Spatiotemporal Dynamics of Carbon Footprint of Main Crop Production in China.

As a major agricultural country, the comprehensive accounting of the dynamics and composition of the carbon footprint of major crops in China will provide a decision-making basis for environmental management and agricultural green development in the whole process of the major crop production system in China. To investigate the spatiotemporal dynamics of the carbon footprint for major crops in China, a life cycle-based carbon footprint approach was used to evaluate the carbon footprint per unit area (CFA) and per unit yield (CFY) of eight crops for the period of 1990 to 2019. Our results showed that the CFA for all major crops showed an increasing trend with time before 2016 but slowly decreased afterward, while the CFY decreased by 16-43% over the past 30 years due to the increase in crop yield. The three main grain crops, rice (4871 ± 418 kg CO2-eq · ha-1), wheat (2766 ± 552 kg CO2-eq · ha-1), and maize (2439 ± 530 kg CO2-eq · ha-1), showed the highest carbon footprint and contribution to the total greenhouse gas (GHG) emissions, mainly due to their larger cultivated areas and higher fertilizer application rates. CH4 emission was the major component of the carbon footprint for rice production, accounting for 66% and 48% of the CFA and CFY, respectively, while fertilizer production and usage were the largest components of carbon footprint for dryland crops, making up to 26-49% of the CFA and 26-50% of the CFY for different crops. The present study also highlighted the spatial and temporal patterns of the carbon footprint for major crops in China, which could serve as references for the development of best management practices for different crop production in China, to mitigate agricultural GHG emission and to pursue low-carbon agriculture.

Life Cycle Assessment on Agricultural Production: A Mini Review on Methodology, Application, and Challenges.

Agricultural Life Cycle Assessment (LCA) is an effective tool for the quantitative evaluation and analysis of agricultural materials production and operation activities in various stages of the agricultural system. Based on the concept of life cycle, it comprehensively summarizes the impact of agriculture on the environment, which is an effective tool to promote the sustainability and green development of agriculture. In recent years, agricultural LCA has been widely used in the agroecosystem for resource and environmental impacts analysis. However, some challenges still exist in agricultural LCA, i.e., the environmental impact assessment index system needs to be improved; its application in different production mode is limited; and combination research with other models needs more attention. This paper discusses the above-mentioned challenges and recommends research priorities for both scientific development and improvements in practical implementation. In summary, further research is needed to construct a regional heterogeneity database and develop innovated methodologies to develop more meaningful functional units for agricultural products to complement LCA by other models. These efforts will make agricultural LCA more robust and effective in environmental impacts assessment to support decision making from individual farm to regional or (inter)national for the sustainable future of agriculture.

Clinicopathologic features and prognostic factors in patients with renal cell carcinoma with sarcomatoid differentiation.

Renal cell carcinoma with sarcomatoid differentiation (RCCs) is rare, accounting for 1-8% of all RCC histological subtypes. In this study, we examined 139 patients with RCCs and aimed to explore their clinicopathologic features and prognostic factors. From January 2007 to January 2019, patients who were pathologically diagnosed with RCCs were included in this retrospective study. Data on clinicopathologic features and overall survival were collected. The expression of CK, vimentin, CK7, and CD10 in the sarcomatoid regions of RCCs was detected. The Kaplan-Meier curves and log-rank tests were used to describe the effect of clinicopathologic characteristics on overall survival. A Cox regression model was used to evaluate risk factors for prognosis. A total of 139 patients with RCCs were identified. The median age at diagnosis was 60 years. The median survival time of all patients was 39 months. The three- and five-year survival rates were 50.2% and 44.0%, respectively. A high pathologic T stage (pT3 and pT4), microvascular invasion, and lymph node metastasis were significant predictors of prognosis. Pathologic T4 stage and lymph node metastasis were independent prognostic factors for overall survival in patients with RCCs. Furthermore, the expression of CD10 was a prognostic factor for overall survival. In this study, a relatively large cohort of patients with RCCs was analyzed. We summarized the clinicopathologic features of RCCs and explored the risk factors for prognosis. Our findings may provide valuable prediction for clinical strategy.

Complete chloroplast genome sequence of Acer sutchuenense subsp. tienchuanenge (Sapindaceae).

Acer sutchuenense subsp. tienchuanenge (Sapindaceae: Acer) is an endangered deciduous arbor species and endemic to China. Being obtained by using genome Illumina pair-end sequencing data, the complete chloroplast genome of A. sutchuenense subsp. tienchuanenge had a typical quadripartite structure, with 156,063 bp long, including a large single-copy (LSC) region of 85,772 bp, a small single-copy (SSC) region of 18,117 bp, and a pair of inverted repeats (IRs) (each 26,087 bp in length). A total of 136 genes were annotated, of which 113 are unique genes, including 30 tRNAs, 4 rRNAs, and 79 protein-coding genes. The overall GC content was 37.9%. The phylogenetic analysis suggested that A. sutchuenense subsp. tienchuanenge was the most closely related to A. griseum and A. triflorum. The complete chloroplast genome of A. sutchuenense subsp. tienchuanenge is valuable for assessment and conservation of genetic resources and further for phylogenetic study of Acer L.

Complete chloroplast genome sequence of Acer nikoense (Sapindaceae).

Acer nikoense (Sapindaceae: Acer) is a deciduous tree, belonging to the Ser. Grisea of Sect. Trifoliata. Its complete genome sequence was obtained using genome Illumina pair-end sequencing data. It had a typical quadripartite structure with 155,952 bp in length, consisting of a large single-copy region (85,720 bp) and a small single-copy region (18,072 bp), as well as a pair of inverted repeats (26,080 bp). The total GC content was 37.9%. A total of 113 unique genes were annotated, including 30 tRNAs, 4 rRNAs, and 79 protein-coding genes. The phylogenetic analysis indicated that A. nikoense and A. triflorum were the most closely related.

Revealing genetic diversity of tree peonies at micro-evolution level with hyper-variable chloroplast markers and floral traits.

KEY MESSAGE: Highly variable regions of chloroplast genome were found to be useful in the detection of plant genetic diversity at micro-evolution level. Our methodology will improve understanding and conservation of plant diversity. Tree peonies are famous flowers with about 2,000 cultivars in the world, belonging to Paeonia sect. Moutan of the Paeoniaceae. They are traditionally classified based on flower forms and colors. Due to the limited number of DNA and morphological markers, and the existence of synonyms and homonyms, evaluation on genetic diversity of so many cultivars remains a challenge. In most cases, it is difficult and even impossible to discriminate tree peony cultivars when they are not in flower. In this study, single nucleotide polymorphism detected from the hyper-variable regions of chloroplast genome was employed to separate tree peony cultivars into different maternal lineages which can be expressed briefly by a nucleotide molecular formula. Our approach enabled a much higher resolution of cultivar identification and classification that has not been obtained before. The newly developed hyper-variable chloroplast markers, as an independent source of taxonomic characteristics, provided novel evidences and higher resolution ability that are helpful in building an effective classification system for evaluation, conservation, and utilization of the tree peony germplasm resources at cultivar level.