Long-Term Dynamic of Cold Stress during Heading and Flowering Stage and Its Effects on Rice Growth in China

Short episodes of low-temperature stress during reproductive stages can cause significant crop yield losses, but our understanding of the dynamics of extreme cold events and their impact on rice growth and yield in the past and present climate remains limited. In this study, by analyzing historical climate, phenology and yield component data, the spatial and temporal variability of cold stress during the rice heading and flowering stages and its impact on rice growth and yield in China was characterized. The results showed that cold stress was unevenly distributed throughout the study region, with the most severe events observed in the Yunnan Plateau with altitudes higher than 1800 m. With the increasing temperature, a significant decreasing trend in cold stress was observed across most of the three ecoregions after the 1970s. However, the phenological-shift effects with the prolonged growing period during the heading and flowering stages have slowed down the cold stress decreasing trend and led to an underestimation of the magnitude of cold stress events. Meanwhile, cold stress during heading and flowering will still be a potential threat to rice production. The cold stress-induced yield loss is related to both the intensification of extreme cold stress and the contribution of related components to yield in the three regions.

Rice (Oryza sativa L.) Growth Modeling Based on Growth Degree Day (GDD) and Artificial Intelligence Algorithms

Rice (Oryza sativa L.) growth prediction is key for precise rice production. However, the traditional linear rice growth forecasting model is ineffective under rapidly changing climate conditions. Here we show that growth rate (Gr) can be well-predicted by artificial intelligence (AI)-based artificial neural networks (ANN) and gene-expression programming (GEP), with accumulated air temperatures based on growth degree day (GDD). In total, 10,246 Gr from 95 cultivations were obtained with three cultivars, TK9, TNG71, and KH147, in Central and Southern Taiwan. The model performance was evaluated by the Pearson correlation coefficient (r), root mean square error (RMSE), and relative RMSE (r-RMSE) in the whole growth period (lifecycle), as well as the average and specific key stages (transplanting, 50% initial tillering, panicle initiation, 50% heading, and physiological maturity). The results in lifecycle Gr modeling showed that ANN and GEP models had comparable r (0.9893), but the GEP model had the lowest RMSE (3.83 days) and r-RMSE (7.24%). In stage average and specific key stages, each model has its own best-fit growth period. Overall, GEP model is recommended for rice growth prediction considering the model performance, applicability, and routine farming work. This study may lead to smart rice production due to the enhanced capacity to predict rice growth in the field.

Seaweed extract effect on arbuscular mycorrhizae spore in soil engineered by earthworm, and the soil effect on upland rice growth

Seaweed extract is known to contain nutrients and growth-regulating substances that affect soil biota, and a source of protection against pests and diseases. Earthworm, which is an example of a soil biota and playing the role of ecosystem engineer, has the ability to produce suitable land biostructures, for the inhabitation of arbuscular mycorrhizal fungi (AMF), which has an impact on upland rice growth. Therefore, this study aims to determine, (i) the effect of seaweed extract on the population of earthworms and spores of arbuscular mycorrhizal fungi, and (ii) the impact of the engineered soil on the growth of local upland rice varieties. Furthermore, the extract of seaweed, such as Kappapychus alvarezii, was divided into five concentration levels, namely 0%, 20%, 40%, 60%, and 80%. Each treatment was drenched into the soil from the cogongrass vegetated area, mixed with 20 Pheretima sp., and maintained for 49 days in the greenhouse. The result showed that the total difference in the earthworms’ concentration treatments was not significant. It also showed that the total AMF spores in the engineered soil products of 20% concentration was the highest. Based on treatment with the earthworm engineered soil products, the highest and lowest vegetative growth and yield components of upland rice were observed at the concentrations of 80% and 0%, respectively. In conclusion, the application of seaweed extract to the soil did not significantly reduce the earthworm population. The extract concentration of 20% also increased the total AMF spore in the engineered soil. Moreover, highly treated engineered soil products increased the growth and yield components of upland Kambowa rice on cogongrass soils.

Rice growth phase analysis in Pidie regency, Indonesia using multitemporal Sentinel-2 image data: a spectral angle mapper approach

Remote sensing data provides fast and relatively accurate information to retrieve the plant growth phase using spectral analysis. Spectral analysis of plants is the critical point of identifying the stages of rice growth using Sentinel-2 data. Sentinel-2 satellite images were utilized for this study. This study aims to analyze the growth phase of rice in Pidie regency, Aceh Province, Indonesia, as a sample area of the rice-growing site. The Spectral Angle Mapper (SAM) approach was performed to describe the plant growth stages. The results show variations in the rice growth phase across the study area for 2019, 2020, and 2021 growing seasons from vegetative, generative, wet fallow, and dry fallow. The most extensive vegetative phase is for April 2021 data, counting for 1,278.16 Ha. The most extensive generative phase was identified of June 2020 data, counting for 1,107.55 Ha. For wet fallow, counting for 949,30 Ha is the largest in this category. A total of 1,311.94 Ha of dry fallow is identified in 2019. The different growth phases and the total area for different years indicate variation in starting for the growing season of the sample location. In this paper, multitemporal Sentinel-2 data analyzed with the SAM approach has demonstrated identifying rice-growing season phases. This finding can help predict the total area along the year for a change of the pattern of the rice-growing season in the last three years of the study area.

Effects of the Autumn Incorporation of Rice Straw and Application of Lime Nitrogen on Methane and Nitrous Oxide Emissions and Rice Growth of a High-Yielding Paddy Field in a Cool-Temperate Region in Japan

The effects of autumn plowing and lime nitrogen application on rice straw decomposition, CH4 and N2O emission and rice growth in the following year in a high-yielding rice cultivated paddy field were evaluated for two years. The experimental plots were set up, combining different times of rice straw (750 g m−2) incorporation into the soil by plowing (autumn or the following spring), with and without lime nitrogen application in autumn (5 g-N m−2). Autumn plowing promoted the decomposition of rice straw, but the application of lime nitrogen did not show a consistent trend. The soil pH was high (7.3) at the studied site, and the alkaline effect of lime nitrogen may not have been significant. As with straw decomposition, CH4 emissions were suppressed by autumn plowing, and no effect from the lime nitrogen application was observed. It was also suggested that the straw decomposition period may be shorter and the CH4 emissions may be higher in high-yielding cultivars that require a longer ripening period than in normal cultivars. The effect of both treatments on N2O emission was not clear. Both the autumn plowing of rice straw and lime nitrogen application were effective in promoting rice growth and increasing rice yield.

Multiple Leveling for Paddy Field Preparation with Double Axis Rotary Tillage Accelerates Rice Growth and Economic Benefits

In the multiple cropping regions of southern China, straw returning has become a widely practiced agronomic measure for rice cultivation. However, excessive straw often leads to a high proportion of stubble in topsoil, which prolongs the leveling time of the paddy field and delays the transplanting date for rice seedlings. In particular, scholars in this region have successively improved multiple paddy field levelers to realize excellent straw returning and subsequent land preparation synchronously, but the economic benefit from land preparation to crop harvest was less reported. Therefore, this study carried out a 2-year rice cultivation experiments to compare the effects of paddy field preparation methods on rice growth and economic benefits within the same growing duration. Three treatments were designed: traditional tillage (TT), double axis rotary tillage (DR) and multiple operations for paddy field preparation (DR + ML), with three repeats. The results showed that DR + ML treatment simplified the operation process while improving the quality of land preparation. Within the same growing duration, DR + ML treatment could reduce the paddy field preparation time and extend the growing time in the field by 5–6 days. Furthermore, in comparison to TT treatment, DR + ML showed advantages in stimulating plant development, increasing dry matter accumulation (DMA), and thereby increasing rice yield by more than 12%. The economic benefits were mainly reflected in saving operation cost of paddy field preparation and improving the output (grain yield), which can generally increase the total profit by 58%. The implementation of this study can provide a reference for a simplified high yield cultivation technique in rice-related multiple cropping systems.