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AimsThis study evaluated the impact of wheat straw return and microbial agent application on rice field environments.MethodsUsing Rice variety Chuankangyou 2115 and a microbial mix of Bacillus subtilis and Trichoderma harzianum. Five treatments were tested: T1 (no straw return), T2 (straw return), T3, T4, and T5 (straw return with varying ratios of Bacillus subtilis and Trichoderma harzianum).ResultsResults indicated significant improvements in rice root length, surface area, dry weight, soil nutrients, and enzyme activity across T2-T5 compared to T1, enhancing yield by 3.81-26.63%. T3 (50:50 microbial ratio) was optimal, further increasing root dry weight, soil enzyme activity, effective panicle and spikelet numbers, and yield. Dominant bacteria in T3 included MBNT15, Defluviicoccus, Rokubacteriales, and Latescibacterota. Higher Trichoderma harzianum proportions (75% in T5) increased straw decomposition but slightly inhibited root growth. Correlation analysis revealed a significant positive relationship between yield and soil microorganisms like Gemmatimonadota and Firmicutes at the heading stage. Factors like dry root weight, straw decomposition rate post-jointing stage, and elevated soil enzyme activity and nutrient content from tiller to jointing stage contributed to increased panicle and spikelet numbers, boosting yield.ConclusionThe optimal Bacillus subtilis and Trichoderma harzianum ratio for straw return was 50:50, effectively improving soil health and synergizing high rice yield with efficient straw utilization.

IntroductionThe use of controlled-release nitrogen (N) fertilizers has been shown to improve yield and N-use efficiency (NUE) in mechanical transplanted rice. However, the fertilizer requirements for mechanical direct-seeding rice differ from those for mechanical transplanted rice. The effects of controlled-release fertilizers on yield, NUE, and quality in mechanical direct-seeding rice are still unknown.MethodsHybrid indica rice varieties Yixiangyou 2115 and Fyou 498 were used as test materials, and slow-mixed N fertilizer (120 kg hm-2) as a base (N1), N1+urea-N (30 kg hm-2) once as a base (N2), N1+urea-N (30 kg hm-2) topdressing at the tillering stage (N3), N1+urea-N (30 kg hm-2) topdressing at the booting stage (N4) four N fertilizer management to study their impact on the yield, NUE and quality of mechanical direct-seeding rice.Results and discussionCompared with Yixiangyou 2115, Fyou 498 significantly increased photosynthetic potential, population growth rate, root vigor, and N transport rate by 3.34–23.88%. This increase further resulted in a significant improvement in the yield and NUE of urea-N topdressing by 1.73–5.95 kg kg-1. However, Fyou 498 showed a significant decrease in the head rice rate and taste value by 3.34–7.67%. All varieties were treated with N4 that significantly increase photosynthetic potential and population growth rate by 15.41–62.72%, reduce the decay rate of root vigor by 5.01–21.39%, promote the N transport amount in stem-sheaths (leaves) by 13.54–59.96%, and then significantly increase the yields by 4.45–20.98% and NUE of urea-N topdressing by 5.20–45.56 kg kg-1. Moreover, the rice processing and taste values were optimized using this model. Correlation analysis revealed to achieve synergistic enhancement of high-yield, high-quality, and high-NUE in rice, it is crucial to focus on increasing photosynthetic potential, population growth rate, and promoting leaf N transport. Specifically, increasing the contribution rate of N transport in stem-sheaths is the most important. These findings offer an effective N management strategy for 4R nutrient stewardship (right source, right method, right rate and right timing) of mechanical direct-seeding hybrid indica rice.

Rice production is the agricultural activity with the highest energy consumption and carbon emission intensity. Water and fertilizer management constitutes an important part of energy input for rice production and a key factor affecting greenhouse gas emissions from paddy fields. Water–fertilizer integration management (AIM) is an automated water and fertilizer management system for large-scale rice production, which can effectively save water and fertilizer resources. At present, the energy utilization and environmental impact of AIM in rice production are not clear. To clarify whether AIM is a water and fertilizer management measure that combines energy conservation and carbon emission reduction, a comparative study between the widely used farmers’ enhanced water and fertilizer management (FEM) in China and AIM was conducted in this paper. Field experiments were conducted to evaluate the rice yield, carbon emission, energy utilization, and economic benefits of the two management methods. The results showed that AIM reduced water and fertilizer inputs, energy inputs, and economic costs by 12.18–28.57%, compared to FEM. The energy utilization efficiency, energy profitability, and energy productivity under AIM were improved by 11.30–12.61%. CH4 and N2O emissions and carbon footprint were reduced by 20.79%, 6.51%, and 16.39%, respectively. Compared with FEM, AIM can effectively improve the utilization efficiency of water and fertilizer resources and reduce carbon emissions. This study presents a mechanized water and fertilizer management approach suitable for large-scale rice production systems in China. By analyzing rice yield, resource utilization efficiency, and environmental benefits, AIM can serve as a crucial management strategy for enhancing productivity, economic returns, and environmental conservation within profitable rice production systems. In the future, further investigation into the impact of AIM on the microbial mechanisms underlying rice yield formation and greenhouse gas emissions is warranted.

The important reason for the commercial value of hybrid rice suffering is due to excessive chalkiness, and the biosynthesis of starch and proteins is critical for regulating chalkiness; however, it is currently unclear how the application of N fertilizer affects grains to reduce their chalkiness and improve their quality. The 2019, 2020, and 2021 trials were conducted in a split-plot design, with high and low chalky varieties as the main plot and N fertilizer rate as the split-plot. The effects of fertilization with 75, 150, and 225 kg N ha−1 on the dynamic synthesis of starch, protein, and endogenous hormones and on the amino acid of hybrid indica rice kernels with different degrees of chalkiness were investigated. Grain physiological activity was higher in low-chalky varieties than in high-chalky varieties, and these physiological parameters were strongly associated with chalkiness formation. Higher N fertilization (150 and 225 kg N ha−1) significantly reduced the proportion of chalky grains (8.93–28.02%) and chalkiness (8.61–33.99%) compared with 75 kg N ha−1. Increased N fertilization decreased the activities of granule-bound starch synthase and starch-debranching enzyme, but significantly increased adenosine diphosphate glucose pyrophosphorylase, soluble starch synthase, and starch-branching enzyme activities, synergistically improving glutamate synthetase and glutamine synthetase enzyme activities, which tended to support the synthesis of amylopectin, α-ketoglutarate, and 3-phosphoglyceric acid-derived amino acids in the endosperm cells of the grains; this favored starch and protein accumulation in the grains at 6–30 days after anthesis. Additionally, N application promoted the synthesis of endogenous hormones 1-aminocyclopropane-1-carboxylic acid, gibberellins, and abscisic acid in grains. Hence, N fertilization reduced the rice chalkiness in hybrid indica rice varieties by balancing grain protein and starch composition and enhancing some endogenous hormone synthesis.

IntroductionNitrogen (N) fertilizer management, especially postponing N topdressing can affect rice eating quality by regulating starch quality of superior and inferior grains, but the details are unclear. This study aimed to evaluate the effects of N topdressing on starch structure and properties of superior and inferior grains in hybrid indica rice with different tastes and to clarify the relationship between starch structure, properties, and taste quality.MethodsTwo hybrid indica rice varieties, namely the low-taste Fyou 498 and high-taste Shuangyou 573, were used as experimental materials. Based on 150 kg·N hm-2, three N fertilizer treatments were established: zero N (N0), local farmer practice (basal fertilizer: tillering fertilizer: panicle fertilizer=7:3:0) (N1), postponing N topdressing (basal fertilizer: tillering fertilizer: panicle fertilizer=3:1:6) (N2).ResultsThe starch granules of superior grains were more complete, and the decrease in small granules content and the stability of starch crystals were a certain extent less than those of inferior grains. Compared with N1, under N2, low-taste and high-taste varieties large starch granules content were significantly reduced by 6.89%, 0.74% in superior grains and 4.26%, 2.71% in inferior grains, the (B2 + B3) chains was significantly reduced by 1.61%, 0.98% in superior grains, and 1.18%, 0.97% in inferior grains, both reduced the relative crystallinity and 1045/1022 cm-1, thereby decreasing the stability of the starch crystalline region and the orderliness of starch granules. N2 treatment reduced the ΔHgel of two varieties. These changes ultimately contributed to the enhancement of the taste values in superior and inferior grains in both varieties, especially the inferior grains. Correlation analysis showed that the average starch volume diameter (D[4,3]) and relative crystallinity were significantly positively correlated with the taste value of superior and inferior sgrains, suggesting their potential use as an evaluation index for the simultaneous enhancement of the taste value of rice with superior and inferior grains.DiscussionBased on 150 kg·N hm-2, postponing N topdressing (basal fertilizer: tillering fertilizer: panicle fertilizer=3:1:6) promotes the enhancement of the overall taste value and provides theoretical information for the production of rice with high quality

IntroductionControlled-release fertilizers effectively improve crop yield and nitrogen use efficiency (NUE). However, their use increases the cost of crop production. Optimal management modes involving urea replacement with controlled-release N fertilizers to increase rice yield through enhanced NUE are not widely explored.MethodsField experiments were conducted from 2017 to 2018 to determine the effects of different controlled-release N fertilizers combined with urea [urea-N (180 kg ha-1, N1)]. We used controlled-release N (150 kg ha-1, N2) as the base, and four controlled-release N and urea-N ratio treatments [(80%:0% (N3), 60%:20% (N4), 40%:40% (N5), or 20%:60% (N6) as the base with 20% urea-N as topdressing at the panicle initiation stage under 150 kg ha-1] to study their impact on the grain yield and NUE of machine-transplanted rice.Results and discussionGrain yield and NUE were positively correlated with increases in photosynthetic production, flag leaf net photosynthetic rate (Pn), root activity, N transport, and grain-filling characteristics. The photosynthetic potential and population growth rate from the jointing to the full-heading stage, highly effective leaf area index (LAI) rate and Pn at the full-heading stage, root activity at 15 d after the full-heading stage, and N transport in the leaves from the full-heading to mature stage were significantly increased by the N4 treatment, thereby increasing both grain yield and NUE. Furthermore, compared with the other N treatments, the N4 treatment promoted the mean filling rate of inferior grains, which is closely related to increased filled grains per spikelet and filled grains rate. These effects ultimately improved the grain yield (5.03-25.75%), N agronomic efficiency (NAE, 3.96-17.58%), and N partial factor productivity (NPP, 3.98-27.13%) under the N4 treatment. Thus, the N4 treatment with controlled-release N (60%) and urea-N (20%) as a base and urea-N (20%) as topdressing at the panicle-initiation stage proved effective in improving the grain yield and NUE of machine-transplanted hybrid indica rice. These findings offer a theoretical and practical basis for enhancing rice grain yield, NUE, and saving the cost of fertilizer.

Chalkiness, which is highly affected by nitrogen (N) management during grain filling, is critical in determining rice appearance quality and consumer acceptability. We investigated the effects of N application rates 75 (N1), 150 (N2), and 225 (N3) kg ha−1 on the source-sink carbohydrate accumulation and grain filling characteristics of two indica hybrid rice cultivars with different chalkiness levels in 2019 and 2020. We further explored the relationship between grain filling and formation of chalkiness in superior and inferior grains. In this study, carbohydrates in the functional leaves and grains of the two varieties, and grain filling parameters, could explain 66.2%, 68.0%, 88.7%, and 91.6% of the total variation of total chalky grain rate and whole chalkiness degree, respectively. They were primarily concentrated in the inferior grains. As the N fertilizer application rate increased, the chalky grain rate and chalkiness degree of both the superior and inferior grains decreased significantly. This interfered with the increase in total chalky grain rate and chalkiness. Moreover, the carbohydrate content in the functional leaves increased significantly in N2 and N3 compared with that in N1. The transfer of soluble sugar from the leaves to the grains decreased the soluble sugar and increased total starch contents, accelerated the development of grain length and width, increased grain water content, and effectively alleviated the contradiction between source and sink. These changes promoted the carbohydrate partition in superior and inferior grains, improved their average filling rate in the middle and later stages, optimized the uniformity of inferior grain fillings, and finally led to the overall reduction in rice chalkiness.

Estimating the aboveground biomass (AGB) of rice using remotely sensed data is critical for reflecting growth status, predicting grain yield, and indicating carbon stocks in agroecosystems. A combination of multisource remotely sensed data has great potential for providing complementary datasets, improving estimation accuracy, and strengthening precision agricultural insights. Here, we explored the potential to estimate rice AGB by using a combination of spectral vegetation indices and wavelet features (spectral parameters) derived from canopy spectral reflectance and texture features and texture indices (texture parameters) derived from unmanned aerial vehicle (UAV) RGB imagery. This study aimed to evaluate the performance of the combined spectral and texture parameters and improve rice AGB estimation. Correlation analysis was performed to select the potential variables to establish the linear and quadratic regression models. Multivariate analysis (multiple stepwise regression, MSR; partial least square, PLS) and machine learning (random forest, RF) were used to evaluate the estimation performance of spectral parameters, texture parameters, and their combination for rice AGB. The results showed that spectral parameters had better linear and quadratic relationships with AGB than texture parameters. For the multivariate analysis and machine learning algorithm, the MSR, PLS, and RF regression models fitted with spectral parameters (R2 values of 0.793, 0.795, and 0.808 for MSR, PLS, and RF, respectively) were more accurate than those fitted with texture parameters (R2 values of 0.540, 0.555, and 0.485 for MSR, PLS, and RF, respectively). The MSR, PLS, and RF regression models fitted with a combination of spectral and texture parameters (R2 values of 0.809, 0.810, and 0.805, respectively) slightly improved the estimation accuracy of AGB over the use of spectral parameters or texture parameters alone. Additionally, the bior1.3 of wavelet features at 947 nm and scale 2 was used to predict the grain yield and had good accuracy for the quadratic regression model. Therefore, the combined use of canopy spectral reflectance and texture information has great potential for improving the estimation accuracy of rice AGB, which is helpful for rice productivity prediction. Combining multisource remotely sensed data from the ground and UAV technology provides new solutions and ideas for rice biomass acquisition.

Limitations of soil water and nitrogen (N) are factors which cause a substantial reduction in cotton (Gossypium hirsutum L.) yield, especially in an arid environment. Suitable management decisions like irrigation method and nitrogen fertilization are the key yield improvement technologies in cotton production systems. Therefore, we hypothesized that optimal water-N supply can increase cotton plant biomass accumulation by maintaining leaf photosynthetic capacity and improving root growth. An outdoor polyvinyl chloride (PVC) tube study was conducted to investigate the effects of two water-N application depths, i.e., 20 cm (H20) or 40 cm (H40) from soil surface and four water-N combinations [deficit irrigation (W55) and no N (N0) (W55N0), W55 and moderate N (N1) (W55N1), moderate irrigation (W75) and N0 (W75N0), W75N1] on the roots growth, leaf photosynthetic traits and dry mass accumulation of cotton crops. H20W55N1 combination increased total dry mass production by 29–82% and reproductive organs biomass by 47–101% compared with other counterparts. Root protective enzyme and nitrate reductase (NR) activity, potential quantum yield of photosystem (PS) II (Fv/Fm), PSII quantum yield in the light [Y(II)] and electron transport rate of PSII were significantly higher in H20W55N1 prior to 82 days after emergence. Root NR activity and protective enzyme were significantly correlated with chlorophyll, Fv/Fm, Y(II) and stomatal conductance. Hence, shallow irrigation (20 cm) with moderate irrigation and N-fertilization application could increase cotton root NR activity and protective enzyme leading to enhance light capture and photochemical energy conversion of PSII before the full flowering stage. This enhanced photoassimilate to reproductive organs.

The changing climatic conditions are causing erratic rains and frequent episodes of moisture stress; these impose a great challenge to cotton productivity by negatively affecting plant physiological, biochemical and molecular processes. This situation requires an efficient management of water-nutrient to achieve optimal crop production. Wise use of water-nutrient in cotton production and improved water use-efficiency may help to produce more crop per drop. We hypothesized that the application of nitrogen into deep soil layers can improve water-nitrogen productivity by promoting root growth and functional attributes of cotton crop. To test this hypothesis, a two-year pot experiment under field conditions was conducted to explore the effects of two irrigation levels (i.e., pre-sowing irrigation (W80) and no pre-sowing irrigation (W0)) combined with different fertilization methods (i.e., surface application (F10) and deep application (F30)) on soil water content, soil available nitrogen, roots morpho-physiological attributes, dry mass and water-nitrogen productivity of cotton. W80 treatment increased root length by 3.1%−17.5% in the 0−40 cm soil layer compared with W0. W80 had 11.3%−52.9% higher root nitrate reductase activity in the 10−30 cm soil layer and 18.8%−67.9% in the 60−80 cm soil layer compared with W0. The W80F10 resulted in 4.3%−44.1% greater root nitrate reductase activity compared with other treatments in the 0−30 cm soil layer at 54−84 days after emergence. Water-nitrogen productivity was positively associated with dry mass, water consumption, root length and root nitrate reductase activity. Our data highlighted that pre-sowing irrigation coupled with basal surface fertilization is a promising option in terms of improved cotton root growth. Functioning in the surface soil profile led to a higher reproductive organ biomass production and water-nitrogen productivity.