Low availability of phosphorus (P) is a major constraint to production of cotton (Gossypium hirsutum L.). The extent to which genotypic variation in root traits exists or contributes to P-acquisition efficiency (PAE) in cotton is unknown. To assess genetic variation in PAE, the biomass and P-acquisition characteristics of 32 cotton genotypes were evaluated in a hydroponic experiment. Significant genotypic variation in biomass and P content was detected among the cotton genotypes in two seasons. We then conducted a 2-year pot experiment to compare P-efficiency traits between three P-efficient and two P-inefficient genotypes under P-deficient and P-sufficient conditions (0 and 75 mg P2O5 kg–1 soil, respectively). We detected significant differences in biomass accumulation and allocation, P accumulation and allocation, root traits and PAE among the five cotton genotypes under P-sufficient and P-deficient conditions. Compared with P-inefficient genotypes, P-efficient genotypes had longer surface fine roots, and greater total root surface area, total root length, surface root length, and P concentration (partitioning index) in bolls. Root morphology, especially surface fine root length and middle root length, played an important role in P uptake under P-deficient conditions.

The root system plays a crucial role in water and nutrient absorption, making it a significant factor affected by nitrogen (N) availability in the soil. However, the intricate dynamics and distribution patterns of cotton (Gossypium hirsutum L.) root density and N nutrient under varying N supplies in Southern Xinjiang, China, have not been thoroughly understood. A two-year experiment (2021 and 2022) was conducted to determine the effects of five N rates (0, 150, 225, 300, and 450 kg N ha⁻¹) on the root system, shoot growth, N uptake and distribution, and cotton yield. Compared to the N0 treatment (0 kg N ha⁻¹), the application of N fertilizer at a rate of 300 kg N ha⁻¹ resulted in consistent and higher seed cotton yields of 5875 kg ha⁻¹ and 6815 kg ha⁻¹ in 2021 and 2022, respectively. This N fertilization also led to a significant improvement in dry matter weight and N uptake by 32.4% and 53.7%, respectively. Furthermore, applying N fertilizer at a rate of 225 kg N ha⁻¹ significantly increased root length density (RLD), root surface density (RSD), and root volume density (RVD) by 49.6–113.3%, 29.1–95.1%, and 42.2–64.4%, respectively, compared to the treatment without N fertilization (0 kg N ha⁻¹). Notably, the roots in the 0–20 cm soil layers exhibited a stronger response to N fertilization compared to the roots distributed in the 20–40 cm soil layers. The root morphology parameters (RLD, RSD, and RVD) at specific soil depths (0–10 cm in the seedling stage, 10–25 cm in the bud stage, and 20–40 cm in the peak boll stage) were significantly associated with N uptake and seed cotton yield. Optimizing nitrogen fertilizer supply within the range of 225–300 kg N ha⁻¹ can enhance root foraging, thereby promoting the interaction between roots and shoots and ultimately improving cotton production in arid areas.

Limited information is available on accumulation, distribution, and remobilisation of dry matter (DM) and nutrients in cotton (Gossypium hirsutum L.) under the interaction of nutrient management and genotype. We conducted a 2-year field experiment to study the impacts of phosphorus (P) treatments (0, 16.5, 33, 66, 132 and 198 kg P ha–1) on growth and P absorption, allocation and remobilisation in three cotton genotypes. At maturity, the maximum DM and P content allocation to seeds were 20.7% and 62.3%, respectively. Compared with the anthesis stage, leaf DM and P content at maturity significantly decreased by 46.3% and 73.6%, respectively; thus, seed P content was mainly contributed by leaves. Compared with the control (nil P), optimal P fertilisation (33–66 kg P ha–1) increased leaf DM and P content at anthesis by 21.2% and 40.8%, promoted P translocation from leaves to seeds by 43%, and improved lint yield at maturity by 22.8%. At anthesis and maturity, the DM and P content of the entire plant, and lint and seed yields were higher in genotypes XLZ57 and XLZ19 than in XLZ13. Suitable P doses increase DM and P accumulation and yield, and improve source–sink relationships of DM and P in cotton.

The sustainability of Korla fragrant pear orchards has been increasingly threatened by prolonged intensive agricultural practices. In response, biofertilizers and green manures have gained attention due to their potential to enhance soil structure, activate microbial functions, and improve nutrient uptake. However, the dynamic changes in soil bacterial communities under such interventions remain inadequately understood. This study was conducted from 2022 to 2023 in 7- to 8-year-old Korla fragrant pear orchards in Bayin’guoleng Mongol Autonomous Prefecture, Xinjiang. The treatments included: conventional fertilization (CK), biofertilizer (JF), oil sunflowers (DK1) with 25 cm row spacing and a seeding rate of 27 kg·hm⁻², oil sunflowers (DK2) with 25 cm row spacing and a seeding rate of 33 kg·hm⁻², sweet clover (CM1) with 20 cm row spacing and a seeding rate of 21 kg·hm⁻², and sweet clover (CM2) with 20 cm row spacing and a seeding rate of 27 kg·hm⁻². During the 2023 pear season, soil samples from the 0–20 cm layer were collected at the fruit setting, expansion, and maturity stages. Their physical and chemical properties were analyzed, and the structure and diversity of the soil bacterial community were examined using 16S rRNA gene high-throughput sequencing. Fruit yield was assessed at the maturity stage. Compared to CK, the relative abundance of Actinobacteria increased by 101.00%, 38.99%, and 50.38% in the JF, DK2, and CM1 treatments, respectively. DK1 and CM1 treatments resulted in a 152.28% and 145.70% increase in the relative abundance of the taxon Subgroup_7, while JF and DK2 treatments enhanced the relative abundance of the taxon Gitt-GS-136 by 318.91% and 324.04%, respectively. The Chao1 index for CM2 was 18.76% higher than CK. LEfSe analysis showed that the DK2 and CM2 treatments had a more significant regulatory effect on bacterial community structure. All treatments led to higher fruit numbers and yield compared to CK, with JF showing the largest yield increase. Fertilizer type, soil nutrients, and bacterial community structure all significantly positively influenced pear yield. In conclusion, high-density oil sunflower planting is the most effective approach for maintaining soil microbial community stability, followed by low-density sweet clover. This study provides a systematic evaluation of the dynamic effects of bio-fertilizers and different green manure planting patterns on soil microbial communities in Korla fragrant pear orchards, presenting practical, microbe-based strategies for sustainable orchard management.

Xinjiang is situated in an arid and semi-arid region, where abundant heat and sunlight create highly favorable conditions for cotton cultivation. Xinjiang’s cotton output accounts for nearly one-quarter of global production. Moreover, the implementation of advanced planting techniques, such as ‘dwarfing, high-density, early-maturing’ strategies combined with mulched drip irrigation, ensures stable and high yields in this region. Despite these advancements, limited research has focused on the microbial mechanisms in cotton fields employing these advanced planting methods. In this study, high-throughput sequencing technology was utilized to investigate the diversity and composition of bacterial and phoD (Alkaline phosphatases encoding gene) communities in the rhizosphere of cotton grown under different yield levels in Xinjiang Province, China. The Mantel test, redundancy analysis (RDA) and partial least squares path modeling (PLS-PM) were employed to explore the interactions between soil bacterial and phoD communities, their network structures, and environmental factors. The bacterial and phoD communities in the cotton rhizosphere were predominantly composed of nine bacterial phyla (i.e., Proteobacteria, Actinobacteria, Acidobacteria, Gemmatimonadetes, Chloroflexi, Bacteroidetes, Rokubacteria, Firmicutes, and Nitrospirae) and five phoD phyla (i.e., Proteobacteria, Actinobacteria, Planctomycetes, Acidobacteria, and Firmicutes), respectively. Alpha diversity analysis indicated that the medium yield cotton field (MYF) exhibited higher bacterial richness and diversity indices compared to low yield (LYF) and high yield (HYF) fields. The symbiotic network analysis of LYF revealed greater values of average degree, number of edges, and modularity, suggesting a more complex network structure in both bacterial and phoD communities. The Mantel test, RDA, and PLS-PM model identified soil pH, electrical conductivity (EC), organic phosphorus (OP), available phosphorus (AP), total nitrogen (TN), microbial biomass carbon (MBC), and clay content as the main driving factors influencing changes in the rhizosphere bacterial community diversity and network structure. These findings provide a theoretical basis for future research aimed at improving soil quality and cotton yield.

To increase the resilience of our food system, we must better understand how ecosystem services such as pest control and pollination provided by a diverse insect community contribute to crop yield. We examined how landscape heterogeneity relates to insect and pollinator diversity, and how insect and pollinator diversity relates to yield of Brassica carinata, a new biofuel crop within common farming practices. Over two years, we planted 35 × 1 acre sites in a roughly 1000‐km² area near Brookings, South Dakota, in the Prairie Coteau. We randomly assigned each site to a combination of three common farming practices: tilling (yes/no), added honey bee hives (yes/no), and treatment with systemic neonicotinoids (yes/no). Insect and pollinator diversity and the heterogeneity of the surrounding landscape at multiple spatial scales were calculated. We observed a significant positive relationship between insect (and pollinator) diversity and yield when fields were untreated, without hives, nor seed treatments. All farming practices within this study increase yield. However, farming practices alter the relationship between yield and insect (and pollinator) diversity. The addition of seed treatment or tillage negates the relationship between insect (and pollinator) diversity with yield. There was no relationship between seed treatment, diversity, and yield for all insects, and the application of seed treatment resulted in lower pollinator diversity. Increased landscape heterogeneity was correlated with more insect diversity at the 1000‐m scale and pollinator diversity at the 3000‐m scale. Our results show that increasing large‐scale landscape heterogeneity increases insect diversity, which serves as a substitute for common farming practices such as application of pesticides, tilling, or bee hives. Increased landscape heterogeneity could increase farmers' net profitability by replacing input costs associated with tillage and seed treatments.