles generated from simultaneously included grain and tops variability in the inverse modelling approach. The results highlight the importance of site-specific fertilizer management when maximising MNR.

Effects of different nitrogen fertilization systems on crop yield and nitrogen use efficiency – Results of a field experiment in southern Germany

The effects of the German Fertilizer Application Ordinance (GFO) on crop yield, nitrogen use efficiency and economical performance are highly controversial in science and practice in Germany. This study presents the results of a multi-year field experiment conducted at an experimental farm in southern Germany, in which the effects of different fertilizer systems on crop yield, protein concentration and nitrogen balance were analyzed.At this study site, relatively low N mineralization from the soil N pool was detected. Wheat (triticum aestivum L.) and barley (hordeum vulgare L.) showed strong yield declines from annual to multi-annual unfertilized plots, for maize (zea mays L.), this yield decrease was not observed. The recommendations according to GFO meets the fertilizer requirement at the trial site well. A 20% reduction of fertilization compared to GFO resulted in a 5% yield reduction and a decrease in protein concentration of wheat and barley.According to the quadratic N response function, the GFO treatment was slightly below the economic optimum nitrogen rate (Nopt) for wheat, and close to Nopt for winter barley on average over the trial years. For maize, a relatively high yield variability has been observed in the trial period so far. Sensor-based fertilization resulted in very high yields with high N use efficiency (up to 85%). This fertilization system can help to reduce nitrogen input and minimize nitrogen surplus.For wheat and barley, N fertilization and N uptake were well balanced, for maize clearly negative N surpluses were calculated. Despite all the discussion and criticism of GFO, the results of the plot trial show that high yields with high N use efficiency can be achieved with fertilization according to GFO.