Agronomy Journal最新文献

Management zone (MZ) or variability zone delineation is a critical component of precision agriculture (PA), enabling site-specific management to optimize crop production and resource efficiency in response to within-field variability. This study evaluated whether digital soil maps (DSM or continuous soil property prediction maps) can serve as a superior information layer compared to the Soil Survey Geographic Database (SSURGO) for soil MZ delineation. High-resolution DSM data of four farmer fields in northeast Oklahoma, including soil features such as macro- and micronutrients, soil texture, and chemical properties at multiple depths, were used in two clustering techniques, k-means and fuzzy c-means (FCM), to delineate DSM-based MZs. Performances of DSM- and SSURGO-based MZs were evaluated using the variance reduction (VR) index based on yield monitor data from four fields between 2014 and 2020. In a baseline comparison (i.e., same number of MZs), k-means and FCM achieved a relative VR increase of 78% on average across all fields compared to SSURGO (with an absolute VR difference of 4%). When the number of MZs increased, VR was further improved by DSM-based clustering, particularly with four to five MZs (VR increased by 236% with five MZs, with an absolute VR difference of 13%). Our results showed that DSM-based clustering outperformed SSURGO-based zoning in reducing the within-zone yield variability. The leverage of DSM and clustering techniques enabled finer-scale on-farm yield variability detection and therefore enhances MZ precision. The insights from this study can inform future site-specific management strategies, ultimately supporting sustainable resource allocation, optimizing inputs, and minimizing environmental impacts.

Drought is a major constraint for oat (Avena sativa L.) production, particularly during critical growth stages. Understanding genotypic responses to drought stress and identifying sensitive periods are essential for improving resilience. We evaluated the effects of drought severity and duration on two oat genotypes, Ajay and Hayden, under greenhouse conditions. Treatments were severe drought: 40% of water-holding capacity (WHC); moderate drought: 60% of WHC; and well-watered: ≥85% of WHC. Treatments were imposed during the heading, flowering, and grain filling stages until harvesting. Overall grain yield decreased by 23% and 41.5% under moderate and severe drought conditions, respectively, compared to the well-watered condition. Hayden had higher grain yields, relative water content (RWC), and water use efficiency (WUE) than Ajay across all drought levels. Ajay showed higher root-to-shoot ratio, tiller number, and panicle number; however, these traits did not improve yield or leaf hydration under drought stress. Yield correlated strongly with yield components, such as panicle number and seed weight, compared to physiological traits, including soil plant analysis, development chlorophyll index, and RWC. Genotypes with high WUE and stable yields when exposed to drought during early reproductive stages should be prioritized in future research, which should directly measure performance under stress rather than rely on pre-maturity physiological indicators.

Pulse crops are becoming more popular to replace summer fallow in the conventional crop–fallow systems for increased crop yields, but limited information exists on the performance of pulse crops and succeeding crop yields and N dynamics in the US northern Great Plains. The objective of the study was to determine plant density, straw and grain yields, grain protein concentration, N uptake, harvest index (HI), N harvest index (NHI), N-use efficiency (NUE), and N removal index (NRI) of three pulse crops (chickpea [Cicer arietinum L.], lentil [Lens culinaris Medik], and pea [Pisum sativum L.]) and one control (spring wheat) as well as succeeding spring wheat in the rotation from 2021 to 2024. Plant density was 70%–203% greater for lentil than chickpea and pea but was 58% lower than spring wheat. Straw and grain yields and N uptake were 10%–68% greater for pea than chickpea and lentil, but yields were 25%–63% lower for pea than spring wheat. Grain protein concentration was 14%–20% greater for pea and lentil than chickpea and 27%–51% greater for pulse crops than spring wheat. The HI and NHI were 5%–25% greater for chickpea and lentil than pea and spring wheat. Spring wheat straw and grain yields, NUE, and NRI following pulse crops were 11%–21% greater than following continuous spring wheat. Because of greater grain yield and protein concentration, pea is recommended as the most effective pulse crop to replace summer fallow and increase crop yields and quality in crop–fallow systems in the northern Great Plains.

Cover crops (CCs) are increasingly recognized for their multifunctionality in provisioning, regulating, and supporting ecosystem services. CCs are characterized by different functional groups, which deliver distinct benefits, such as N fixation, nutrient scavenging, or pest suppression. Research on CCs has expanded rapidly over recent decades, yet this growth has also been accompanied by significant semantic inconsistencies in the terminology used to describe CCs, including terms such as “green manure,” “catch crops,” “trap crops,” “service plants,” “service crops,” “living mulch,” and “companion plants.” This variability is more than linguistic. It hinders literature searches, biases meta-analyses, impedes standardization, complicates policy development, and obstructs effective cross-disciplinary collaboration and knowledge transfer. Furthermore, terminological ambiguity creates inefficiencies in research and challenges for educational and algorithmic tools. To address these issues, we argue for harmonization in CC terminology, proposing that the phrase “cover crops” be systematically included in titles, abstracts, or keywords of all CC publications while allowing complementary terms to highlight specific functions of CCs. Greater consistency in language will enhance the clarity, comparability, and impact of CC research, supporting both scientific advancement and practical implementation of CCs in agroecological systems.

Growing fall cover crops (CCs) before soybeans (Glycine max L.) is an encouraged practice in the Mid-Atlantic United States. Previous studies indicated that CC termination time can influence soil moisture during the soybean growing season. However, there is a lack of studies providing comprehensive data on soil moisture dynamics and plant water stress metrics. This study was conducted over 3 site-years in Pennsylvania on silt loam and silt clay loam soils to evaluate four treatments: early planting brown (soybean planted early into pre-killed CC, i.e., terminated approximately 2 weeks before soybean planting), early planting green (soybean planted early into living CC, i.e., terminated immediately after soybean planting), late planting brown (soybean planted late into pre-killed CC), and late planting green (soybean planted late into living CC). In 1 site-year, late planting green conserved soil water content later in the growing season, compared to planting brown. In all site-years, soybean grain δ¹³C, an indicator of plant water stress, was higher in the early planting brown (−27.5‰) than in the late planting green (−28.0‰) treatment. δ¹³C was negatively correlated with CC biomass at termination (r = −0.40) and yield (r = −0.50). When soybeans were planted early, soybean yield was 7%–70% higher with planting green than planting brown. Late planting green treatment yielded comparably or higher than early planting brown. These findings suggest that delaying CC termination to increase CC biomass can mitigate soybean water stress and translate to yield gains in the rainfed no-till systems of central and southeast Pennsylvania.

For irrigated cotton (Gossypium hirsutum L.) in Florida, the current nitrogen (N) fertilizer recommendation is 67 kg N ha⁻¹ and has not changed in the last 40 years despite changes in cultural practices and development of new varieties. A study was conducted at three locations to re-evaluate cotton [Delta Pine 2038 B3XF (DP 2038)] response to six N rates (0, 50, 101, 151, 202, and 252 kg ha⁻¹), using a randomized complete block design with four replications on sandy soils. The objectives of this study were to quantify N rate effects on (1) growth, (2) in-season petiole nitrate-N (PNN), and (3) yield and N use efficiency, with the goal of N rate optimization. Results indicate that leaf area index was maximized at 101–151 kg N ha⁻¹. Application of 101 kg N ha⁻¹ maintained PNN sufficiency throughout bloom. PNN between 7800 and 8692 mg kg⁻¹ at bloom, and 1733 and 4500 mg kg⁻¹ at 4 weeks after bloom can be considered sufficient for optimum yield. Statistically, no significant increase in biomass and lint yield was found beyond the application of 101 kg N ha⁻¹. A negative correlation was found between N applied and fertilizer N use efficiency (r = −0.85), and internal N use efficiency (r = −0.61). The best-fit linear plateau model showed 113 kg N ha⁻¹ as the agronomic and economic optimum N rate for irrigated cotton in Florida. Yield goal-based analysis indicates that 50 kg N ha⁻¹ (45 lbs N acre⁻¹) is required to produce 2.5 bales of cotton ha⁻¹ (∼1 bale acre⁻¹; 1 bale = 218 kg lint), enabling site-specific, yield-targeted N application.

The contribution rate of fertilizer nitrogen (N)—defined as the percentage of N uptake from fertilizer relative to total N uptake—is a fundamental parameter for establishing knowledge-based fertilization recommendations in crop production. This study aimed to compare the fertilizer N contribution rate for achieving maximum grain yield between double- and single-cropped rice (Oryza sativa L.). Data from four field experiments conducted between 2014 and 2023 were used to analyze the relationships of fertilizer N contribution rate and grain yield with N application rate in both double- and single-cropped rice, thereby estimating the fertilizer N contribution rate required to achieve maximum grain yield. The results showed that the fertilizer N contribution rate increased by 3.21%–3.58% and 1.92%–2.35% for each 10 kg ha⁻¹ increase in N application rate in double- and single-cropped rice, respectively. Maximum grain yields were achieved at N application rates of 190–208 kg ha⁻¹ per crop for double-cropped rice and 211–244 kg ha⁻¹ for single-cropped rice. Correspondingly, the fertilizer N contribution rates for achieving maximum grain yield ranged from 60.91% to 74.51% in double-cropped rice and from 46.90% to 49.65% in single-cropped rice. These results indicate that N fertilizers contribute more to grain yield in double- than in single-cropped rice, underscoring the importance of developing N management strategies and policies tailored to specific rice cropping systems.

Timely planting and uniform stands are prerequisites for optimal corn (Zea mays L.) production. However, frequent rainfall often limits corn acreage planted in the southeast region of the United States. Planting faster might offer a potential solution as new technology claims up to 19 km h⁻¹ planting speeds without sacrificing seed singulation or yield. The objective of this study was to evaluate corn response to varying planting speeds in Mississippi. Trials were arranged as a randomized complete block design during the 2023 and 2024 cropping seasons. A precision planter (John Deere bar and MaxEmerge 2 row units retrofitted with Ag Leader SureSpeed and SureForce) was tested at 9.7, 14.5, and 17.7 km h⁻¹ actual ground speeds. A mechanical planter (John Deere 1700 ground-driven planter equipped with eSet meters) at 9.7 km h⁻¹ was used as a standard check. Corn hybrid DKC 70-27 was planted at 81,800 and 85,000 seeds ha⁻¹ in 2023 and 2024, respectively. In both seasons, increased planting speed generally lowered plant population and quality of seed placement with increased skips and spacing variability. Planting at 14.5 km h⁻¹ optimized precision and reduced multiples using the precision planter. Moreover, planting speed beyond 14.5 km h⁻¹ did not affect corn yield. The precision planter at 17.7 km h⁻¹ exhibited improved performance over the mechanical planter at 9.7 km h⁻¹, particularly in maintaining lower miss and multiple indices. Using this technology, Mississippi corn producers can plant more land within the critical planting window at higher speeds without affecting yield.

Annual bluegrass (Poa annua L.) is a winter annual weed with limited herbicide control options in cool-season turfgrasses. This research evaluated the effect of irrigation frequency and mowing height on annual bluegrass cover in perennial ryegrass (Lolium perenne L.) in 2019 and 2020 on a 3-year-old mixed stand in “North Brunswick, NJ.” Treatments were arranged in a 2-by-2 factorial in a randomized split-plot design with mowing height (11 or 38 mm) as the main plot and irrigation frequency (once or thrice week⁻¹) as subplot. From June to October each year, both irrigation frequency treatments were irrigated to 60% reference evapotranspiration minus rainfall. Soil volumetric water content was consistently lower in once week⁻¹ irrigation treatments in both years. Annual bluegrass cover was affected by irrigation frequency and mowing height, but no interaction was detected. In October, annual bluegrass cover was reduced (47%) in once week⁻¹ treatments compared to thrice week⁻¹ treatments (59%). Additionally, annual bluegrass cover in October was reduced in treatments mown at 38 mm (46%) compared to 11 mm (60%). Irrigation frequency had no effect on turfgrass quality, green cover, or normalized difference vegetation index (NDVI); however, mowing height affected these response variables. When differences were present, all values were greater in the higher mown treatments. This research suggests reducing irrigation frequency reduces annual bluegrass cover without affecting turfgrass quality, green cover, or NDVI in the humid subtropical climate (near the Humid Continental climate zone). Additionally, increasing mowing height will reduce annual bluegrass cover.

Sodding is a method that provides immediate turfgrass cover and reduces the soil erosion potential at renovated sites. Because of its rhizomatous growth habit, Kentucky bluegrass (KB) (Poa pratensis L.) produces high-quality sod strength; however, tall fescue (TF) (Festuca arundinacea Shred.) is growing in popularity because of its superior heat and drought tolerance. The bunch-type growth habit of TF can result in weak sod strength and handling, which often requires plastic netting or the addition of KB at planting to improve sod strength during harvest and transplanting. Sod producers need more information on seeding ratios and classifications of KB when mixed with TF. Multiple field experiments in Kansas were conducted to evaluate the influence of seed mixture ratios (97:3, 95:5, and 90:10 w/w TF:KB) and KB classifications or growth aggressiveness labels on establishment speed, sod strength (maximum tensile strength and required work to tear), and sod handling (1–5 scale) at three harvests; 9, 10, and 12 months after planting. Experiment 1 results indicated 95:5 (w/w) TF:KB sod mixtures yielded similar establishment speed and sod strength across multiple harvests (12.1–15.9 N-m required work to tear sod), regardless of cultivar. Experiment 2 revealed some 95:5 and 90:10 (w/w) of TF:KB sod mixtures produced higher maximum tensile strength compared to 100% TF, but all 97:3 mixture ratios were similar in sod strength and established as quickly as 100% TF sod. Results will assist sod producers and turfgrass practitioners with information when mixing KB with TF for commercial sod.