Agronomy Journal最新文献

About 90% of the Texas High Plains area depends on the water supply from the Ogallala aquifer. The decline of the Ogallala water table raises a concern for the sustainability of producing the traditional irrigated field crops due to their high water demand. Thus, diversifying cropping systems may be a solution. However, about 70% of the irrigated cropland uses center pivots that may negatively impact specialty crop quality. Thus, a 3-year experiment was conducted to assess the potential of using mobile drip irrigation (MDI) to produce fresh watermelon compared to center pivot sprinkler irrigation using low-elevation spray application (LESA), and surface drip irrigation with plastic mulch (DI). The study evaluated the effects of irrigation systems on crop yield, fruit quality, physiological responses, water use efficiency (WUE), and irrigation use efficiency (IUE). On average, plants under MDI had higher yields (106 Mg ha⁻¹) than those under DI (70 Mg ha⁻¹) and LESA (68 Mg ha⁻¹). Plants under MDI and DI also had more fruits per plant (1.9) than those under LESA (1.4). The higher yield was associated with higher biomass and photosynthetic function. In general, fruit quality was not affected by irrigation system. In addition, plants under MDI system showed a higher WUE and IUE, and less water stress than those under LESA and DI systems. Results of this study suggest that irrigating under an MDI system is a good alternative for growers in the Texas High Plains that aim to diversify their cropping system with high-value vegetable crops such as watermelon (Citrullus lanatus).

Deviation from uniform target plant population density in sunflower (Helianthus annuus L.) production may negatively affect canopy closure, yield, and grain quality. The objective of this study was to evaluate the effects of plant density heterogeneity on yield, quality, and canopy closure in confectionery and oilseed sunflowers. Field experiments consisted of fixed differences in the number of skips/doubles per plot while maintaining equal total number of plants, and stand gaps with proportional decreasing plant counts. These were conducted in Minnesota, Texas, and Colorado, USA. Experiments revealed that yield was occasionally influenced by heterogeneity, with more uniform stand density yielding higher; however, substantial changes in uniformity of plant density often resulted in no differences in yield. Confectionery sunflowers compensated for yield losses in thinner stands mainly by producing larger seeds (observed range of 0.1%–46.2% of seeds over a 9.53 mm sieve), while oilseed sunflowers increased seed production per head (as shown by invariable test weight across treatments within environments). Plants that were unharvestable for any cause (most often due to head rot disease or lodging) were more prevalent in less uniform stands, and faster canopy closure was achieved in uniformly spaced plants. Although sunflower is very resilient to stand uniformity issues, these findings underscore the importance of uniform sunflower plant spacing for effective weed suppression and crop performance and highlight the need for further research into sunflower yield compensation mechanisms.

With an increase in the frequency of hot-dry-windy weather and reported significant increase in winter wheat (Triticum aestivum L.) in-season average temperatures, it is important to understand how soil management affects yield stability. This study quantified the combined effects of tillage and fertilizer-N on winter wheat yield stability in a wheat–sorghum [Sorghum bicolor (L.) Moench]–fallow crop rotation. The research was conducted from 1975 to 2022 and the experimental design was a randomized complete block with a split-split-plot arrangement. Crop phases were the main plots, tillage (conventional tillage [CT], reduced tillage [RT], and no-tillage [NT]) in the sub-plot, and N application rates (0, 22, 45, and 67 kg N ha⁻¹ or 0, 45, 90, and 134 kg N ha⁻¹) in the sub-sub-plot. Results showed winter wheat yield under NT increased by 0.8 Mg ha⁻¹, compared with about 1.1 Mg ha⁻¹ for CT and RT, when environmental average increased by 1 Mg ha⁻¹ for N rates ≤90 kg ha⁻¹. Yields with CT and RT increased by 0.8 Mg ha⁻¹, compared with about 1.1 Mg ha⁻¹ rate for NT, when environmental average increased by 1 Mg ha⁻¹ for N >90 kg ha⁻¹. In 30%–52% of the time, CT wheat yield was greater than NT, but yield advantage with CT decreased as fertilizer-N rate increases. Yield stability of winter wheat varied by tillage and fertilizer rate. We concluded that NT wheat required greater N rates to reach the same yield potential as CT and RT, and long-term CT or RT wheat at 45 kg N ha⁻¹ was most stable.

In Australia, the soil-borne disease common root rot (Bipolaris sorokiniana) (CRR) in wheat (Triticum aestivum L.) leads to substantial yield losses, yet has limited visible aboveground symptoms, making detection and identification labor intensive. Near-infrared (NIR) spectroscopy offers an early potential identification solution for CRR in wheat and has previously been reported with success for crop disease detection. This study investigated the ability of nondestructive NIR spectroscopy in combination with deep neural networks (DNN), logistic regression (LR), and principal component analysis combined with support vector machines (PCA-SVM) for early-stage CRR detection in wheat. NIR spectra of five different wheat varieties with varying resistance to CRR were collected in two seasons of glasshouse and three seasons of field trials using a portable spectrometer. Results demonstrated that DNN outperformed LR and PCA-SVM, achieving 66%–91% average classification accuracy in glasshouse trials and an average accuracy of 73% with up to 87% in field trials, effectively distinguishing inoculated and non-inoculated wheat plants from seedling to anthesis stages. Validation with a third season of field data achieved an average of 77% accuracy for the most susceptible variety during the stem elongation stage. NIR reflectance within 1600–1700 nm was identified as most important for estimating CRR presence, with initial detection occurring 35 days after sowing (DAS) in the glasshouse and 46 DAS in the field. In conclusion, a NIR spectrometer with a DNN model successfully performed disease classification, with the potential as a portable early disease detection tool to assist farm management decisions.

The study explored the performance of hybrid and population rye (Secale cereale) cultivars under two different crop management intensities in Poland: moderate-intensity and high-intensity management. The focus was grain yield, grain quality, yield components, and variety stability in two growing seasons (2018/2019 and 2019/2020) at three locations. Hybrid cultivars consistently yielded higher grain yields (9.81 t ha⁻¹) than population cultivars (7.90 t ha⁻¹), with increase of 24.9%. However, hybrid cultivars had lower protein content (8.94%) than population cultivars (9.77%). Spike number was the most influential factor on yield, followed by 1000-grain weight and grains per spike, regardless of cultivar type. Hybrid cultivars displayed a lower degree of stability as assessed using the ranking sum of the Shukla variance and the multi-trait stability index. Hybrid cultivars were strongly dependent on resistance to fungal diseases, including Septoria (Mycosphaerella graminicola), and increased stability under moderate-intensity management. Resistance to soil acidification became more important for cultivar stability under high-intensity management.

Long-term experiments can help to understand soil phosphorus (P) dynamics and improve nutrient management strategies. This research evaluated long-term (2002–2021) soil P dynamics and yield response to a range of P fertilizer rates in a continuous high-yielding irrigated corn (Zea mays L.) experiment with low initial soil phosphorus test (SPT, 10.5 mg kg⁻¹). The experiment was established near Clay Center, NE, and five P rates (0, 10, 20, 39, and 59 kg P ha⁻¹) were evaluated. Soil samples at 20-cm depth were collected in eight cropping seasons. Yield response to P fertilizer increased after 20 years from 0.64 to 2.79 Mg ha⁻¹. The application of 39 kg P ha⁻¹ year⁻¹ increased soil Bray-1 P to 19.5 mg kg⁻¹, outyielded all other P treatments, and resulted in a positive relative P balance. Over 20 years, 0 kg P ha⁻¹ year⁻¹ decreased Bray-1 P from 10.5 to 5.5 mg kg⁻¹. Annual P rates of 0, 10, and 20 kg P ha⁻¹ produced a negative relative P balance and SPT below the critical soil test value (CSTV). The CSTV was 22.2 mg kg⁻¹ for a continuous irrigated corn cropping system. A 53% increase in the P fertilizer rate (from 39 to 59 kg P ha⁻¹ year⁻¹) produced a threefold increment in the soil test P build-up rate. High-yielding irrigated continuous corn production systems (>14 Mg ha⁻¹) are required to apply at least 39 kg P ha⁻¹ year⁻¹ to maintain SPT and a positive relative P balance over years.

Switchgrass (Panicum virgatum L.) is one of several grass species being bred for use as a biomass crop to support the biofuel industry. Increases in biomass yield are imperative to ensure that crops such as switchgrass can sustainably meet the needs of this industry. Genomic selection is one strategy that can accelerate breeding gains for complex traits such as biomass yield. The goal of this study was to conduct three cycles of genomic selection in a previously trained Liberty switchgrass population and compare that to one cycle of phenotypic selection, both of which required 3 years to complete. The advanced lines were tested across five locations and three hardiness zones in the Central United States using a randomized complete block design with four replicates. There were strong genotype × location interactions, but the first two generations of genomic selection were superior to Liberty at four of the five evaluation locations. Conversely, phenotypic selection failed to result in significant gains in biomass yield for any of the five evaluation locations. Based on these results from Liberty switchgrass, genomic selection methods are expected to at least double the rates of gain in biomass yield relative to previous estimates using phenotypic selection methods.

Inappropriate rainfed crop management, especially wrong tillage and crop residue management, led to reduce the diversity of soil biological quality, especially soil macrofauna community, in semiarid region. This study was conducted to investigate the effect of 5 year conservation agriculture operation techniques on the quality and the diversity indices of soil macrofauna community in the rainfed lands in the west of Iran. This experiment was carried out in the statistical format of split-split plots based on a randomized completely block design with three replications. The main treatments include control or conventional tillage, compound tillage, chisel tillage, and direct cultivation (no tillage) with three sub-treatments of plant residues (no residues, one-third, and two-thirds of plant residues) in rainfed wheat (Triticum aestivum) rotation with rainfed chickpea (Cicer arietinum). Changes in soil biological quality indicators, such as soil microbial respiration were measured. Also, the indicators related to the population of soil macrofauna, including biodiversity index, uniformity index, and species richness, were measured and the effect of treatments on the measured indicators were compared with the classical statistical method of analysis of variance and Duncan's mean comparison test. The results showed that conservation agricultural treatments, including no-tillage treatment, have led to significant increase of 19% and 15% of macrofauna biodiversity index in wheat and chickpea, respectively. Also, keeping one-third of the wheat residues has led to an 18% increase in the biodiversity index of the soil macrofauna during the evaluation period. Biodiversity index and taxonomic richness of soil macrofauna were generally higher in the years of wheat than chickpea, and on the contrary, the species uniformity index of soil macrofauna biological community was higher in chickpea than wheat.

The stability of a trait refers to the extent to which its expression in a given genotype varies across environments. The more stable a trait, the less variable its expression. Grain yield stability is a central consideration in corn production to ensure that hybrids perform consistently across environments and is frequently quantified given its importance. Little attention has been paid to the stability of corn yield components, kernel number per m² (KN), and kernel weight (KW). Our hypothesis is that while previous research suggests that yield stability of commercial corn hybrids is generally consistent, the stabilities of KN and KW may exhibit significant differences, even when overall yield stability remains constant. This study evaluated the yield and yield component stabilities of 23 commercial corn hybrids conducted on-farm at five location-years in Ontario, Canada, using Finlay–Wilkinson regression. Most (61%) hybrids exhibited average yield stability with β₁-values close to 1.0. But seven hybrids displaying average yield stability had KN and/or KW stabilities significantly different than average. While in absolute terms, KW was always more stable than KN across environments, the data indicate that hybrids have different mechanisms to achieve stable yields in terms of relative yield component adjustments. Overall, 14 hybrids had yield component β₁-values significantly more or less stable than average. The instances where yield component β₁-values differed significantly from 1.0 were almost equally divided between KN and KW. These findings support the potential for hybrid-specific corn management, that is, tailoring management practices to take advantage of hybrid variation in yield component stabilities.