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In order to clarify yield formation mechanism of mechanical dry direct-sowing rice, the objective of this experiment was to study the effects of different mechanical dry direct-sowing modes on growth and development characteristics and yield of rice. Two different rice cultivars of indica hybrid rice F you 498 (143 days growth duration) and conventional japonica rice Xudao 4 (145 days growth duration) were planted with two mechanical dry direct-sowing modes, including a shallow rotary tillage land and mechanic drilling simultaneously (B1), regulating soil moisture and two rotary tillage before mechanic drilling (B2). Manual broad-cast sowing (B3) was set as control at the same time. We investigated and performed growth analysis during different growth periods, and determined yield formation and physiological characteristics under different direct-sowing treatments. The dry direct-sowing machine in this study was modified by Nanjing Agricultural University and was re-modified by Sichuan Agricultural University. This machine has six drills and sowed depth 2.0 cm, drill spacing 28.0 cm, working area 1.50 m. Motive power of this machine was the Shanghai New Holland tractor (SNH504). This test adopted row spacing 20 m × 1.5 m, each plot covered 30 m2 of seeding amount was 30.0 kg/hm2 of indica hybrid rice F you 498, 37.5 kg/hm2 of conventional japonica rice Xudao 4 respectively. The nitrogen fertilizer amount was 180 kg/hm2, and the amount of potash and phosphate were 90 and 180 kg/hm2, respectively. The N application ratios was applied on 4 splits: 50% basal, 30% tillering fertilizer at the third leaf stage, 10% panicle N-fertilizer at the 4th leaves emerged from the top, 10% ear granular fertilizer at the full heading stage. The phosphate fertilizer was applied as base fertilizer. The potash fertilizer application ratio of basic fertilizer, tillering fertilizer and ear granular fertilizer was 2:1:1. The other management measures were at a uniform with high-yield cultivation. The results showed that the variety difference and direct-sowing modes significantly affected dry matter accumulation and leaf area index (LAI) at the mainly growth periods, net photosynthetic rate (Pn) and protective enzyme activities of flag leaves, root bleeding intensity, culm lodging resistance during the grain filling stage and the grain yield. Under different direct-sowing modes, the various indicators on yield and growth characteristics of F you 498 were significantly higher than those of Xudao 4. Compared with B3 treatment, rice under mechanical direct-seeding modes could optimize the number of rice tillering, improve the percentage of earbearing tiller, maintain an appropriate LAI and increase efficient leaf area ratio at the full-heading stage. Besides mechanical direct-seeding could improve photosynthetic capacity at the grain filling stage and therefore increase the accumulation of photosynthetic products. In addition, Pn and protective enzyme activities in flag leaves, root bleeding intensity, culm lodging resistance during the grain filling stage under mechanical direct-seeding modes were superior, and rice could gain higher seed-setting rate and 1000-grain weight with a number of effective panicles. These outstanding traits should be the important reason for mechanical direct-sowing rice further to increase yield. Under different mechanical direct-sowing modes, compared with B3, B2 treatment was the best model in this study referred as the mechanical direct-sowing treatments, which could further promote the dry matter accumulation, alleviate LAI decay, increase root vigor and the ability of culm lodging resistance during grain filling stage, consequently, promoting the seed-setting rate and 1000-grain weight as well as the grain yield. [ABSTRACT FROM AUTHOR]

• This work provides a new model framework for predicting grain yield. • Combining spectral data and RGB images to develop the fusion models of grain yield. • Multi-source remotely sensed data can improve the estimation accuracy of rice LCC. • Multi-source remotely sensed data has the potential for grain yield prediction. Predicting rice grain yield using multi-source remotely sensed data is crucial for improving prediction accuracy, optimizing nitrogen management, and advancing precision agricultural development. However, the feasibility and reliability of using multi-source remotely sensed data to predict the grain yield remain unclear. Therefore, this study aimed to explore the possibility of providing rice leaf chlorophyll content (LCC) estimations and predictions of the grain yield using multi-source remotely sensed data. Two rice field experiments were conducted with various rice cultivars and nitrogen rates, and a field spectrometer and an unmanned aerial vehicle (UAV) equipped with a digital camera were employed to acquire the spectral reflectance and red–green–blue (RGB) images at the tillering, jointing, and full-heading stages. Destructive sampling was then conducted to measure the LCC and grain yield. The LCC was used as a bridge to develop remotely sensed prediction models for the grain yield. First, the linear relationship between grain yield and the LCC was determined at the tillering, jointing, and full-heading stages. A multiple linear regression (MLR) model was then developed to predict grain yield using multi-temporal LCCs at three growth stages. Second, multiple stepwise regression, support vector regression, and back propagation neural network were used to evaluate the estimation performance of spectral reflectance, RGB image data, and their combination for LCC. Third, the most accurate LCC estimation model was selected and coupled with the linear and MLR models of grain yield. The results showed that grain yield was significantly and positively related to the LCC at the tillering, jointing, and full-heading stages, and that the MLR model of grain yield achieved the best estimation accuracy using multi-temporal LCCs. The fusion models established by combining spectral reflectance and RGB image data improved LCC estimation accuracies. Using multi-growth stages, the most accurate predictions of grain yield were obtained from LCC estimation models (R 2 = 0.698, RMSE = 0.742 t ha−1, rRMSE = 9.004 %) compared to those using single growth stages. Our study concluded that multi-source remotely sensed data fused from ground-based spectral reference and UAV-based RGB images can better predict and explain the grain yield for both single and multi-growth stages. This study provides a novel method of estimating the crop chlorophyll content and grain yield. [ABSTRACT FROM AUTHOR]

Triangle planting geometry (TPG) is a new rice arrangement mode, whereby plants form a “dense intra-hill, sparse inter-hill” group structure. This allows them to have more spatial options, thus avoiding excessive infra-hill competition when compared to conventional row configurations. However, there is limited information on how TPG might affect rice production, especially for newly-bred varieties featuring a heavy panicle size (5 g panicle −1 ). This study was conducted to evaluate grain yield performance and yield component changes of heavy panicle varieties under TPG. Moreover, to identify any promising agronomy traits and population structural features that might explain the difference in yield performance as well as to probe whether the high-yielding performance of TPG is reproducible in other circumstances. In 2012, Eryou498 (a heavy panicle variety) was grown under four planting geometries (PGs) in two fields that had similar soil fertility, but that were conducted with either conventional tillage or zero-tillage systems. In 2013, two heavy panicle varieties and two medium panicle varieties (2–5 g panicle −1 ) were grown under three PGs in two ecological regions. Grain yield and effective panicles were significantly affected by both variety and PG. A significant interaction of PG and variety was seen on grain yield, but the high-yielding performance of TPG was consistent with all varieties. Sufficient total spikelets were the basis of achieving a high grain yield. Effective panicles predominantly attributed to total spikelets across all four experiments. Robust spikelets were crucial when grain yield was at a high level. Heavy panicle varieties and TPG showed some similar high-yielding traits. These included rapid crop growth rate (CGR) during the two weeks before full heading, plenty non-structural carbohydrate (NSC) accumulated at full heading, mass NSC output in two weeks after full heading, and high radiation use efficiency (RUE). Rice under TPG presented a more compact top three leaves as well as more stretched lower leaves when compared to other PGs. Overall, all leaves of heavy panicle varieties were more stretched than those found in medium ones. Heavy panicle varieties accumulated more nitrogen (N) in leaves from elongation to 30 days after full heading while PG showed no significant effect on leaf N concentration during the late grain-filling period. These results suggest that the high-yielding performance of TPG is reproducible in other circumstances. The combination of TPG and heavy panicle varieties is advantageous, allowing for a more efficient canopy structure for heavy panicle varieties and a more robust photosynthetic ability at late grain-filling period under TPG. [ABSTRACT FROM AUTHOR]

• Methodical nitrogen–water distribution management (MNWD) couples nitrogen and water application in rice production. • MNWD stabilized rice yield and reduced nitrogen and water input in rice production simultaneously. • Larger amount of root in soil layers deeper than 10 cm of MNWD was the key for higher water and nitrogen use efficiencies. Methodical nitrogen–water (N–W) distribution management (MNWD) is a comprehensive N–W management technique designed to meet the requirements of rice production in China and specifically, the stabilization of grain yield and reduction of input resources. In this study, four split plot field experiments were conducted in two locations to examine the impact of MNWD on N use efficiency (NUE) and water use efficiency (WUE). We used high N efficiency rice varieties, Dexiang 4103 and Fyou 498, and low N efficiency varieties, Yixiang 3724 and Chuanyou 6203, and three N–W management techniques were established as subplot treatments, including farmers' usual management (FU), N–W coupling management (NWC), and MNWD. Under MNWD, N application rates were 20% lower than those under NWC and FU, whereas the amounts of irrigation water were reduced by 20%–25% and 42%–48%, respectively. Yields under MNWD were similar to those under NWC (–2.51–0.45%), and there was an average yield increase of 8.13%–13.95% over FU. Rice plants under MNWD had larger amounts of roots, particularly in soil depth > 10 cm There were significant positive correlations between root dry mass in the various soil depths and WUE and irrigation WUE (IWUE), with the impact of roots in soil depth > 10 cm on rice plant WUE (IWUE) pronounced. MNWD's IWUE was higher than that of NWC and FU by 22.95%–38.79% and 86.49%–126.69%, respectively, and its WUE was higher by 6.75%–20.74% and 37.05%–71.80%, respectively. Correlation analysis showed that the N absorption and accumulation capacities of rice plants under MNWD increased along with increases in soil fertility. The MNWD's NUE advantage was apparent in soil depth > 10 cm where its root dry mass was especially large, with an average biomass productivity of N higher than that of NWC and FU by 4.16%–10.78% and 7.49%–18.01%, respectively and an N internal efficiency higher by 0.33%–8.29% and 5.32%–10.04%, respectively. Overall, MNWD effectively improved WUE and NUE of rice without significant grain yield reduction. [ABSTRACT FROM AUTHOR]