Agricultural & Environmental Letters最新文献

We evaluated a geospatially explicit phosphorus (P) use efficiency (PUE) monitoring method in crop fields using proximal sensing, field observations, and machine learning. Corn (Zea mays L.) yield and grain protein content were measured using an Ag Leader yield monitor and a CropScan sensor near Riesel, Texas. Topsoil P (0–15 cm) and grain P levels were analyzed for samples collected at strategic field locations. A random forest model was trained to predict PUE using soil electrical conductivity (EC_a) from a Veris instrument and topographic variables as predictors (R² = 0.78, root mean squared error = 0.01). CropScan sensor effectively estimated grain P content, supporting field-wide PUE upscaling. EC_a and elevation were the primary drivers of PUE variation. The resulting maps are valuable for monitoring PUE in crop fields and guiding variable-rate fertilizer applications. This scalable approach provides a robust framework for monitoring nutrient dynamics and efficiency, informing precision management strategies to enhance yield and sustainability in crop production systems.

Soybean [Glycine max (L.) Merr.] seed critical amino acid (CAA) content is a key quality factor for buyers worldwide, yet its spatial variability remains unclear. This study evaluated the correlation between growing latitude and CAA content in soybean seed using published data. Pearson's r values were extracted, converted to Fisher's Z as an effect-size metric, and analyzed using a random-effects model. Lysine, cystine, methionine, and tryptophan showed no significant correlations, while threonine exhibited a significant negative correlation with absolute latitude (Z = −0.50, p = 0.04). Subgroup analysis revealed additional significant correlations for lysine in soybean meal (Z = −0.74, p = 0.04) and for threonine (chemical methods to measure CAAs: Z = −0.58, p = 0.03; studies conducted outside the United States: Z = −0.78, p = 0.02). The absence of consistent correlations across multiple soybean-growing regions worldwide suggests that latitude alone should not determine a buyer's purchasing decision regarding soybean CAA content.

Biosolids are commonly used as soil amendments; however, repeated application of biosolids results in phosphorus (P) accumulation, elevating environmental risks by increasing P loss through runoff and leaching. Predicting soil P loss after ceasing biosolids application remains challenging. In a laboratory experiment, 80 leaching events were applied to sandy soils with biosolids application histories from active use to 15 years post-application. Soils with recent applications showed an early peak in P release that later stabilized, while those with legacy applications exhibited lower but more consistent P release. These results suggest that fresh biosolids contained a highly mobile P fraction that depletes over time, leaving behind more fixed P that may persist for decades. These P release trajectories could be reasonably modeled by two-pool exponential decay models. Overall, these findings highlight the importance of biosolids aging in regulating P dynamics and identify the hot moments in P loss in biosolids-impacted systems.

Cover crop mixtures provide ecosystem services, but species’ relative abundance in mixtures is challenging to manage. We report on an 11-year experiment where our main objective was to use species selection and seeding rate adjustments over time to increase the evenness of mixtures. Replacing rye with triticale and red clover with crimson clover while adjusting seeding rates resulted in mixtures that were more even and closer to the desired composition (greater legume biomass) than the original communities. For example, the first version of a six-species mixture produced biomass composed of 81% grass, 5% brassica, and 14% legume, but after adjustments, subsequent versions contained 25% grass, 10% brassica, and 65% legume biomass. Substituting a less aggressive grass for a dominant grass and a more aggressive legume for a weaker legume better balanced the mixture to meet farmers’ ecosystem service goals, as did reducing the proportion of grass seed in the mixtures.

Robusta (Coffea canephora Pierre ex Froehner) is a vital cash crop for smallholder farmers in the Ecuadorian Amazon. However, fertility recommendations for robusta production are highly variable across contexts, necessitating regionally tailored recommendations to better diagnose yield-limiting nutrients. Across a gradient of input intensities and agroforestry reflective of local practices, we employed the least absolute shrinkage and selection operator (LASSO) regression to identify which soil fertility measures and leaf nutrients best explained robusta yields across replicated management system treatments in the Ecuadorian Amazon. Leaf nutrients, particularly calcium and magnesium, were stronger and more parsimonious predictors of yields than soil inorganic nitrogen and Mehlich-3 extractable phosphorus and potassium. Although the LASSO model provided reasonable yield estimates (R² = 0.74; root mean square error = 0.23 kg tree⁻¹), model underestimation of yields >1.0 kg tree⁻¹ suggests that other factor(s) not captured by soil and foliar nutrient measures may limit cherry production in higher-yielding systems.

Agronomic use of specialty products known as biostimulants to improve crop productivity is growing. Traditionally, biostimulants are defined as any substance or microorganism applied to plants to enhance nutrient use efficiency, tolerance to abiotic stress, and crop yield and/or quality. However, grouping non-living products with living microbial inoculants poses regulatory guideline challenges. Moreover, peer-reviewed literature and regulatory legislation utilize “biostimulants” while industry and farmers have recently adopted the term “biologicals,” confusing discussions related to product regulation and policy. To better understand the challenges associated with this input sector, we have focused on four critical aspects: (1) the current regulatory status, (2) terminology disparity of biostimulants and biologicals, (3) key attributes that distinguish microorganisms from non-living biostimulants, and (4) mechanism of action differences between plant growth-promoting microorganisms and plant growth regulators. Therefore, we propose that living beneficial microorganisms and non-living biostimulants be separated with distinct regulatory requirements.

Management of phosphorus (P) inputs to agroecosystems is often evaluated by phosphorus use efficiency (PUE), but different calculation approaches may yield discrepancies in estimated PUE values. We evaluated PUE (i) indirectly calculated by difference in crop P uptake between a P-fertilized versus a P-unfertilized control (PUE_diff) and (ii) directly measured by tracing radioisotopically labeled fertilizer P (PUE_isotope). Using two ammonium phosphate fertilizers of high (monoammonium phosphate [MAP]) and low (struvite) water solubility in three soils with non-limiting extractable soil P concentrations (Mehlich-3 P > 25 mg kg⁻¹), we find dissimilar PUE_isotope versus PUE_diff. PUE_diff often yielded negative values (77% of observations), whereas PUE_isotope was (i) positive and (ii) higher (two- to fourfold) for MAP than struvite, and (iii) unassociated with soil Mehlich-3 P concentrations. Thus, PUE_diff appears to underestimate PUE and miss differences in PUE among fertilizerss. Our results raise the need to reconsider calculation of PUE and to address practical challenges to in situ measurement of PUE_isotope.

Knowledge Graphs organize and connect disparate data for integrating information in a user-friendly interface for recommendations and applications. This analytical tool for supporting data interrogation has not been widely applied in agronomy. This article focuses on Knowledge Graph applicability and specifically the utility of the recently released Esri ArcGIS Knowledge platform for identifying system resilience using a community-driven database (Forage Data Hub; 52,997 entries from 108 unique locations over 51 years) comprising legacy datasets encompassing multiple temporal and spatial scales. Overall, perennial systems had greater drought risk resilience estimates (DRRE) than annuals, with alfalfa (Medicago sativa) having a “very high” DRRE across ecoregions. Knowledge Graphs provided information on how geography and agronomic systems interact to impact resilience. Results can be used to design agricultural systems within specific geographic locations with greater resilience and stability in the face of a changing climate per geographic region.