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BACKGROUND AND AIMS: Acid soils constrain legume growth and biochars have been shown to address these constraints and enhance biological N₂ fixation in glasshouse studies. A dissection of causal mechanisms from multiple crop field studies is lacking. METHODS: In a sub-tropical field study, faba bean (Vicia faba L.) was cultivated in rotation with corn (Zea mays) following amendment of two contrasting biochars, compost and lime in a rhodic ferralsol. Key soil parameters and plant nutrient uptake were investigated alongside stable ¹⁵ N isotope methodologies to elucidate the causal mechanisms for enhanced biological N₂ fixation and crop productivity. RESULTS: Biological N₂ fixation was associated with plant Mo uptake, which was driven by reductions in soil acidity following lime and papermill (PM) biochar amendment. In contrast, crop yield was associated with plant P and B uptake, and amelioration of soil pH constraints. These were most effectively ameliorated by PM biochar as it addressed both pH constraints and low soil nutrient status. CONCLUSIONS: While liming resulted in the highest biological N₂ fixation, biochars provided greater benefits to faba bean yield by addressing P nutrition and ameliorating Al toxicity.

This investigation combines two independent methods of identifying crop growing conditions and husbandry practices—functional weed ecology and crop stable carbon and nitrogen isotope analysis—in order to assess their potential for inferring the intensity of past cereal production systems using archaeobotanical assemblages. Present-day organic cereal farming in Haute Provence, France features crop varieties adapted to low-nutrient soils managed through crop rotation, with little to no manuring. Weed quadrat survey of 60 crop field transects in this region revealed that floristic variation primarily reflects geographical differences. Functional ecological weed data clearly distinguish the Provence fields from those surveyed in a previous study of intensively managed spelt wheat in Asturias, north-western Spain: as expected, weed ecological data reflect higher soil fertility and disturbance in Asturias. Similarly, crop stable nitrogen isotope values distinguish between intensive manuring in Asturias and long-term cultivation with minimal manuring in Haute Provence. The new model of cereal cultivation intensity based on weed ecology and crop isotope values in Haute Provence and Asturias was tested through application to two other present-day regimes, successfully identifying a high-intensity regime in the Sighisoara region, Romania, and low-intensity production in Kastamonu, Turkey. Application of this new model to Neolithic archaeobotanical assemblages in central Europe suggests that early farming tended to be intensive, and likely incorporated manuring, but also exhibited considerable variation, providing a finer grained understanding of cultivation intensity than previously available.

Aim: To simulate the sowing dates of 11 major annual crops at the global scale at high spatial resolution, based on climatic conditions and crop-specific temperature requirements. Location: Global. Methods: Sowing dates under rainfed conditions are simulated deterministically based on a set of rules depending on crop-and climate-specific characteristics. We assume that farmers base their timing of sowing on experiences with past precipitation and temperature conditions, with the intra-annual variability being especially important. The start of the growing period is assumed to be dependent either on the onset of the wet season or on the exceeding of a crop-specific temperature threshold for emergence. To validate our methodology, a global data set of observed monthly growing periods (MIRCA2000) is used. Results: We show simulated sowing dates for 11 major field crops world-wide and give rules for determining their sowing dates in a specific climatic region. For all simulated crops, except for rapeseed and cassava, in at least 50% of the grid cells and on at least 60% of the cultivated area, the difference between simulated and observed sowing dates is less than 1 month. Deviations of more than 5 months occur in regions characterized by multiple-cropping systems, in tropical regions which, despite seasonality, have favourable conditions throughout the year, and in countries with large climatic gradients. Main conclusions: Sowing dates under rainfed conditions for various annual crops can be satisfactorily estimated from climatic conditions for large parts of the earth. Our methodology is globally applicable, and therefore suitable for simulating sowing dates as input for crop growth models applied at the global scale and taking climate change into account.

The moth pest fall armyworm, Spodoptera frugiperda (J.E. Smith) (Lepidoptera: Noctuidae) is now present throughout much of the Eastern Hemisphere where it poses a significant economic threat to a number of crops. Native to the Western Hemisphere, fall armyworm is one of the primary pests of corn in the Americas and periodically causes significant economic damage to sorghum, millet, cotton, rice, and forage grasses. This broad host range is in part the result of two populations historically designated as host strains (C-strain and R-strain) that differ in their host plant preferences. Reports of infestations in Africa have to date mostly been limited to the C-strain preferred crops of corn and sorghum, with little evidence of an R-strain presence. However, this could reflect a bias in monitoring intensity, with the R-strain perhaps being more prevalent in other crop systems that have not been as routinely examined for the pest. Because knowledge of whether and to what extent both strains are present is critical to assessments of crops at immediate risk, we analyzed specimens obtained from a systematic survey of pasture grass and rice fields, habitats typically preferred by the R-strain, done contemporaneously with collections from corn fields in Ghana and Togo. Substantial larval infestations were only observed in corn, while pheromone trap capture numbers were high only in corn and rice habitats. Little to no fall armyworm were found in the pasture setting. Comparisons with a meta-analysis of studies from South America identified differences in the pattern of strain-specific markers typically found in fall armyworm collected from rice habitats between the two hemispheres. Genetic tests of specimens from rice and corn area traps failed to show evidence of differential mating between strains. These results are consistent with the R-strain being rare or even absent in Africa and, at least for the Ghana-Togo area, this R-strain lack does not appear to be due to limitations in pest monitoring. The implications of these results to the crops at risk in Africa and the accuracy of existing molecular markers of strain identity are discussed.

Precision weed management, an application of precision agriculture, accounts for within-field variability of weed infestation and herbicide damage. Unmanned aerial vehicles (UAVs) provide a unique platform for remote sensing of field crops. They are more efficient and flexible than manned agricultural airplanes in acquiring high-resolution images at low altitudes and low speeds. UAVs are more universal than agricultural aircraft, because the latter are used only in specific regions. We have developed and used UAV systems for red-green-blue digital and color-infrared imaging over crop fields to identify weed species, determine crop injury from dicamba at different doses, and detect naturally grown glyphosate-resistant weeds. This article presents remote sensing technologies for weed management and focuses on development and application of UAV-based low-altitude remote sensing technology for precision weed management. In particular, this article futher discusses the potential application of UAV-based plant-sensing systems for mapping the distributions of glyphosate-resistant and glyphosate-susceptible weeds in crop fields. Nomenclature: Dicamba; glyphosate

Soil salinization threatens crop production; however, in multi-crop field systems, evidence for the effectiveness of waste biomass-functional microorganism composite amendments remains limited. Here, we developed a composite microbial soil conditioner (F2) using pine needles and crushed corn cobs as carriers combined with salt-tolerant strains Bacillus subtilis (K1), Azotobacter chroococcum (Y1), and Bacillus gelatinus (J3) to remediate moderately saline-alkali soil from central Gansu (pH 8.36 ± 0.18; EC 1658 ± 55.24 μS·cm−1). Saturation screening identified an optimal carrier ratio of pine needles:corn cobs = 1:2 and an inoculum ratio of K1:Y1:J3 = 1:2:1. In pot experiments, F2 increased soil organic matter and water-holding capacity, enhanced alkaline phosphatase, urease, and sucrase activities, and significantly reduced soil pH and EC. Maize seedling height and chlorophyll content increased by 53.87% and 38.88%, respectively. Amplicon-based microbiome profiling indicated enrichment of beneficial microbial taxa and strengthened primary metabolic functions under F2. Field validation across five crops (flax, potato, edible sunflower, sorghum, and maize) showed consistent growth and yield-related improvements. Overall, these results demonstrate that the biomass–microbe composite amendment effectively alleviates saline-alkali constraints by jointly improving soil properties, microbial functions, and crop performance.

Accurate crop mapping is a fundamental requirement in various agricultural applications, such as inventory, yield modeling, and resource management. However, it is challenging due to crop fields’ high spectral, spatial, and temporal variabilities. New technology in space-borne Earth observation systems has provided high spatial and temporal resolution image data as a valuable source of information, which can produce accurate crop maps through efficient analytical approaches. Spatial information has high importance in accurate crop mapping; a Window-based strategy is a common way to extract spatial information by considering neighbourhood information. However, crop field boundaries implicitly exist in image data and can be more helpful in identifying different crop types. This study proposes Guided Filtered Sparse Auto-Encoder (GFSAE) as a deep learning framework guided implicitly with field boundary information to produce accurate crop maps. The proposed GFSAE was evaluated over two time-series datasets of high-resolution PlanetScope (3 m) and RapidEye (5 m) imagery, and the results were compared against the usual Sparse Auto Encoder (SAE). The results show impressive improvements in terms of all performance metrics for both datasets (namely 3.69% in Overal Accuracy, 0.04 in Kappa, and 4.15% in F-score for the PlanetScope dataset, and 3.71% in OA, 0.05 in K, and 1.61% in F-score for RapidEye dataset). Comparing accuracy metrics in field boundary areas has also proved the superiority of GFSAE over the original classifier in classifying these areas. It is also appropriate to be used in field boundary delineation applications.

Semi-natural grasslands in Europe are insect biodiversity hotspots and important source habitats delivering ecosystem services to adjacent agricultural land by species spillover. However, this spillover might also occur in the opposite direction, affecting the diversity of semi-natural grasslands. This opposite spillover has got little attention in scientific literature even though generalist species penetrating into the grasslands can affect local biotic interactions, community composition and the conservation value of grassland habitats. In this study, we examined spillover effects from two different adjacent habitat types on carabid beetle assemblages in 20 semi-natural calcareous grasslands. The grasslands were either adjacent to a cereal crop field or to a coniferous forest. We found distinct differences in carabid beetle assemblages in calcareous grasslands depending on adjacent habitat type. Species richness and activity density were higher, but the evenness was lower in calcareous grasslands adjacent to crop fields compared with calcareous grasslands adjacent to coniferous forests. Further, we found a strong spillover of carabid beetles from adjacent crop fields after crop harvest, which may result in transiently increased predation pressure and resource competition in calcareous grasslands. Our results highlight that species composition, diversity and presumably ecosystem functions within semi-natural habitats are affected by the type and management of surrounding habitats. This needs to be considered by nature conservation measures, which aim to protect the unique insect communities of semi-natural European grasslands.

This study was conducted to determine status of heavy metals in agricultural soils under different patterns of land use. A total of 38, 40 and 45 soil samples for bare vegetable field, greenhouse vegetable field, and grain crop field were respectively taken from surface layer (0-20 cm) from selected experimental areas away from suburbs of ten counties (or districts or cities) in four provinces or municipalities of Huabei plain in north China. Information of crop production history, including varieties, rotation systems and fertilizer use, at the corresponding sampling sites was surveyed. Soil total Cu, Zn, Cd, Pb, Cr, As and Hg were measured. The results showed that the contents of total Cu, Zn, Cd, Pb, Cr, As, and Hg in the soil samples, especially soil total Cu and Zn contents, were higher in the bare vegetable field and the greenhouse vegetable field than that in the grain crop field. Long-term use of excessive chemical fertilizers and organic manures in the bare vegetable field and the greenhouse vegetable field contributed to the accumulation of Cu, Zn, and other heavy metals in the soils. The contents of total Cu, Zn, and other heavy metals in soils increased with increasing vegetable production history of the research areas. In comparison with the grain crop field, the comprehensive pollution indices of the seven soil heavy metals and the single-factor pollution indices of soil Zn, Cu, Cd, Cr, and Hg based on the second criterion of Environmental Quality Standard for Soils were significantly higher in the bare vegetable field and the greenhouse vegetable field. Soils from the greenhouse vegetable field were slightly contaminated according to the comprehensive pollution index, and soils from the bare vegetable field and the grain crop field were at the warning heavy metal pollution level. The soils were contaminated with Cd according to the single-factor pollution index. The Cd pollution was relatively more serious in the bare vegetable field and the greenhouse vegetable field than that in the grain crop field. The soils selected with different land use patterns were not contaminated with Zn, Cu, Pb, Cr, As and Hg.

In most of Nigeria’s rural communities, land holdings are small and uneven; and this impacts significantly on their mechanisation potentials. This fragmented nature of the farmlands also inhibits the creation of an effective land market. This study utilised a digital orthomosaic generated from an Unmanned Aerial Vehicle (UAV) survey in evaluating the productivity levels of traditional and mechanised farmers in Okeho Community of Oyo State, South-Western Nigeria. The aerial survey was conducted with a DJI Phantom 4 Professional UAV covering 250 acres of traditional and mechanised farmlands to produce a very high resolution orthomosaic at 6 cm spatial resolution. Sixty-three respondents (61 traditional farmers and 2 mechanised farmers) were also interviewed using questionnaires. Their responses were keyed into a database with the Open Data Kit (ODK) data collector. The orthomosaic was classified into farmland units and a database of the farmers land holdings was created in ArcGIS software. Some parameters influencing their productivity were computed – Crop Field Fraction (CFF) and Crop Yield Index (CYI). The results showed that very few farmers had a shared equity on land (only 3%); most farms were acquired under freehold or lease. Also, only 1% of their farm sizes was larger than 5 acres. There was a sharp disparity in the crop field fraction (traditional farms – 32.2; mechanised farms – 68.8), and the productivity from the mechanised farmers surpasses that of the traditional farmers. It is recommended that the Government should support cluster farming systems among farmers to boost productivity.