Integrating crop redistribution and improved managements could meet China’s food demand with lower environmental costs

Sustainably feeding the growing population in China attracts attention globally. Despite practices success, producing enough food to simultaneously address resource and pollution problems has been infeasible. To assess how to achieve this goal in 2035, we created a pathway that synergistic combining improved managements and cropland redistribution based on 11.1 million farmer surveys and 4,272 georeferenced field observations. Here, we firstly selected the practices of top 10% performers in crop yield and nitrogen (N) efficiency as crop-specific attainable improved managements at the county level. The optimized crop distribution within improved managements was then performed to minimize inputs (N and phosphorus fertilizer, irrigation water) or environmental impacts (reactive N [Nr] loss and greenhouse gas [GHG] emissions). We identified that combing improved managements and cropland redistribution could produce enough food demands in 2035, with 24% more production compared to 2012. It also reduced the inputs and environmental impacts in a range of 19%-35%, mainly sourced from the central and eastern coastal areas by improved productivity and diminished cropland of fruit and vegetables. These findings highlight the necessity for a synergistic combination of measures to sustainably feed the growing population and establish a more realistic and effective policy.

350 Nutrient Movement in the Environment: Confined versus Grazing Systems

Grazing systems perform multiple ecosystem services including food production, climate regulation, nutrient cycling, and erosion control. Ruminants can also express their natural behaviors on pasture, with recent research revealing that dairy cows were more motivated to go outside for grazing than stay indoors consuming fresh TMR offered immediately after the afternoon milking. In addition, consumers often associate grazing systems with “healthier and happier cows” and are willing to pay premiums for “grass-fed” dairy products. However, milk production and nutrient utilization generally decrease in pasture-based compared with confinement systems, which may reduce farm profitability depending on milk pay prices. It should be noted that there is limited research reporting milk N efficiency (milk N/N intake) or methane emissions in confined versus grazing dairy cows using data collected from the same experiments. Therefore, our overarching objective was to build data sets to compare nutrient utilization in dairy cows under confinement or grazing management where milk N efficiency or methane emissions or both were reported in the same study. Dietary strategies to mitigate methane emissions in grazing dairy systems such as the use of high-quality forages (e.g., brassicas, perennial ryegrass), concentrate and seaweed supplementation, and forage species and management will be explored. For instance, Jersey cows grazing forage canola offered at 40% of the total DM emitted 31% less methane than those kept indoors and fed TMR (419 vs. 289 g/d, respectively) in an experiment conducted at the University of New Hampshire. Methane yield and methane intensity also decreased (P < 0.001) by 29.3% and 23.4%, respectively, in the same study. Irish researchers reported that methane production (-37%), yield (-11.5%), and intensity (-13%) decreased significantly in Holstein-Friesian cows offered perennial ryegrass herbage versus TMR. Data from whole-farm models comparing confinement and grazing systems will be presented and discussed.

Responses of nitrogen efficiency and antioxidant system of summer maize to waterlogging stress under different tillage

Waterlogging was one of the main abiotic stresses affecting maize yield and growth in the North China Plain, while ridge tillage effectually improved soil environment, enhanced crop stress resistance to waterlogging, and increased grain yield of waterlogged maize. In order to explore the responses of nitrogen (N) efficiency and antioxidant system of summer maize to waterlogging stress under different tillage, a field experiment was conducted to explore N use efficiency, leaf activities of superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT), and malondialdehyde (MDA) content of waterlogged maize Denghai 605 (DH605) and Zhengdan 958 (ZD958) under different tillage system (ridge planting and flat planting). Our results showed that ridge tillage was beneficial to ameliorate waterlogging damages on antioxidant system by increasing SOD, POD, and CAT activities, and decreasing MDA content. Moreover, ridge tillage significantly increased N efficiency of waterlogged maize. N translocation amount (NTA), N translocation efficiency (NTE), N contribution proportion (NCP), N harvest index (NHI), and N use efficiency (NUE) of waterlogging treatment under ridge planting system (W-V3+R) for DH605 was increased by 108%, 69%, 60%, 8% and 16%, while ZD958 increased by 248%, 132%, 146%, 13% and 16%, respectively, compared to those of waterlogging treatment under flat planting system (W-V3). Ultimately, ridge tillage led to a significant yield improvement by 39% and 50% for DH605 and ZD958, respectively, compared to that of W-V3. In conclusion, ridge tillage was conducive to retard leaf aging, and enhance nitrogen efficiency, thereby resulting in a yield improvement of waterlogged summer maize.

Event boundary detection using autonomous agents in a sensor network

We propose a novel approach to event boundary detection, where autonomous agents are deployed in order to minimize the number of transmissions required to discover an event boundary. The goal of our algorithm is to reduce the number of non-boundary node transmissions (i.e. nodes within the event area and not within transmission distance to the boundary), since the sensory data from these nodes are not required for event boundary detection. The algorithm works by first randomly generating a fraction of agents within the event nodes, then discovering and mapping the boundary, and finally reporting the aggregated results to the user. Simulations demonstrate that the algorithm exhibits O(n) efficiency relationship with the event area, which is an improvement over existing methods that show O(n²) relationships. Furthermore, we demonstrate that the boundary of an event may be successfully mapped using the proposed algorithm.

Event boundary detection using autonomous agents in a sensor network

We propose a novel approach to event boundary detection, where autonomous agents are deployed in order to minimize the number of transmissions required to discover an event boundary. The goal of our algorithm is to reduce the number of non-boundary node transmissions (i.e. nodes within the event area and not within transmission distance to the boundary), since the sensory data from these nodes are not required for event boundary detection. The algorithm works by first randomly generating a fraction of agents within the event nodes, then discovering and mapping the boundary, and finally reporting the aggregated results to the user. Simulations demonstrate that the algorithm exhibits O(n) efficiency relationship with the event area, which is an improvement over existing methods that show O(n²) relationships. Furthermore, we demonstrate that the boundary of an event may be successfully mapped using the proposed algorithm.

The effects of birth weight and estimated breeding value for protein deposition on nitrogen efficiency in growing pigs

The effects of birth weight (BiW) (low BiW (LBW) vs high BiW (HBW)) and estimated breeding value for protein deposition (EBV) (low EBV (LBV) vs high EBV (HBV)) on N retention, N efficiency and concentrations of metabolites in plasma and urine related to N efficiency in growing pigs were studied. At an age of 14 weeks, 10 LBW-LBV (BiW: 1.07 + 0.09 (SD) kg; EBV: -2.52 + 3.97 g/d, compared to an average crossbred pig with a protein deposition of 165 g/d), 10 LBW-HBV (BiW: 1.02 + 0.13 kg; EBV: 10.47 + 4.26 g/d), 10 HBW-LBV (BiW: 1.80 + 0.13 kg; EBV: -2.15 + 2.28 g/d), and 10 HBW-HBV (BiW: 1.80 + 0.15 kg; EBV: 11.18 + 3.68 g/d), male growing pigs were allotted to the experiment. The pigs were individually housed in metabolism cages and were subjected to a N balance study in two sequential periods of 5 d, after a 11-d dietary adaptation period. Pigs were assigned to a protein adequate (A) or protein restricted (R, 70% of A) regime in a change-over design. Pigs were fed 2.8 times the energy requirements for maintenance. Non-targeted metabolomics analyses were performed in urine and blood plasma samples. The N retention (in g/d) was higher in the HBW than in the LBW pigs (P < 0.001). The N retention (in g/(kg BW 0.75.d)) and N efficiency, however, were not affected by BiW of the pigs. The N retention (P = 0.04) and N efficiency (P = 0.04) were higher in HBV than in LVB pigs on the A regime, but were not affected by EBV in pigs on the R regime. Restricting the dietary protein supply with 30% decreased the N retention (P < 0.001) but increased the N efficiency (P = 0.003). Non-targeted metabolomics showed that a hexose, free amino acids (AA) and lysophosphatidylcholines were the most important metabolites in plasma for the discrimination between HBV and LBV pigs, whereas metabolites of microbial origin contributed to the discrimination between HBV and LBV pigs in urine. This study shows that BiW does not affect N efficiency in later life of pigs. Nitrogen efficiency and N retention were higher in HBV than in LBV pigs on the A regime, but similar in HBV and LBV pigs on the R regime. In precision feeding concepts aiming to further optimize protein and AA efficiency in pigs, the variation in EBV for protein deposition of pigs should be considered as a factor determining N retention, growth performance and N-efficiency.

Integrative Transcriptome and Proteome Analysis Identifies Major Molecular Regulation Pathways Involved in Ramie (Boehmeria nivea (L.) Gaudich) under Nitrogen and Water Co-Limitation

Water and N are the most important factors affecting ramie (Boehmeria nivea (L.) Gaudich) growth. In this study, de novo transcriptome assembly and Tandem Mass Tags (TMT) based quantitative proteome analysis of ramie under nitrogen and water co-limitation conditions were performed, and exposed to treatments, including drought and N-deficit (WdNd), proper water but N-deficit (WNd), proper N but drought (WdN), and proper N and water (CK), respectively. A total of 64,848 unigenes (41.92% of total unigenes) were annotated in at least one database, including NCBI non-redundant protein sequences (Nr), Swiss-Prot, Protein family (Pfam), Gene Ontology (GO) and KEGG Orthology (KO), and 4268 protein groups were identified. Most significant changes in transcript levels happened under water-limited conditions, but most significant changes in protein level happened under water-limited conditions only with proper N. Poor correlation between differentially expressed genes (DEGs) and differentially expressed proteins (DEPs) was observed in ramie responding to the treatments. DEG/DEP regulation patterns related to major metabolic processes responding to water and N deficiency were analyzed, including photosynthesis, ethylene responding, glycolysis, and nitrogen metabolism. Moreover, 41 DEGs and 61 DEPs involved in regulating adaptation of ramie under water and N stresses were provided in the study, including DEGs/DEPs related to UDP—glucuronosyhransferase (UGT), ATP synthase, and carbonate dehydratase. The strong dependency of N-response of ramie on water conditions at the gene and protein levels was highlighted. Advices for simultaneously improving water and N efficiency in ramie were also provided, especially in breeding N efficient varieties with drought resistance. This study provided extensive new information on the transcriptome, proteome, their correlation, and diversification in ramie responding to water and N co-limitation.

Screening and comprehensive evaluation of rice (Oryza sativa L. subsp. japonica Kato) germplasm resources for nitrogen efficiency in Xinjiang, China

Comprehensive screening of rice (Oryza sativa L. subsp. japonica Kato) germplasm resources with different nitrogen (N) efficiency levels is effective for improving N use efficiency (NUE) while reducing pollution and providing high quality, yield, and efficiency agriculture. We investigated 14 indices of 38 varieties under three N application levels to assess differences among genotypes. Rice varieties were classified for screening and identifying N efficient. Descriptive statistical analysis results indicated significant differences in relative yield, and also in NUE indices (agronomic utilization rate and partial productivity of N fertilizer). The genotype main effects and genotype–environment interaction effects (GGE) biplot analysis was used to evaluate suitable varieties, compare the stable and high yield capabilities of different varieties, find the ideal variety, and describe the correlation, discrimination and representativeness of the indices under different N application levels. Descriptive statistical, discrimitiveness and representativeness and factor analysis were used to select indices, in which the panicle number per plant and soil and plant analyzer development (SPAD) value were the key indices for evaluation and identification. Heatmap and hierarchical cluster analysis based on the average value of evaluation indices, and scatter plot based on the comprehensive value of N efficiency (P) according to formula showed that all varieties could be divided into five types under different N treatments. Our findings work toward developing N efficient rice varieties to improve NUE, reduce N fertilizer application and thus N waste, consequently mitigating the effects of rice production on the environment to ensure food security and sustainable agricultural development.

Birth weight affects body protein retention but not nitrogen efficiency in the later life of pigs

Exploring factors that might affect nitrogen (N) efficiency in pigs could support the development of precision feeding concepts. Therefore, an experiment was conducted to determine the effects of birth weight (BiW) on N retention, N efficiency, and concentrations of metabolites in plasma and urine related to N efficiency in male pigs of 14 wk of age. BiW of the low BiW (LBW) and high BiW (HBW) pigs was 1.11 ± 0.14 and 1.79 ± 0.12 kg, respectively. Twenty LBW and 20 HBW pigs were individually housed in metabolism cages and were subjected to an N balance study in two sequential periods of 5 d, after an 11-d adaptation period. Pigs were assigned to a protein adequate (A) or protein restricted (R, 70% of A) regime in a change-over design and fed restrictedly 2.8 times the energy requirements for maintenance. Nontargeted metabolomics analyses were performed in urine and blood plasma samples. The N retention in g/d was higher in the HBW than in the LBW pigs (P < 0.001). The N retention in g/(kg BW0.75·d) and N efficiency (= 100% × N retention / N intake), however, were not affected by BiW of the pigs. Moreover, fecal digestibility of N and urinary concentration of N and urea were not affected by BiW of the pigs. The concentration of insulin (P = 0.08) and insulin-like growth factor-1 (IGF-1;P = 0.05) in blood plasma was higher in HBW pigs, whereas the concentration of α-amino N tended to be lower in HBW pigs (P = 0.06). The LBW and HBW pigs could not be discriminated based on the plasma and urinary metabolites retrieved by nontargeted metabolomics. Restricting dietary protein supply decreased N retention (P < 0.001), N efficiency (P = 0.07), fecal N digestibility (P < 0.001), urinary concentration of N and urea (P < 0.001), and concentration of urea (P < 0.001), IGF-1 (P < 0.001), and α-amino N (P < 0.001) in blood plasma. The plasma and urinary metabolites differing between dietary protein regime were mostly amino acids (AA) or their derivatives, metabolites of the tricarboxylic acid cycle, and glucuronidated compounds, almost all being higher in the pigs fed the A regime. This study shows that BiW affects absolute N retention but does not affect N efficiency in growing pigs. Therefore, in precision feeding concepts, BiW of pigs should be considered as a factor determining protein deposition capacity but less as a trait determining N efficiency.