Ratooning is a cultivation technique that involves harvesting a second crop (referred to as a ratoon) originating from the stubbles of the first crop. Rice ratooning has been implemented in countries located in tropical and temperate regions. Based on recent studies conducted in southwestern Japan, this review introduces and discusses the effects of harvest time and cutting height of the first crop and the roles of leaf blades and nonstructural carbohydrates (NSC) in the stubbles of the first crop on grain yield to provide the essential information necessary for the development of rice production technologies using ratooning.

Labor-saving technology has seen developments as the farmer population ages in Japan, and one of them is the assist suit. The assist suit can be categorized into exoskeleton and supporter types based on whether it is rigid and into active and passive types based on whether it is powered. The evaluation methods of the assist suit can be broadly classified into biomechanical analysis, physiological evaluation, and psychological evaluation. JIS B 8456-1 provides a method for measuring the mechanical assistive force, which is a static force or torque, of the lumbar support type, and we developed a method for measuring the dynamic assistive force, which is a dynamic force or torque, as a method building on top of the JIS method. The assistive forces can be compared with the tolerance of the human joints to estimate the operational safety of the assist suit on a human. Lifting and transporting objects, holding a half-sit posture, and picking fruits are representative tasks expected to utilize the assist suit in agriculture. In Japan, falls are considered the most important hazard because farmers often work on uneven ground with poor footing surrounded by many obstacles.

Bismuth (Bi) is a minor metal used in semiconductors as a lead substitute. We have previously demonstrated that Bi inhibits plant growth and causes cell death. However, the mechanism of growth inhibition by Bi remains unclear. Reactive Oxygen Species (ROS) are involved in the phytotoxicity of heavy metals. The effect of Bi on ROS production in plants is unknown. We examined O₂^.− and H₂O₂ involvement in Bi-treated Arabidopsis thaliana and found that these have decreased production in Bi-treated leaves and roots. SOD is involved in ROS metabolism, and the FeSOD expression level was not affected upon Bi treatment. In Bi-treated root meristems, the cell cycle was arrested. However, the genomic DNA of Bi-treated plants was not digested. Therefore, Bi may inhibit enzymes related to the cell cycle. These findings indicate that Bi phytotoxicity causes ROS disruption and cell cycle arrest.

The automation of agricultural implement changeovers is crucial for minimizing human intervention in the operation of autonomous farming systems. To ensure system safety and resilience, it is imperative to recognize implements as non-obstacle objects, thereby facilitating the seamless hitching of implements with autonomous tractors. This study presents the initial step in developing a safety function for autonomous implement changeover by assessing the performance of YOLO-based detectors, primarily in terms of precision and speed in detecting target implements and humans. These detectors are trained using transfer learning, employing four YOLOv5 variants (YOLOv5s, YOLOv5m, YOLOv5l, and YOLOv5x) and a custom dataset comprising 26,661 labeled images across nine classes of implements and eight classes of obstacles and equipment. The training results show a high average precision (AP) of the detectors, varying from 0.907 to 0.995, for detecting the implements. The mean average precision (mAP@0.5) for detecting all classes ranged from 0.955 to 0.966. Furthermore, testing involving tractor-implement alignments demonstrates the rapid detection of implements and humans by all detectors, with average inference times varying from 7.0 to 20.5 ms. These detectors consistently provide accurate predictions for target objects, with confidence scores (CS) varying from 87.6% to 90.4%. Notably, the detector trained with the medium-variant YOLOv5m is the optimal model with overall performance in terms of both detection speed and accuracy.

This study aims to identify consumer evaluation of green-labeled rice in China using e-commerce review data. It also proposes a random forest model to predict consumer evaluation of green-labeled rice. First, using text mining techniques, we summarized the tf-idf scoring for each of the two products reviewed. Second, we constructed a random forest model to find the important words affecting the rating of green-labeled rice. Finally, we used co-occurrence networks to clarify the relationship among keywords that influence consumer evaluations and whether the influence is positive or negative. We found that consumers placed importance on the packaging, texture, taste, price, quality, and likes of green-labeled rice at the time of purchase and after purchase. Moreover, we found that the words green food, traceability, and quality led to good evaluations of green-labeled rice. Chinese consumers were found to be more likely to purchase products with quality certification labels, but it was also found that green food certification is not necessarily an attribute that consumers value most.

As weaning piglets are easily susceptible to infections and diarrhea, addressing these issues is critical in pig production. Therefore, the use of probiotics has garnered increasing attention. Limosilactobacillus reuteri (L. reuteri) is one of the most studied probiotics that can colonize the gut of a wide range of animals. Studies examining the effects of L. reuteri in pigs have suggested that it can be used as a probiotic to reduce intestinal diseases in piglets and improve productivity. In our study, L. reuteri strain 164 (L164) was isolated from farm pig feces. The isolated L164 was evaluated for antibiotic susceptibility, and we found that L164 had little antibiotic resistance. L164 is also resistant to low pH and bile treatment, similar to Lacticaseibacillus rhamnosus strain GG, a notable probiotic strain. The gene expression analysis of L164-ingested mice indicated that L164 may activate the aryl hydrocarbon receptor, decrease intestinal epithelial stem cells in the ileum, and increase enterochromaffin cells in the colon. Furthermore, experiments using a mouse model of colitis showed that L164 inhibited colon shortening caused by a chemical colitogen and reduced diarrheal symptoms. These results suggest that L164 is a promising probiotic for weaning piglets.

We empirically examined coppice growth characteristics after one- and two-stage thinning in a coppiced teak plantation (2 × 4 m plant spacing) in Nong Bua Lamphu, Thailand, in June 2011. For the one-stage thinning, we thinned all but one sprout per stump (P1), while in the two-stage thinning, we thinned all but two sprouts per stump in the first thinning and a dominant sprout per stump (P2ds) in the second thinning 4 years later. Teak trees were clear-cut at 15 years old in December 2010 at the study site; their growth and stem condition data were available until 8.6 and 4.5 years, respectively. The relative growth rate was estimated by integrating hierarchical Bayesian modeling with a generalized linear mixed model to determine the treatment effects. P2ds caught up with P1 in both diameter at breast height and tree height by year 7 (P > 0.05). At year 4.5, P2ds showed 86% healthy coppices, whereas 74% of P1 were healthy due to wind damage within ~2 years of the first thinning. Self-thinning was implied to occur in year 5 for both treatments. In year 4, the growth diameter decelerated, with asymptotically decreasing relative spacing indices of 23 and 20 on the one- and two-sprout plots, respectively. On growth and stem conditions, two-stage thinning showed higher potential than one-stage thinning for teak reforestation under coppice regeneration.

While the global forest area is decreasing overall, it is experiencing growth in China. This study uses econometric methods to analyze the causal factors behind this increase, focusing particularly on socioeconomic factors. Previous research has given scant attention to stationarity, and few studies have considered regional characteristics such as China’s forest resource distribution and the economic disparity between Inland and Coastal areas. We used panel data collected between 1993 to 2018 from four regions in China. Panel unit root and panel cointegration tests were employed, and panel ARDL models were specified. The results reveal that the long-term relationship between forest area and gross regional product per capita (GRPPC) varies by region. A linear relationship with a positive slope was realized between forest area and GRPPC in the Northeast and Central regions. However, an inverted U-shaped relationship is found between forest area and GRPPC in the East and West regions. Throughout the analysis, the Northeast and Central regions appeared to be in the recovery phase of forest area under a positive relationship with economic growth. In contrast, the East and West regions reached a stable phase with sufficient recovered forests and a constant level of economic development.

In this paper, we describe the utilization of coco peat, commonly used in horticultural production, as a bulking agent for dairy cow manure composting. Coco peat has high water absorption and low moisture content, which are important factors for bulking agents; however, its utility in composting processes has not been clarified. Our objective of this study was to clarify the characteristics of coco peat as a bulking agent in composting material. Stainless fermenters with a volume of 430 L were used as an experimental device. The mixture of cow manure and coco peat was adjusted to 70%, 74%, 78%, and 82% moisture content, and cow manure and rice husks adjusted to 70% moisture content were used as control. As a result, the organic matter decomposition rate and compost temperature were low under the condition of mixing coco peat at the same moisture content as rice husk, and coco peat was not a significantly more effective bulking agent than rice husks. However, composting was possible even at high moisture contents above 75%, where fermentation stagnation can occur in rice husks. The higher moisture content using coco peat led to a higher temperature of the composting material and more organic matter decomposition because of more easily degraded organic matter content originating in manure. Moreover, ammonia emission and the decrease in fertilizer components were less in coco peat than in the control. Therefore, it can be concluded that coco peat can be used as an alternative bulking agent for dairy cow manure composting.