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Tag: Crops & Agronomy

  • Multimodal dataset improves land cover and crop mapping benchmarks

    What the study found

    The study introduces FLAIR-HUB, a large-scale multimodal land cover dataset with 20 cm annotations covering 2528 km² of France. The authors report that using nearly all available modalities gave the best land cover performance, and that multimodal fusion and fine-grained classification are complex.

    Why the authors say this matters

    The authors conclude that FLAIR-HUB provides a valuable foundation for supervised, self-supervised, and transfer learning in Earth Observation research. They also say the dataset and benchmarks can support progress in land cover and crop mapping.

    What the researchers tested

    The researchers built a benchmark using six aligned data sources: aerial imagery, Sentinel-2 optical multi-spectral time series, Sentinel-1 synthetic aperture radar (SAR) time series, high-resolution SPOT satellite images, topographic data, and historical aerial images. They evaluated multimodal fusion and deep learning models, including convolutional neural networks and transformers, and also explored multi-task learning.

    What worked and what didn't

    The best land cover result reported was 78.2% accuracy and 65.8% mean Intersection over Union, achieved using nearly all modalities. The abstract says the benchmarks underscore the complexity of multimodal fusion and fine-grained classification, but it does not provide detailed per-model comparisons in the summary.

    What to keep in mind

    The available summary does not describe detailed limitations beyond noting the complexity of multimodal fusion and fine-grained classification. It also does not give full results for every tested model, task, or modality combination.

    • FLAIR-HUB is a large-scale multimodal land cover dataset covering 2528 km² of France.
    • The dataset includes six aligned modalities, from aerial imagery to satellite time series and historical aerial images.
    • Annotations are very high resolution, at 20 cm, supporting fine-grained land cover description.
    • The best land cover performance reported was 78.2% accuracy and 65.8% mean Intersection over Union.
    • The strongest result used nearly all modalities rather than a single source.

  • NDVI trends differed between Brazil’s Cerrado regions

    What the study found

    The study found a "remote-sensing paradox" in which the established agricultural region was more stable than the agricultural frontier, despite having more long-standing land conversion. The main common driver of Normalized Difference Vegetation Index (NDVI, a satellite-based measure of greenness) decline was conversion of native savanna to croplands and pastures.

    Why the authors say this matters

    The authors conclude that NDVI-based assessments of land degradation in the Cerrado must consider early land-use history and agricultural management relative to the satellite observation period. The findings indicate that the meaning of NDVI trends can depend on how long land has been used agriculturally.

    What the researchers tested

    The researchers analyzed NDVI trajectories from MODIS satellite data from 2000 to 2022 in two contrasting regions of the Brazilian Cerrado: an established agricultural region and an expanding frontier. They derived NDVI trajectories using Trends.Earth, correlated them with MODIS Gross Primary Production (GPP, a measure of plant carbon uptake), and tested common and region-specific drivers with binary logistic regression and Wald-type Z tests.

    What worked and what didn't

    The established agricultural region showed the smallest share of NDVI decrease, at 7%, and the highest share of increase, at 52%. The agricultural frontier showed greater NDVI decline, at 16%, and smaller increases, at 37%; positive NDVI-GPP relationships were weaker in the established region. Region-specific drivers included precipitation, soil sand content, and fire frequency, and longer agricultural use duration was associated with NDVI increases, which the authors say likely reflects management practices that mask underlying degradation.

    What to keep in mind

    The abstract does not describe all possible limitations, so only the stated scope can be reported. The analysis is limited to two regions in the Brazilian Cerrado and to the 2000-2022 MODIS observation period.

    • The study reported a remote-sensing paradox between an established agricultural region and an expanding frontier in the Brazilian Cerrado.
    • The main shared driver of NDVI decline was conversion of native savanna to croplands and pastures.
    • The established agricultural region had 7% NDVI decrease and 52% NDVI increase, while the frontier had 16% decrease and 37% increase.
    • Positive NDVI-GPP relationships were weaker in the established region.
    • Precipitation, soil sand content, and fire frequency were region-specific drivers.
    • The authors say early land-use history and agricultural management should be considered when interpreting NDVI-based land degradation assessments.

  • Wheat amino acid digestibility varied across samples in pullets

    What the study found

    The study found that wheat samples from different sources varied considerably in chemical composition, and that standardized ileal amino acid digestibility differed significantly among the samples. The authors report that prediction equations based on wheat chemical properties could estimate digestibility for most amino acids in pullets.

    Why the authors say this matters

    The authors say this matters because wheat is a major alternative to corn in layer diets, and a lack of established assessment and prediction models limits precision formulation. The study suggests that the equations could be a tool for rapid and accurate evaluation of the amino acid nutritional value of wheat in pullets.

    What the researchers tested

    The researchers evaluated 10 wheat samples from different sources for physical properties, conventional nutritional components, amino acid profiles, and standardized ileal amino acid digestibility, which means digestibility measured at the end of the small intestine. They fed the samples to Jingfen No.8 pullets during brooding (days 28-31) and growing (days 92-95) periods, using 11 dietary groups that included a nitrogen-free diet and 10 test diets in which wheat was the sole amino acid source.

    What worked and what didn't

    The chemical components of the wheat samples showed considerable variation, with coefficients of variation above 10% for ether extract, crude fiber, neutral detergent fiber, calcium, and total phosphorus. The standardized ileal digestibility values of the 15 analyzed amino acids differed significantly among wheat samples, and most amino acids were significantly correlated with different chemical measures in each growth period; the best-fitting brooding-period model was the serine equation with R² = 0.869, while four growing-period equations had R² > 0.80.

    What to keep in mind

    The abstract does not describe limitations beyond the fact that the study used 10 wheat samples and one pullet strain. The summary also does not provide the full set of prediction equations or detail how well each amino acid model performed beyond the reported best fits.

    • Wheat samples from different sources varied substantially in chemical composition.
    • Standardized ileal amino acid digestibility differed significantly across the wheat samples.
    • Digestibility in pullets was linked to different wheat properties in brooding and growing periods.
    • A serine-based equation had the best brooding-period fit, with R² = 0.869.
    • Four growing-period prediction equations had R² values above 0.80.
  • Hayman’s diallel analysis found mixed inheritance patterns in durum wheat traits

    Hayman’s diallel analysis found mixed inheritance patterns in durum wheat traits

    What the study found

    The study found that inheritance patterns for eight agronomic traits in durum wheat differed across F1 and F2 generations. Plant height was mainly controlled by additive gene action, while several yield-related traits showed non-additive inheritance and overdominance.

    Why the authors say this matters

    The authors conclude that these patterns support different breeding strategies for different traits. They suggest pedigree selection for additive traits in early generations and recurrent or advanced-generation selection for yield components, to improve durum wheat under semi-arid Mediterranean conditions.

    What the researchers tested

    The researchers used Hayman's diallel analysis, a breeding design for estimating how parental genes influence traits, in a 4 × 4 half-diallel mating scheme. They evaluated F1 and F2 progenies in field trials at the INRAA experimental station in Sétif, Algeria, during the 2021-2022 and 2023-2024 growing seasons.

    What worked and what didn't

    Significant genotypic variation was found across all studied traits. Plant height showed predominantly additive gene action, while spike length and number of grains per spike shifted from overdominance in F1 to partial dominance in F2, and spike weight, number of spikes per plant, and grain yield showed persistent non-additive inheritance and overdominance across generations.

    What to keep in mind

    The abstract does not describe detailed limitations. It also reports that dominance effects decreased in F2 for most traits and that allele distribution was asymmetric, but it does not provide additional caveats beyond the study's own breeding context.

    • Eight agronomic traits were analyzed in durum wheat F1 and F2 progenies.
    • Plant height was predominantly governed by additive gene action.
    • Spike length and number of grains per spike shifted from overdominance in F1 to partial dominance in F2.
    • Spike weight, number of spikes per plant, and grain yield showed persistent non-additive inheritance across generations.
    • High broad-sense heritability and variable narrow-sense heritability led the authors to recommend generation-specific breeding strategies.
  • Hybrid agri-food practices support rural producer resilience

    Hybrid agri-food practices support rural producer resilience

    What the study found

    The review found that hybrid practices combining social innovation and sustainable entrepreneurship in agri-food systems were associated with socio-environmental resilience for rural producers. The abstract says these practices worked best when they were embedded in favorable institutional environments and supported by public policies and legal frameworks.

    Why the authors say this matters

    The authors conclude that the findings offer practical guidance for policymakers and practitioners designing integrated rural development strategies. The study suggests that cross-sector collaboration and enabling institutional conditions matter for long-term sustainability of hybrid agri-food initiatives.

    What the researchers tested

    The researchers carried out a systematic review using PRISMA 2020 methodology. They characterized social innovation and sustainable entrepreneurship practices, assessed their effects across sustainability dimensions, and identified success factors and barriers in agri-food initiatives.

    What worked and what didn't

    The review found more studies on social innovation than on sustainable entrepreneurship, with cases from Europe, Africa, Asia, Oceania, and the Americas. Reported benefits included social inclusion, community empowerment, market access, income diversification, and improved environmental practices; facilitating factors included collaborative governance, local leadership, and the ability to combine different resources. Barriers included regulatory frameworks that did not fit the initiatives, reliance on external funding, and tensions between economic and socio-environmental goals.

    What to keep in mind

    The abstract does not describe study-level quality limits or detailed evaluation criteria beyond the review approach. It also notes that the evidence base was more developed for social innovation than for sustainable entrepreneurship.

    • The review linked hybrid social innovation and sustainable entrepreneurship practices to socio-environmental resilience in rural agri-food settings.
    • Reported benefits included social inclusion, community empowerment, market access, income diversification, and better environmental practices.
    • Key facilitators were collaborative governance, local leadership, and the ability to combine heterogeneous resources.
    • Main barriers included poorly adapted regulations, dependence on external funding, and tensions between economic and socio-environmental goals.
    • The evidence base was larger for social innovation than for sustainable entrepreneurship.
  • Genome-wide mapping identified malt-quality loci in Ethiopian barley

    Genome-wide mapping identified malt-quality loci in Ethiopian barley

    What the study found

    The study found significant genetic variation in malt quality traits across Ethiopian barley genotypes and identified 19 significant genomic loci associated with these traits. The authors also reported moderate to high narrow-sense heritability for the traits they measured, suggesting strong genetic control.

    Why the authors say this matters

    The authors conclude that the identified loci are promising molecular markers for marker-assisted selection, a breeding approach that uses DNA markers to help choose plants with desired traits. They say this provides tools for developing improved malting barley cultivars in Ethiopia.

    What the researchers tested

    The researchers evaluated a panel of 260 barley genotypes across four sites in Ethiopia for five malt-quality traits. They used Illumina 50K iSelect single nucleotide polymorphism markers and six multi-locus genome-wide association study models to look for genomic regions linked to those traits.

    What worked and what didn't

    Extract content ranged from 81.66% to 60.00%, and protein content ranged from 17.63% to 9.03% across the genotypes. The study reported that the highest number of significant associations was found on chromosomes 4H, 6H, and 7H, and that the significant loci had LOD scores from 3.06 to 5.36, r² values from 6.98% to 25.35%, and minor allele frequencies from 0.054 to 0.465.

    What to keep in mind

    The abstract does not describe detailed limitations beyond noting that further functional validation of the identified loci is needed. The results are based on Ethiopian barley germplasm and the traits and markers tested in this panel, so the summary should be understood within that scope.

    • A panel of 260 Ethiopian barley genotypes was tested across four sites.
    • The study identified 19 significant loci associated with malt quality traits.
    • Extract content and protein content varied widely across the genotypes.
    • The traits showed moderate to high narrow-sense heritability.
    • The authors say the loci may help marker-assisted selection in breeding.

  • Drip fertigation improved winter wheat yield and nitrogen uptake

    What the study found

    Drip fertigation, a method that delivers water and fertilizer through drip irrigation, increased winter wheat grain yield and nitrogen uptake compared with conventional management. The study also found that it shifted the best planting density upward and made high yields less sensitive to planting-density changes.

    Why the authors say this matters

    The authors conclude that drip fertigation may help winter wheat maintain high yield and reduce yield losses when planting density is not exactly at the optimum. They also suggest it improves the coordination between the plant's source and sink, meaning the balance between dry matter production and grain demand.

    What the researchers tested

    The researchers compared conventional management with drip fertigation across a wide planting-density range from 100 to 800 seeds per square meter over two growing seasons. They measured grain yield, yield components, population traits, dry matter production, source-sink indices, canopy nitrogen status, nitrogen uptake, and nitrogen-use efficiency.

    What worked and what didn't

    Across seasons, drip fertigation increased grain yield by 15.4% to 20.8% relative to conventional management. Yield followed a quadratic response to planting density under both regimes, but drip fertigation raised the optimal planting density to 456-487 seeds per square meter, compared with 377-378 under conventional management, and sustained near-maximum yields across a broader range of densities. It also increased productive stem percentage, grains per ear, post-anthesis dry matter production, post-anthesis nitrogen uptake, total nitrogen uptake at maturity, grain nitrogen accumulation, fertilizer-nitrogen recovery efficiency, and agronomic efficiency.

    What to keep in mind

    The abstract describes two growing seasons and the planting-density range tested, so the findings are limited to those conditions. It does not describe broader environmental limitations, economic tradeoffs, or whether the results would hold in other regions or wheat varieties.

    • Drip fertigation increased winter wheat grain yield by 15.4% to 20.8% versus conventional management.
    • The optimal planting density was higher under drip fertigation than under conventional management.
    • Drip fertigation improved productive stem percentage, grains per ear, and grain number per square meter.
    • Post-anthesis dry matter production and post-anthesis nitrogen uptake were both higher with drip fertigation.
    • Fertilizer-nitrogen recovery efficiency and agronomic efficiency also increased under drip fertigation.

  • Global green wave centroid shifts north and east

    What the study found

    The study found that the global "green wave" centroid, meaning the seasonal movement of vegetation across Earth, shifts northward during both boreal and austral summer. It also found that the eastward shift is accelerating, while the overall trajectory amplitude is decreasing.

    Why the authors say this matters

    The authors conclude that tracking the green wave's centroid reveals how changing land dynamics across regions affect the global functioning of Earth's terrestrial biosphere. They present this as a way to better quantify global phenology, meaning seasonal timing in vegetation.

    What the researchers tested

    The researchers proposed a concept to quantify global phenology by tracking the green wave's centroid using satellite data and Earth system model data. They used this trajectory to summarize global phenological dynamics and directional trends.

    What worked and what didn't

    The centroid approach identified northward movement during both summer periods, with the austral summer shift consistently larger than the boreal summer shift across datasets. It also detected an accelerating eastward shift and a decreasing trajectory amplitude, which the abstract says is projected to intensify throughout this century.

    What to keep in mind

    The abstract does not describe detailed limitations beyond noting that a unified metric had been lacking. It also does not provide numerical values in the summary provided here.

    • The global green wave centroid shifts northward in both boreal and austral summer.
    • The austral summer northward shift is consistently larger than the boreal summer shift across datasets.
    • The green wave trajectory amplitude is decreasing and is projected to intensify this century.
    • An accelerating eastward shift was detected and described as previously unreported.
    • The approach uses satellite and Earth system model data to track global phenology.
  • Chefs’ views may limit plant-based meat dishes on menus

    Chefs’ views may limit plant-based meat dishes on menus

    What the study found

    The study found that chefs' hesitation to offer plant-based meat dishes is linked to several factors, including popularity, familiarity, taste, enjoyment of cooking, naturalness, environmental sustainability, cost, and product availability. The authors also report that educating chefs about plant-based meat appears to be a promising way to increase these dishes on restaurant menus.

    Why the authors say this matters

    The authors say replacing some meat dishes with plant-based alternatives would make the hospitality industry more environmentally sustainable. They conclude that educating chefs on plant-based meat could be a leverage point for increasing the availability of meat alternatives in restaurants.

    What the researchers tested

    The researchers used a sequential mixed-methods design, meaning they combined interviews and a survey. They first interviewed 37 Australian restaurant chefs and managers to identify why chefs hesitate to offer plant-based meat dishes, then used those insights to develop a mini-theory and test it in a quantitative survey study.

    What worked and what didn't

    The interviews suggested several reasons for not using plant-based meat: popularity, familiarity, taste, enjoyment of cooking, naturalness, environmental sustainability, cost, and availability. The later survey was used to test the mini-theory and to identify opportunities for encouraging chefs to offer plant-based meat dishes, but the abstract does not give detailed survey results.

    What to keep in mind

    The summary available here does not report detailed quantitative findings from the survey. The study focused on the demand side and on Australian restaurant chefs and managers, so its scope is limited to that context.

    • The study links chefs' reluctance to serve plant-based meat dishes to several practical and preference-related factors.
    • Interviews were conducted with 37 Australian restaurant chefs and managers.
    • The researchers used interview findings to build a mini-theory and then tested it with a survey.
    • The authors suggest educating chefs about plant-based meat may help increase menu availability.
    • The abstract does not provide detailed survey outcomes.

  • Wheat canopy temperature varies by time of day and growth stage

    What the study found

    The study found that canopy temperature in wheat changed strongly across the day and across growth stages, and that the best time to measure it depended on whether plants were rainfed or irrigated. It also found that a single measurement time can miss short heat events and can give an incomplete picture of thermal status.

    Why the authors say this matters

    The authors conclude that multi-temporal phenotyping, meaning repeated temperature measurements over time, is needed for breeding and physiological interpretation under drought and heat. They also suggest that context-specific measurement windows are important because the optimal time for discrimination changed with environment and stage.

    What the researchers tested

    The researchers measured wheat canopy temperature (the temperature of the plant canopy) across different hours of the day, growth stages, and environments under Mediterranean conditions. They compared rainfed and irrigated conditions, analyzed variance components, examined clustering and alluvial patterns, and modeled canopy temperature responses to vapor pressure deficit, a measure of how dry and demanding the air is for water loss.

    What worked and what didn't

    Genotypic discrimination peaked around mid-afternoon, near 15:00, under rainfed conditions, while under irrigation the best window shifted with stage to about 13:30-15:00. Variance-component analyses showed a strong genetic signal, with 87.6-97.7% of total variance attributable to genotypic effects pooled across hours. Genotype rankings were less stable across hours under rainfed conditions, CT > 32 °C depended strongly on time of day and stage, and CT-vapor pressure deficit sensitivity was largely environment-dependent with weak cross-environment correspondence (Spearman ρ = -0.166).

    What to keep in mind

    The abstract does not describe specific limitations beyond noting that single-time-point phenotyping is incomplete. The reported findings are based on wheat breeding under Mediterranean conditions, so the scope in the abstract is limited to that context.

    • Canopy temperature in wheat varied strongly by hour of day and growth stage.
    • The optimal measurement window depended on environment: rainfed plants peaked around 15:00, while irrigated plants peaked around 13:30-15:00 depending on stage.
    • Most variance in canopy temperature was attributed to genotypic effects, at 87.6-97.7% across hours.
    • Canopy temperatures above 32 °C depended strongly on time of day and stage, and maximum values captured short heat events missed by daily means.
    • Genotype rankings changed more across hours under rainfed conditions, showing within-day re-ranking.
    • CT-vapor pressure deficit sensitivity varied by environment and showed weak cross-environment correspondence.