Explore the vast range of titles available.

Sensitivity analysis is useful to downgrade/upgrade the number of inputs to limit greenhouse emissions and enhance crop yield. The primary data from the 300 rice (grain crop) and 300 cotton (cash crop) farmers were gathered in face-to-face interviews by applying a multistage random sampling technique using a well-structured pretested questionnaire. Energy use efficiency was estimated with data envelopment analysis (DEA) model, and a second-stage regression analysis was conducted by applying Cobb–Douglas production function to evaluate the influencing factors affecting. The results exhibit that chemical fertilizers, diesel fuel and water for irrigation are the major energy inputs that are accounted to be 15,721.55, 10,787.50 and 6411.08 MJ ha −1 for rice production, while for cotton diesel fuel, chemical fertilizer and water for irrigation were calculated to be 13,860.94, 12,691.10 and 4456.34 MJ ha −1 , respectively. Total GHGs emissions were found to be 920.69 and 954.71 kg CO 2eq ha −1 from rice and cotton productions, respectively. Energy use efficiency (1.33 and 1.53), specific energy (11.03 and 7.69 MJ ha −1 ), energy productivity (0.09 and 0.13 kg MJ −1 ) and energy gained (14,497.85 and 20,047.56 MJ ha −1 ) for rice and cotton crop, respectively. Moreover, the results obtained through the second-stage regression analysis revealed that excessive application of fertilizer had a negative impact on the yield of rice and cotton, while farm machinery, diesel fuel and biocides had a positive effect. We hope that these findings could help in the management of the energy budget that we believe will reduce the high emissions of GHGs to address the growing environmental hazards.

Perennial grain crops hold the promise of stabilizing fragile lands, while contributing grain and grazing in mixed farming systems. Recently, perennial rice was reported to successfully survive, regrow, and yield across a diverse range of environments in Southern China and Laos, with perennial rice PR23 being identified as a prime candidate for release to farmers. This paper reports the evaluation of PR23 for release, by (1) comparing its survival, regrowth, performance, and adaptation with preferred annual rices across nine ecological regions in southern Yunnan Province of China; (2) examining the economic costs and benefits of perennial versus annual rice there; and (3) discussing the evidence for the release of PR23 as a broadly adapted and acceptable cultivar for farmers. Overall, the grain yield of PR23 was similar to those of the preferred annual rice cultivars RD23 and HXR7, but the economic analysis indicated substantial labour savings for farmers by growing the perennial instead of the annual. PR23 was comparable to the annuals in phenology, plant height, grain yield, and grain size, and was acceptable in grain and cooking quality. Farmers were keen to grow it because of reduced costs and especially savings in labour. PR23 is proposed for release to farmers because of its comparable grain yields to annual rices, its acceptable grain and milling quality, its cost and labour savings, and the likely benefits to soil stability and ecological sustainability, along with more flexible farming systems.

PurposeLow carbon footprint agriculture has received increasing attention in the effect of reducing greenhouse gas emissions and mitigating climate change. However, little is known about how crop diversification may affect the system productivity and the carbon footprint.MethodsIn this study, we analyzed the carbon footprints of four cropping systems: winter wheat (Triticum aestivum L.)–summer maize (Zea mays L.) (WM, grain crop pattern, 1-year cycle); ryegrass (Lolium perenne L.)–sweet sorghum (Sorghum bicolor (L.) Moench) (RS, forage crop pattern, 1-year cycle); ryegrass–sweet sorghum → winter wheat–summer maize (RSWM, grain plus forage crop pattern, 2-year cycle); and switchgrass (Panicum virgatum L.) perennial cropping (SG, energy crop pattern) that have been evaluated in a long-term (2009–2015) field experiment in the North China Plain (NCP). Carbon footprints were expressed using three metrics: CFa (per unit area), CFb (per kg of biomass), and CFe (per unit of economic output).Results and discussionThe results showed that switchgrass as a perennial herbaceous crop with one cut per year had the lowest annual carbon footprint at three metrics. The WM cropping system had the highest annual CFa, CFb, and CFe values which were 1.73, 2.23, and 1.78 times higher, respectively, than those of the RSWM cropping system. The RS cropping system had the lower annual CFa, CFb, and CFe values, which accounted for 20.9, 3.4, and 2.9%, respectively, of the WM cropping system. The four cropping systems had annual carbon footprints at per unit area, per kilogram of biomass and per unit of economic output ranked from lowest to highest of SG < RS < RSWM < WM.ConclusionsWe conclude that appropriately designed, diversified cropping systems that include grain, forage, and bioenergy crops can effectively reduce the carbon footprint while maintaining or even increasing the systems productivity in the North China Plain.

The application of legume green manure (LGM) is a traditional and valuable practice for agroecosystem management. In the present study, we conducted a meta-analysis to explore the effect of LGM on the yields of three major grain crops in China under different cropping systems and environmental conditions based on 315 field trial datasets. LGM application increased the yield of the three major grain crops significantly by 12.60% compared to those under no LGM application, with wheat, maize, and rice yields increasing significantly by 9.49%, 16.70%, and 19.22%, respectively. In addition, yield increases were significant under crop rotation with grain crops but not under intercropping. The amount of LGM returned to the field (dry weight) at only 2000–3000 kg/ha and 3000–4000 kg/ha increased yield significantly by 12.32% and 11.94%, respectively. The greatest yield increases were observed when annual precipitation was higher than 600 mm, while annual average temperature was higher than 10 °C, and when soil organic matter content was 0–10 g/kg, with 19.64%, 14.11%, and 32.63% increases, respectively. All regions in China, excluding North China, had significant yield increases, with the largest yield increase, 27.12%, observed in Northeast China. The results of the meta-analysis demonstrated that LGM increases yield of all the three major grain crops in China. Additionally, the benefits were also observed under appropriate planting system, green manure biomass, and environmental factors.

The ground beetles Zabrus tenebrioides and Harpalus rufipes (Coleoptera, Carabidae) are two of the most prevalent pests of wheat and other grasses. This article presents current data on their distribution and the results of modelling the bioclimatic ranges of these species using the maximum entropy method. To improve the model, we used various RStudio packages including the R script “thin points 4-1-18.R” package spThin and the «Raster» RStudio package. We determined the climatic parameters that promote the dispersal of the species, as well as the optimum conditions for the growth of Z. tenebrioides and H. rufipes. Maps forecasting the distribution of the studied species were generated through the perspective of two climate scenarios: RCP 2.6 and RCP 8.5. For the modelling, we utilised 435 geographic points of Z. tenebrioides occurrence and 653 points of H. rufipes occurrence. Both species have similar bioclimatic ranges, and the most favourable conditions for them are fields of grain crops. The most significant parameters influencing Z. tenebrioides are those of moisture, whereas H. rufipes is most sensitive to the temperature parameters. According to the generated climatic models for both species, a decrease in the areas of their ranges would occur in their eastern, more continental areas, with a slight shift towards the north.

Lepista sordida is a type of high-quality rare edible and medicinal mushroom, and its research boom is just beginning. More than 80 million tons of grain crop residues are produced each year in Heilongjiang Province. To realize the exploration and utilization of wild L. sordida mushrooms and also provide a theoretical support for the high-value utilization of these resources in Heilongjiang Province, we evaluated the cultivation of L. sordida mushrooms using rice straw, corncob, and soybean straw as substrates. L. sordida grew on all three substrates, and the biological efficiency and yield of the mushrooms grown on soybean straw and corncob were 32.33 ± 1.78% and 4.20 ± 0.23 kg m−2, and 30.15 ± 0.93% and 3.92 ± 0.12 kg m−2, respectively, which increased by 9.38% and 2.08% compared with that on the rice straw substrate with 3.84 ± 0.12 kg m−2 and 29.56 ± 0.89%. The time it took for the mycelia to colonize and initiate primordia on the soybean straw substrate was 22.33 ± 0.58 d and 19.67 ± 0.58 d, respectively, which was delayed by 2 d and 3 d compared with that on the rice straw substrate with 20.67 ± 2.08 d and 16.33 ± 0.58 d, respectively. The fruiting bodies grown on corncob and soybean straw substrates were relatively larger than those on the rice straw substrate. The highest amount of crude protein was 57.38 ± 0.08 g 100 g−1, and the lowest amount of crude polysaccharide was 6.03 ± 0.01 g 100 g−1. They were observed on mushrooms collected from the corncob substrate. The contents of the heavy metal mercury, lead, arsenic, and cadmium in the fruiting bodies grown on each substrate were within the national safety range.

Sunflower is one of the most important oilseed crops in the world, since its grains have high oil content (38% to 50%), primarily used for the production of high quality oil. The production of sunflower increases the supply of protein meal for animal feeding, which enables the increase of protein production, more specifically meat, eggs and milk. Grain production systems in Brazil have peculiarities, since two to three different crops are grown in a special arrangement, in the same area and year. Notwithstanding the small cultivated area in Brazil of 62.3 thousand hectares, sunflower is used in succession or rotation with other grain crops such as soybean or maize, showing an enormous potential for expansion and can be cultivated from latitudes 33°S to 5°N, especially in the Brazilian Cerrado biome. Sunflower cultivation in succession to soybean as a second summer crop can also reduce environmental impacts because of the more efficient usage of production factors, such as land and sharing of agricultural inputs, machinery, infrastructure and workforce. The success of establishing the sunflower is associated with the adequate management of soil fertility, use of cultivars adapted to different environments, plant arrangement, seed quality and adequate phytosanitary management, among other factors. It also needs strategic actions, planning and, long-term research and technology diffusion. Le tournesol est l’une des cultures oléagineuses les plus importantes au monde, car ses graines présentent une teneur en huile élevée (38 % à 50 %) principalement utilisée pour la production d’huile de haute qualité. La production de tournesol fournit également des farines riches en protéines pour l’alimentation animale, ce qui permet d’augmenter la production de protéines, et notamment celle de viande, d’œufs et de lait. Les systèmes de production au Brésil présentent des particularités, puisque seules deux à trois cultures différentes sont cultivées dans une même région et pour une même année. Malgré une petite superficie cultivée de 62 300 hectares, le tournesol au Brésil est utilisé en succession ou en rotation avec le soja ou le maïs, et présente un fort potentiel d’expansion car sa culture est possible pour des latitudes allant de 33 ° S à 5 ° N, en particulier dans le Cerrado. La culture du tournesol en alternance avec le soja comme seconde culture d’été permet également de réduire les impacts environnementaux en raison de l’utilisation plus efficace des facteurs de production comme la terre et le partage des intrants agricoles, des machines, des infrastructures et de la main-d’œuvre. Le succès de l’implantation du tournesol est associé à une gestion adéquate de la fertilité du sol, à l’utilisation de cultivars adaptés à différents environnements, à une bonne structure de peuplement, à la qualité des semences et à une gestion phytosanitaire adaptée, entre autres facteurs. La culture a également besoin d’actions stratégiques, d’une recherche planifiée sur le long terme, et de diffusion de la technologie.

Perennial grain crops are expected to sequester soil carbon (C) and improve soil health due to their large and extensive root systems. To examine the rate of initial soil C accumulation in a perennial grain crop, we compared soil under perennial intermediate wheatgrass (IWG) with that under annual winter wheat 4 years after the crops were first planted. In addition, we tested the effect of three nitrogen (N) sources on C pools: Low available N (Low N (Organic N); 90 kg N ha−1 poultry litter), moderately available N (Mid N; 90 kg N ha−1 urea) and high available N (High N; 135 kg N ha−1 urea). We measured aboveground C (grain + straw), and coarse and fine root C to a depth of 1 m. Particulate organic matter (POM-C), fractionated by size, was used to indicate labile and more stabilized soil C pools. At harvest, IWG had 1.9 times more straw C and up to 15 times more root C compared with wheat. There were no differences in the size of the large (6 mm–250 µm) or medium (250–53 µm) POM-C fractions between wheat and IWG (P > 0.05) in surface horizons (0–10 cm). Large POM-C under IWG ranged from 3.6 ± 0.3 to 4.0 ± 0.7 g C kg soil−1 across the three N rates, similar to wheat under which large POM-C ranged from 3.6 ± 1.4 to 4.7 ± 0.7 g C kg soil−1. Averaged across N level, medium POM-C was 11.1 ± 0.8 and 11.3 ± 0.7 g C kg soil−1 for IWG and wheat, respectively. Despite IWG's greater above and belowground biomass (to 70 cm), POM-C fractions in IWG and wheat were similar. Post-hoc power analysis revealed that in order to detect differences in the labile C pool at 0–10 cm with an acceptable power (~80%) a 15% difference would be required between wheat and IWG. This demonstrates that on sandy soils with low cation exchange capacity, perennial IWG will need to be in place for longer than 4 years in order to detect an accumulated soil C difference > 15%.

The agricultural sustainable development for human well-being considers food security and ecological health as well as people’s socio-economic conditions. Nowadays, most of the holistic assessments of agricultural sustainability, mainly focus on food production and ecological consequences, relatively lacking analysis from the socio-economic perspective. In this context, this study constructs an agricultural social life cycle assessment model based on the guidelines of UNEP to assess the social and economic impacts on the three major staple grain crops in China, including maize, rice and wheat. The assessment model aims to analyze effects of stakeholders containing farmer, agricultural value chain actors, consumer, rural areas, society, and impact categories including high-quality growth of agriculture, a comfortable life in rural areas, the prosperity of rural people. The data is mainly from national statistical databases and representative industry databases. The impact assessment adopts social risk and social impact as quantitative characterization methods, and Analytical Hierarchical Process to obtain weights. The results show that: among the three major grain crops, farmers are the most important factors for stakeholders, and agricultural industrial development has the greatest potential negative impacts on society; maize has the most positive impacts on agricultural sustainable development in China.

Arable land protection is essential for Zero hunger the Sustainable Development Goals of United Nations, and the arable land protection includes two aspects, non-farming and non-grain. We try to monitor the arable land protection in Zhejiang with domestic satellite imagery. Satellite remote technology has become an essential way to monitor the land cover change (for non-farming) and grain crops (for non-grain). However, current monitoring frequency and scale were unable to satisfy the needs for non-farming monitoring. The low-resolution image cannot satisfy the feature of land fragmentation of Zhejiang for non-grain monitoring. To address the above problem, this paper proposes a land cover change method to monitor non-farming purposes based on deeplabv3+ with monthly coverage 2 meters resolution images. By focusing on rebuilding training data set and improving training strategy with hard example training, the difficulty of the spurious change caused by the adjustment of farming structure is solved. At the same time, this paper builds three training processes (Initial training, Fine training, Retraining for promotion) based on Fully Convolutional Neural Network FCN-8S to monitor the main grain crops in Zhejiang. The phenological features are added into the process of training to further improve the accuracy. At present, land cover change method of this paper has been applied in Zhejiang province and the monitoring of grain crops has been carried out in some regions according to the specific requirements. The result shows that both the two methods exhibit good accuracy and generalization ability at the time and space scale.