Local Agricultural Development Research Articles

Chemical Composition and Geographic Variation of Cold Pressed Balanites aegyptiaca Kernel Oil.

With the increasing impacts of climate change, establishing more sustainable and robust plants such as desert dates (Balanites aegyptiaca) seems to be necessary. Known for its resilience in arid conditions, this tree has the potential to become a more important food source, particularly for its potential to yield edible oil. This study characterized Balanites kernel oil (BKO) as a promising oil source in arid regions, studying the influence of geographical origin and environmental factors. Moroccan and Sudanese BKO samples were analyzed and compared with Mauritanian BKO. In the fatty acid profile, unsaturated fatty acids constituted over 70% of the BKO profile, with a predominance of linoleic acid (Li), oleic acid (Ol), palmitic acid (Pa), and stearic acid (St). Consequently, the predominant triacylglycerols were PaLiLi, PaLiOl, LiLiOl, OlLiOl, and StLiOl. α-Tocopherol dominated the tocochromanol composition (324 to 607 mg/kg), followed by γ-tocopherol (120 to 226 mg/kg), constituting 90% of the total tocochromanols. The total phytosterol content in BKO ranged from 871 to 2218 mg/kg oil, with β-sitosterol dominating (58% to 74%). Principal Component Analysis revealed that the geographical origin significantly influences BKO composition, emphasizing environmental factors, particularly water deficit and/or temperatures. Notably, Moroccan BKO collected from an area characterized by high aridity and relatively low winter temperatures, showcased a unique profile in fatty acid, phytosterols, and tocochromanols. The valorization of BKO presents an opportunity for local agricultural development in arid regions and a role model for plant development and agricultural practices in other parts of the world.

Foliar application of selenium promotes starch content accumulation and quality enhancement in foxtail millet grains

ContextThe northern regions of China are the core production areas for foxtail millet. However, the lack of selenium in the soil constrains local agricultural development. Foliar application of selenium is a significant method to improve selenium levels, yet few studies have systematically analyzed the effects of selenium on the quality of millet, especially its starch content. ObjectiveThis study aims to assess the effects of selenium foliar spray on the starch composition and overall content within millet grains, specifically by elucidating the mechanisms through examining changes in chlorophyll content in the flag leaves during the grain-filling stage and the activity of enzymes related to starch synthesis in the grains. Additionally, this research seeks to determine the optimal rate of selenium application that would maximize the quantity and quality of starch in millet grains. MethodsA two-year field experiment on foxtail millet was conducted with five selenium treatments (Se rates of 0, 20, 40, 60, and 100 g Se/ha, defined as T0, T1, T2, T3, T4 in this study, respectively). Grain starch content, activities of starch synthesis-related enzymes, flag leaves chlorophyll content, and antioxidant status of the flag leaves were measured at seven time points during grain filling. ResultsThe starch content in foxtail millet grains increased quadratically with the application of selenium, reaching a maximum under the T3 treatment, which enhanced the content by 15.27 % and 11.97 % over two years, respectively. The addition of selenium at low concentrations (T1-T3 treatments) not only enhanced the activities of the three starch synthesis-related enzymes, AGPase, SuSy, and SSS, but also delayed the senescence of the flag leaves, thereby promoting grain starch synthesis. In contrast, excessive selenium application (T4 treatment) expedited the aging of the flag leaves, grain starch synthesis was inhibited compared to the T3 treatment. Moreover, foliar application of selenium led to an increase in the SSS activity in the grains, which in turn reduced the content of straight-chain starch. Under the T3 treatment, the grain straight-chain starch content decreased by 22.30 % and 28.35 % over two years, respectively. ConclusionsFoliar application of selenium enhanced the activities of enzymes related to grain starch synthesis and had a dual effect on the senescence process of flag leaves, regulating the content and composition of starch in foxtail millet grains. The spraying concentration of 60 g Se/ha was most favorable for the accumulation and quality improvement of grain starch. ImplicationsThe results of this study will aid in enhancing the value-added potential of foxtail millet starch products through precise fertilization, improving the yield and quality of foxtail millet in northern China.

Sika deer trajectory prediction considering environmental factors by timeseries transformer-based architecture

Recently, the damage to agriculture, forestry, and fishery by wildlife has become a serious social problem. The damage caused by a conflict between wildlife and human society often causes less motivation for farming and is expected to significantly inhibit the development of local agriculture and forestry. However, the current management of wildlife is limited to primitive methods such as stabilizing the population by culling reliant on experience. To prevent this problem, the trajectory prediction of wildlife is one of the solutions for efficient wildlife management.In this study, we propose a machine learning architecture for predicting wildlife trajectories, considering surrounding environmental factors. Particularly, we propose a machine learning architecture that more accurately predicts trajectories using a timeseries transformer model that can learn long-term dependencies and add a submodel that can consider surrounding environmental factors. The proposed architecture allows interpreting which past trajectory areas should be focused on when predicting a trajectory by visualizing the weight of the focus mechanism, one of the elements comprising the transformer model. Further, the proposed architecture can decide the priority of elements of a multivariate timeseries input by considering a variable selection network (VSN), which considers the relationship of timeseries between a given time point and those before and after using casual convolutions. The main advantage of our methods is to understand the potential environmental factors to predict animal trajectories by analyzing the importance of each input feature representation in VSN.We experimented to evaluate the proposed method using one of the largest biologging datasets of sika deer (Cervus nippon) in Kanagawa Prefecture, Japan. The proposed method outperforms existing methods on various evaluation metrics and can effectively consider environmental factors in predicting trajectories. In addition, we analyze the results and show that the proposed architecture can pay attention to the times that individuals moved significantly within the observation period by visualizing the trajectories for the best and worst cases and the weight of each environmental factor.

South-South cooperation and food security: Evidence from Chinese agricultural technology demonstration Center in Africa

Using the Chinese Agriculture Technology Demonstration Center (ATDC) in Africa as a quasi-natural experiment, we examine the causal impacts of China’s aid on crop production in Africa. The data pertain to African country-by-crop panel data from 2000 to 2018. Leveraging the triple difference-in-differences method, we find that the ATDC leads to increased crop production and improved trade dependence. The positive effects are more pronounced for free-standing technical support and ATDCs operated by state-owned enterprises. Lastly, the ATDC has profound implications for local agriculture and rural development.

Trends and driving forces of agricultural carbon emissions: A case study of Anhui, China.

To facilitate accurate prediction and empirical research on regional agricultural carbon emissions, this paper uses the LLE-PSO-XGBoost carbon emission model, which combines the Local Linear Embedding (LLE), Particle Swarm Algorithm (PSO) and Extreme Gradient Boosting Algorithm (XGBoost), to forecast regional agricultural carbon emissions in Anhui Province under different scenarios. The results show that the regional agricultural carbon emissions in Anhui Province generally show an upward and then downward trend during 2000-2021, and the regional agricultural carbon emissions in Anhui Province in 2030 are expected to fluctuate between 11,342,100 tones and 14,445,700 tones under five different set scenarios. The projections of regional agricultural carbon emissions can play an important role in supporting the development of local regional agriculture, helping to guide the input and policy guidance of local rural low-carbon agriculture and promoting the development of rural areas towards a resource-saving and environment-friendly society.

Study on Modeling and Evaluating Alfalfa Yield and Optimal Water Use Efficiency in the Agro-Pastoral Ecotone of Northern China.

The agro-pastoral ecotone in northern China is the main production area of agriculture and animal husbandry, in which agricultural development relies entirely on groundwater. Due to the increasing water consumption of groundwater year by year, groundwater resources are becoming increasingly scarce. The substantial water demand and low germination rate in the first year are the main characteristics of alfalfa (Medicago sativa L.) yield in the agro-pastoral ecotone in northern China. Due to unscientific irrigation, water resources are seriously wasted, which restricts the development of local agriculture and animal husbandry. The study constructed the Dssat-Forages-Alfalfa model and used soil water content, leaf area index, and yield data collected with in situ observation experiments in 2022 and 2023 to calibrate and validate the parameters. The study found ARE < 10%, ENRMS < 15%, and R2 ≥ 0.85. The model simulation accuracy was acceptable. The study revealed that the water consumption at the surface soil layer (0-20 cm) was more than 6~12% and 13~31% than that at the 20-40 cm and 40-60 cm soil layers, respectively. The study showed when the irrigation quota was 30 mm, the annual yield of alfalfa (Medicago sativa L.) (7435 kg/ha) was consistent with that of the irrigation quota of 33 mm, and increased by 3.99% to 5.34% and 6.86% to 10.67% compared with that of irrigation quotas of 27 mm and 24 mm, respectively. To ensure the germination rate of alfalfa (Medicago sativa L.), it is recommended to control the initial soil water content at 0.8 θfc~1.0 θfc, with an irrigation quota of 30 mm, which was the best scheme for water-use efficiency and economic yield. The study aimed to provide technological support for the rational utilization of groundwater and the scientific improvement of alfalfa yield in the agro-pastoral ecotone in northern China.

The Modern Agriculture Development of Arid and Semi-Arid Areas in China

It was very important to study the agricultural development of arid and semi-arid areas in China for national food security. This area accounts for about 1/3 of China's land area. However, due to long-term water scarcity, strong sandstorms, and severe soil salinization, local agricultural development was limited.Nowadays, with the continuous development of agricultural technology in arid and semi-arid areas, the agricultural development in arid and semi-arid areas of our country had undergone earth-shaking changes. In this paper, from the initial unification of plastic film cover in arid and semi-arid areas to the normalization of greenhouses and solar greenhouses, and with the development of electrification technology and the gradual maturity of information technology, agricultural development has gradually moved from traditional to the era of modernization, information and intelligence, the above four aspects to discuss the agricultural development process in arid and semi-arid areas of our country.

Optimization of network flows for rural extension of fruit and vegetable agricultural technologies

Abstract This paper focuses on the rural promotion of fruit and vegetable agricultural technology and proposes a network flow optimization model based on linear programming for the diffusion of fruit and vegetable agricultural technology. Based on the Bass model, it describes the process of natural growth of network users and the word-of-mouth effect among them. Fruit and vegetable agricultural technology diffusion in real social networks is fitted and predicted by the social network information dissemination model, and the network flow problem of fruit and vegetable agricultural technology promotion is optimized using linear programming equations. Based on this basis, the algorithm designed in this paper and the effect of rural promotion of fruit and vegetable agricultural technology are analyzed with relevant data. The results show that the coefficient of the variable of the number of promotion times in the behavior of agrotechnology promotion is 0.064, which has a significant positive effect on the evaluation of the rural promotion performance of fruit and vegetable agricultural technology, indicating that increasing the number of agricultural technology training and enriching the content of agricultural technology promotion will help to improve the evaluation of the rural promotion performance of fruit and vegetable agricultural technology by farmers. The network flow optimization model constructed in this paper can enable farmers to master more modern fruit and vegetable agricultural technology to meet the needs of modern production of fruit and vegetable agriculture so as to improve the level of local fruit and vegetable agricultural development.

Climate Smart Agriculture: The Role of Fertilizer Innovations and Efficient Plant Nutrient Management

Climate change has emerged as a significant threat to the global agro-economy, adversely affecting agricultural productivity, food security, and local and global agricultural development goals. To ensure sustainable crop productivity and meet future demands, it is essential to take prompt actions to address the current challenges of lower agricultural productivity due to climate change. Climate-smart agriculture (CSA) is a novel concept that offers a promising approach to tackle these challenges by introducing sustainable farming practices that minimize negative environmental impacts and enhance resilience to climate change. It involves realigning current agricultural practices and introducing smart techniques to reduce the adverse effects of agriculture that contribute to climate change and higher carbon footprints. The importance of climate-smart fertilizers in agricultural productivity cannot be overemphasized, as the soil is susceptible to structural changes and alterations in nutrient availability due to climatic impacts. Therefore, the implementation of proper nutrient management mechanisms and advanced fertilizer innovations has become a top priority in implementing the concepts of CSA. Consequently, there has been a greater focus on introducing more climate-adaptive and resilient plant nutrient delivery systems and technologies in recent times. For instance, nanofertilizer, bio-based controlled-release and slow-release fertilizers have provided a more sustainable and climate-friendly alternative to traditional synthetic fertilizers. Despite the innovations, challenges remain in implementing CSA practices and practices of climate-smart fertilizers at scale. This is largely attributed to the lack of proper knowledge and a streamlined policy framework on climate resilience in agriculture and fertilizers. This article seeks to review the role of fertilizer innovations and nutrient management in CSA, targeting the reduction of nutrient losses due to climate changes. It also examines the current status of climate-smart fertilizers with a particular emphasis on the current implementation challenges and future prospects in fertilizer production, leading to global food security by adapting to climatic changes. By highlighting specific examples of modern climate-smart agriculture and fertilizer management, this article aims to provide insights into the potential benefits and challenges of implementing CSA practices and encourage further research and development in this important field.&#x0D; Keywords: Climate-smart agriculture, Climate-smart fertilizers, Climate change, Nutrient Management, Innovations in fertilizers

Effective Solutions to Ecological and Water Environment Problems in the Sanjiang Plain: Utilization of Farmland Drainage Resources

The Sanjiang Plain stands as a pivotal grain-producing region in China. Faced with population growth and the imperative of ensuring food security, the rapid expansion of agricultural land in the Sanjiang Plain has led to escalating ecological and water-environmental challenges, hindering the sustainable development of regional agriculture. This research aims to explore and propose practical measures for utilizing agricultural drainage resources to address the ecological and water-environmental issues resulting from agricultural expansion in the Sanjiang Plain, striving to achieve harmonious and sustainable economic and environmental growth. The discussion revolves around the potential alleviation of water quality, water quantity, and ecological health issues in the Sanjiang Plain through the proposed approach. Considering regional characteristics, the focus is on potential environmental drawbacks resulting from the improper application of the method. Building on these findings, effective strategies are presented to enhance the systematic operation of agricultural drainage resource utilization in the region. In conclusion, addressing ecological and water-environmental challenges stemming from local agricultural development is imperative for the Sanjiang Plain to realize sustainable development for the economy and the environment.

Transforming food systems: a gendered perspective on local agricultural innovation in Cuba.

Compared to many countries, Cuba has made significant progress in advancing women's rights and gender equity; however, disparities remain. In the country's rural communities and agricultural sector, women continue to face barriers to equal participation and recognition for the value of their work. This case study shares the story of gender equity efforts that have been conducted within the framework of a broader development project-the Project to Strengthen a System of Innovation in Local Agricultural Development (PIAL, for its initials in Spanish). PIAL began in 2001 as a participatory plant-breeding initiative aimed at increasing the genetic diversity of key crops such as maize and beans. Over the course of two decades, the project's goals expanded to include an emphasis on increasing women's participation. In the beginning, those efforts focused on including women in the participatory plant-breeding activities, which enabled them to prioritize traits they cared about such as grain texture, cooking speed, and taste in the selection process. Over time, the participatory nature of the PIAL methodology empowered women to identify and pursue capacity-building in other areas of local agricultural innovation. While PPB remained central to PIAL, women also chose to pursue opportunities in seed bank management, leadership training, and small-scale farm-based entrepreneurship. The results of the PIAL work on gender have included not just more inclusive plant breeding, but also important economic improvements for rural women as they have been able to diversify their livelihoods, and social change as they have gained confidence and recognition as leaders in their households, communities, and beyond.

Comparative Analysis of Agricultural Competitiveness of Prefecture-level Cities in Shandong Provinc

Agricultural competitiveness is an important indicator for measuring the level of local agricultural development, and high-quality agricultural development is the future development trend of agriculture. This paper analyzes the changes and factors of agricultural competitiveness in Shandong Province, and makes a comprehensive evaluation, and puts forward measures and suggestions to promote the development of high-quality agriculture in Shandong Province. In this paper, relevant agricultural data of 16 prefecture-level cities in Shandong Province are selected, and factor analysis is used to assess the level of agricultural competitiveness of prefecture-level cities in Shandong Province. The results show that the overall distribution of agricultural competitiveness in Shandong Province is uneven, with large gaps and low values. The geographical distribution shows the trend of "high in the middle and low around", and the input-output and economic factors, planting output, fruit and vegetable output, fishery output all affect the competitiveness of Shandong's agriculture. Therefore, the future development direction of Shandong Province's agriculture should be based on the actual development situation, and the competitiveness of agriculture in each prefecture-level city should be improved according to local conditions.

The impact of digital economy on green development of agriculture and its spatial spillover effect

PurposeBy discussing the spatial spillover effect and regional heterogeneity of digital economy and green agricultural development level, this paper aims to provide countermeasures and suggestions for the better development of green agriculture in the contemporary era when digital economy is universally developed and at the same time provide development suggestions suitable for green agriculture's development characteristics and initial conditions for different regions.Design/methodology/approachThis paper discusses the theoretical foundation of the digital economy and green agriculture development and utilizes panel data from 30 provinces in China from 2011 to 2018. By employing the Super-Efficiency Slack-based Measure and Malmquist-Luenberger (SBM-ML) model based on unexpected output to measure the total factor productivity of green agriculture and employing the spatial panel Durbin model to empirically test the spatiotemporal effects of the digital economy on green agriculture development from both temporal and spatial dimensions. Finally, the model is tested for robustness as well as heterogeneity.FindingsThe research findings are as follows: First, from the perspective of time effect, digital economy has a continuous driving effect on the development of green agriculture and with the passage of time, this effect becomes more and more prominent; second, from the perspective of spatial effect, digital economy has a significant positive impact on the development of local green agriculture, while digital economy has a significant negative impact on the development of surrounding green agriculture. Finally, the impact of digital economy on the development of green agriculture shows significant differences in different dimensions and regions.Originality/valueAs an important driver of economic growth, the digital economy has injected new impetus into agricultural and rural development. Along with the intensifying environmental pollution problems, how to influence the green development of agriculture through the digital economy is a proposition worthy of attention nowadays. This paper analyzes the relationship between the digital economy and agricultural green development in multiple dimensions by exploring the temporal and spatial spillover effects of the digital economy on agricultural green development, as well as the heterogeneity in different dimensions and in different regions and derives policy insights accordingly in order to improve relevant policies.

Assessment of the Environmental Impacts of a Localized Food System and Food Waste Reduction in a Water-Scarce Region Using Diet Optimization Models.

Despite growing interest in fresh local produce across the United States, scaling up local agricultural development might impose new environmental pressures on increasingly scarce water and land resources in specific localities. Drawing upon the case of the Palouse of the US Inland Northwest, this study evaluates land and water footprints of local foods along with food waste reduction in a water-scarce region. We used both non-robust and robust diet-optimization techniques to estimate the minimum amounts of irrigation water necessary to grow foods locally and to satisfy the local population's caloric or nutrition needs. Our modeling results indicate that, on an annual basis, an increase of less than 5% of the current freshwater withdrawal on the Palouse could satisfy 10% of the local population's aspirational demand for locally grown food products, while more than 35% of local foods (by mass) may be wasted. Furthermore, reducing food waste by 50% could simultaneously reduce water use by up to 24%, cropland use by 13%, and pastureland use by 20%. Our findings not only provide intriguing information for access to local food but could also be used to stimulate new efforts to increase consumers' and retailers' awareness of environmental benefits associated with food waste reduction.

Application of data mining based on swarm intelligence algorithm in financial support of livestock and poultry breeding insurance

Among the components of China’s actual economic structure, aquaculture has always been a key project, and as a part of agriculture, it has been greatly developed. However, there are still many problems in the actual breeding process, such as low financial support, low information transparency, high financing difficulty and lack of channels, high claims costs and serious moral hazard in the livestock and poultry breeding insurance field, which will affect the development and progress of the industry. Therefore, in this context, this paper improves the efficiency analysis of financial support for livestock and poultry breeding insurance by introducing data mining and swarm intelligence algorithms. Then use the analysis data to build a model to further evaluate the efficiency of financial support. The construction of the model is roughly divided into four parts: insurance density, insurance depth, insurance amount and income. The weight of different indicators is calculated through the analytic hierarchy process, and the overall ranking results are output through consistency test. Some data of the above models are used as the output indicators of DEA decision-making units for top-down ranking. The result analysis shows that the development of technology in this industry can effectively improve the actual productivity of agricultural crops, thus effectively promoting the development of local agriculture. In this paper, data mining and swarm intelligence algorithms are introduced into livestock and poultry breeding insurance to complete the analysis and evaluation of financial support.

Farmland Hydrology Cycle and Agronomic Measures in Agroforestry for the Efficient Utilization of Water Resources under Karst Desertification Environments

Severe soil-water loss and unfertile soil frequently occur under karst desertification environments. The surface-underground dual structure in these areas allows the surface water to leak into the subsurface through cracks and sinkholes, as well as other conduits, causing a special “karst drought”. Hence, water-resource shortage has become a challenge for local agricultural development. To realize efficient utilization of water resources, an urgent need is to clearly understand and study the law of farmland hydrological cycles under agroforestry practices, which is still understudied. Here, we focused on the hydrological cycle at the farmland scale and water-saving measures under agroforestry in three study areas representing different degrees of karst desertification. First, a significant positive correlation was found between total and available precipitations as well as land evapotranspiration (LET). Second, under agronomic measures, the soil water content in the three areas was all higher than that of the control group while soil evaporation was all lower. This indicates that agronomic measures can contribute to the efficient use of water resources by halting soil evaporation and increasing soil water content. Third, dwarf dense planting and pruning technologies were helpful in inhibiting crop transpiration and reducing vegetation interception. Fourth, in the farmland hydrological cycle of agroforestry, 77.45% of precipitation transformed into soil water storage, 24.81% into soil evaporation, 20.73% into plant transpiration, 17.40% into groundwater, and 5.18% into vegetation interception. However, their sum was greater than 100%, suggesting that the farmland-scale water cycle is an open system. The implication is that different agronomic practices under agroforestry bring certain water-saving benefits by constraining the conversion of ineffective water and promoting the storage of effective water, thus opening up promising opportunities for efficiently utilizing water resources in karst desertification areas. The finding is also significant to the control of karst desertification, soil and water conservation, and karst drought alleviation.

QUALITATIVE LONGITUDINAL ANALYSIS OF LIVESTOCK FARMING IN THE IBAGUÉ FAN REGION (TOLIMA, COLOMBIA)

&lt;p&gt;&lt;strong&gt;Background.&lt;/strong&gt; The Fan of Ibagué is one of the most important livestock and agricultural regions in the country, which faces a sustainability crisis and whose origins can be a critical point for understanding it. &lt;strong&gt;Objective.&lt;/strong&gt; To understand the historical processes of settlement of the Ibague fan and the development of the rice and livestock industries in the region. &lt;strong&gt;Methodology.&lt;/strong&gt; This historical perspective is constructed from agroecology, a transdisciplinary science that seeks to understand the multidimensional nature of current environmental problems. Qualitative analysis is thus relevant at this point since it provides means to analyze ecosystem transformations and the consequences derived from contemporary production practices. Oral testimonies by diverse actors (producers, members of institutions, traders, researchers in the region) were gathered through semi-structured interviews after field visits and later analyzed in the search for agricultural production milestones and their role in the ecological transformation of the region. The findings were contrasted with written sources and documentary records such as agricultural censuses, institutional files, and fieldwork evidence. &lt;strong&gt;Results.&lt;/strong&gt; Four crucial events in the local agricultural development of the Ibagué Fan were reported: the extensive livestock farming around 1900, which lead to the consolidation of four generations of producers; the construction of irrigation channels which benefited large-scale rice production in the area by the mid-twentieth century; the combination of rice production, livestock farming and all its associated crops; and finally, the introduction of sustainable livestock farming projects. &lt;strong&gt;Implications&lt;/strong&gt;. Historical analyzes show the need to know the perspective of the actors involved in the development of agriculture and livestock in the region over the years; these milestones are fundamental for the development of public policies that recognize the historical, social and geographical particularities. &lt;strong&gt;Conclusions&lt;/strong&gt;. The history of the colonization of the Colombian territory from the seventeenth century was characterized by the introduction, adaptation, and expansion of the livestock farming culture, together with the populating of the territories near the plains of the Magdalena river, as it was the main connecting route in the region.&lt;/p&gt;

Asynchronous Transformation of Cropping Patterns from 5800–2200 cal BP on the Southern Loess Plateau, China

Archaeobotanical studies have largely illuminated spatiotemporal differences in agricultural development across the Loess Plateau. However, the particularities of local agricultural development have not been adequately studied for complex geographical, environmental, and prehistoric contexts. Here, new archaeobotanical data and radiocarbon dating results from 27 Neolithic and Bronze Age sites in Baoji are reported. Combining these data with published archaeobotanical datasets, this study explores shifts (and underlying driving factors) in cropping patterns from the late Neolithic to Bronze Age on the southern Loess Plateau (SLP). Regional geographic, environmental, and climatic factors produced mixed millet-rice agricultural systems in the Guanzhong Plain (GZP) and western Henan Province (WHN) and foxtail and broomcorn millet dry-farming systems in the Upper Weihe River (UWR) from 5800–4500 cal BP. Wheat and barley were added to the agricultural systems of the UWR as auxiliary crops after ~4000 cal BP, while cropping patterns remained largely unchanged in GZP and WHN from 4500–3500 cal BP. Cultural exchanges and technological innovations may have influenced the formation of different agricultural patterns across the three regions (i.e., GZP, WHN, and UWR) from 4500–3500 cal BP. From 3500–2200 cal BP, wheat and barley became increasingly important crops on the SLP, although their importance varied spatially, and rice was rarely cultivated. Spatiotemporal variation in cropping patterns was driven by altered survival pressures associated with climate deterioration and population growth from 3500–2200 cal BP. This process was reinforced by internal social developments, as well as interactions with close northern neighbors, in the Shang-Zhou period.

A Bi-Temporal-Feature-Difference- and Object-Based Method for Mapping Rice-Crayfish Fields in Sihong, China

Rice-crayfish field (i.e., RCF) distribution mapping is crucial for the adjustment of the local crop cultivation structure and agricultural development. The single-temporal images of two phenological periods in the year were classified separately, and then the areas where the water disappeared were identified as RCFs in previous studies. However, due to the differences in the segmentation of lakes and rivers between the two images, the incorrect extraction of RCFs is unavoidable. To solve this problem, a bi-temporal-feature-difference-coupling object-based (BTFDOB) algorithm was proposed in order to map RCFs in Sihong County. We mapped RCFs by segmenting the bi-temporal images simultaneously based on the object-based method and selecting appropriate feature differences as the classification features. To evaluate the applicability, the classification results of the previous two years obtained using the single-temporal- and object-based (STOB) method were compared with the results of the BTFDOB method. The results suggested that spectral feature differences showed high feature importance, which could effectively distinguish the RCFs from non-RCFs. Our method worked well, with an overall accuracy (OA) of 96.77%. Compared with the STOB method, OA was improved by up to 2.18% across three years of data. The RCFs were concentrated in the low-lying eastern and southern regions, and the cultivation scale was expanded in Sihong. These findings indicate that the BTFDOB method can accurately identify RCFs, providing scientific support for the dynamic monitoring and rational management of the pattern.

Does fiscal expenditure promote green agricultural productivity gains: An investigation on corn production

Promoting green and low-carbon development in agriculture is the key to achieving high-quality development, in which financial expenditure on agriculture is an essential means to support its green development. This study first estimates the green productivity of twenty corn-growing provinces by the by-production model with Luenberger total factor productivity indicator in China from 2004 to 2018. Then the impact of fiscal spending on its green productivity growth and its mechanism are investigated by the econometric models. The results show that the average green total factor productivity indicator of China's twenty corn-growing provinces from 2004 to 2018 is 2.54%. The share of fiscal expenditure stock in agricultural output has a positive but insignificant direct impact on green productivity, whereas it significantly influences corn GTFP mainly through enhancing rural infrastructure. The share of fiscal expenditure stock has a larger effect on the green productivity in small corn-growing provinces. The findings suggest that the government should provide financial support suitable for local agricultural development.