Agricultural Factor Productivity Research Articles

Produção de coentro sob soluções nutritivas preparadas com águas salobras e densidades de semeio

ABSTRACT The use of brackish water in semi-arid regions is sometimes necessary, as water is the most limiting factor for agricultural production in these regions. The present study was conducted aiming to evaluate the production of bunches of Coriandrum sativum L., cultivar Tabocas, in hydroponic system plants exposed to nutrient solutions prepared with brackish water, obtained by mixing water from a community dam (electrical conductivity of 9.93 dS m-1) with rainwater. The treatments consisted of four values of electrical conductivity of the nutrient solution (1.49, 3.14, 4.87, and 6.44 dS m-1) and three seeding densities (1.0, 1.5, and 2.0 g of seeds per cell), arranged in a completely randomized experimental design in a 4 × 3 factorial scheme, with three replicates. Plant height was not affected up to the electrical conductivity of the nutrient solution of 6.44 dS m-1 with increasing seeding density. The electrical conductivity of the nutrient solution up to 6.44 dS m-1 at the seeding density of 2.0 g of seed per cell did not affect the shoot fresh and dry mass of the hydroponic coriander, mitigating the deleterious effect of salinity on water use efficiency.

Trocas gasosas, pigmentos fotossintéticos e crescimento de quiabeiro hidropônico sob estresse salino e ácido salicílico

ABSTRACT The high concentrations of salts present in the water sources of the Brazilian Northeastern semi-arid region stand out as one of the limiting factors for agricultural production, contributing to soil salinization and/or sodification. Thus, it is extremely important to identify strategies to mitigate the effects of salt stress on plants, such as the foliar application of salicylic acid. In this context, the objective of the present study was to evaluate the effect of foliar application of salicylic acid as an attenuator of salt stress on leaf gas exchange, water relations, photosynthetic pigments, and growth of okra cv. Canindé grown in a hydroponic system. The experiment was conducted in a greenhouse, in Pombal, PB, Brazil. The treatments consisted of four levels of electrical conductivity of the nutrient solution - ECns (3.0, 5.0, 7.0, and 9.0 dS m-1) and four concentrations of salicylic acid - SA (0, 1.2, 2.4, and 3.6 mM) distributed in a completely randomized design in a split-plot scheme, considering the ECns levels as the plots and SA concentrations as the subplots, with four replicates and two plants per plot. ECns from 3.0 dS m-1 inhibited the synthesis of photosynthetic pigments, leaf gas exchange, and growth of okra cv. Canindé. Foliar application of salicylic acid at concentrations of up to 3.6 mM does not alleviate the effects of salt stress on water relations, gas exchange and growth of okra. Salicylic acid at a concentration of 1.8 mM stimulates chlorophyll a and b biosynthesis in okra under ECns of 3.0 and 4.0 dS m-1, respectively.

On the impacts of agricultural subsidies on agricultural carbon emissions in China: empirical evidence from microdata of rice production.

China's agricultural subsidy system has increased the investment on the agricultural production factors such as energy and chemistry, which caused an increase of agricultural carbon emissions. Based on the Thousand-Village Survey data from Shanghai University of Finance and Economics in 2013, the focal paper uses ordinary and two-stage least squares (OLS and 2SLS) to systematically investigate the impact and mechanism of agricultural subsidies on agricultural carbon emissions in China. Results show that China's current agricultural subsidy system has a promoting effect on agricultural carbon emissions. Four types of agricultural subsidies, namely, direct grain subsidies, subsidies for improved varieties, comprehensive subsidies for agricultural materials, and agricultural machinery purchase subsidies, impact the agricultural carbon emissions in ascending order. The agricultural subsidies increase the agricultural carbon emissions directly and indirectly. The findings indicate that a new type of agricultural subsidy system should be constructed, which mainly includes subsidies for farmers' out-migrating for work and land transfer, direct subsidies for grain, and subsidies for improved seed varieties. Among them, the direct grain subsidies should be implemented on the size of planting area and subsidies for improved seed varieties on the size of farmland to reduce the agricultural carbon emissions.

Study on two nematode species suggests climate change will inflict greater crop damage

Food security has become one of the greatest challenges of the millennium and it is predicted to be exacerbated by climate change due to the adverse effects of soil temperature on crop productivity. Although plant-parasitic nematodes are one of the most important limiting factors of agricultural production, the fate of soil temperature in their biology is not fully understood. Here we present the effects of soil temperature on survival, reproduction, virulence, and disease severity from the perspective of two nematode species Rotylenchulus reniformis and Meloidogyne floridensis. The two nematode species were purposefully selected to represent a significant threat to annual and perennial crops. We employed novel approaches of direct as well as indirect heat exposure to evaluate nematode biology. The direct heat exposure assay involved the exposure of nematodes to hot water in a heating block at 32, 33, and 34 °C for 7 h, and subsequent evaluation of their survival after 18 h. The indirect exposure assay employed a commercial heat mat to raise soil temperatures to 32, 33, and 34 °C for 7 h during the daytime, and subsequent evaluation of nematode reproduction, virulence, and/or disease severity over the period of 6 weeks after inoculation. When directly exposed to hot water at 34 °C, the survival of R. reniformis increased by 10% while the survival of M. floridensis decreased by 12% relative to that at 32 °C. Upon increasing soil temperatures from 32 to 34 °C, the reproduction of R. reniformis and M. floridensis decreased by 49% and 53%, respectively. A significant reduction in the reproduction of M. floridensis occurred when soil temperature was increased from 33 to 34 °C, however, the same condition did not significantly affect R. reniformis reproduction suggesting the latter species has a greater ability to adapt to increasing soil temperature. Additionally, the virulence of R. reniformis was greater at 33 and 34 °C relative to that at 30 °C indicating increased aggressiveness of the nematode at higher soil temperatures. The virulence of M. floridensis appeared to be decreased as evident from increased root biomass when soil temperature was increased from 32 to 34 °C, however, the greater root biomass may have resulted from increased root galling at the higher temperatures. Results of the current study suggest that while higher soil temperatures due to climate change may lead to reduced nematode reproduction, crop losses will likely increase due to increased nematode virulence. Through the current study, we report practical evidence of the quantitative impact of climate change on the biology of plant-parasitic nematodes. Further studies involving a wider range of temperature and exposure time are needed to better understand nematode biology under climate change.

A Comprehensive Approach to Assess the Impact of Agricultural Production Factors on Selected Ecosystem Services in Poland

The conservation of environmental resources is aimed at ensuring the continuity of ecosystem services for future generations and maintaining ecosystem integrity. Given the extensive reliance of agriculture on the environment, it is crucial to identify factors that impact the quality of ecosystem services (ESs), which can be regulated at large and heterogeneous national or European scales. This research, conducted within the Polish use case of the AGRICORE project, aims to demonstrate the feasibility of establishing indicators depicted in three ES categories, which can be shaped under the actions of the Common Agricultural Policy (CAP). The study was conducted based on national sources, mostly the database of the Central Statistical Office. The analyses of regression showed a significant impact of selected agricultural productivity factors on the key performance indicators (KPIs) assessing the level of selected ESs. The yield of cereal grains, which quantitatively expresses the potential of current crop production, depended to the greatest extent (r = 0.81) on a comprehensive indicator of the agricultural production space suitability, as well as on the rise of the level of nitrogen fertilization (r = 0.68), and also on the reduced share of permanent grassland in the agricultural area (r = −0.53). It was proved that in territorial units, in which the level of nitrogen fertilization per 1 ha was greater, the share of soils with favorable pH > 5.5 was also greater. The gross nitrogen balance had a positive and significant correlation with the level of investment subsidies (r = 0.86), the share of agricultural land in the total area (r = 0.67), and the level of nitrogen fertilization (r = 0.66). Notably, there were positive correlations between the level of environmental subsidies and the increase in forestation (r = 0.68) and also between air quality and the share of cereals in the sowing structure (r = 0.86). Additionally, the impact of agricultural productivity factors on cultural eco-services was found, e.g., the share of ecological land had a positive impact on the number of natural monuments, the area of nature reserves, the number of agritourists, and agritourism nights, while the share of cereals in the sowing structure negatively correlated with the most of analyzed cultural indicators. These results are useful for the development of a module for the ABM model that employs the desired environmental parameters to provide different assessments of the impact of selected agricultural productivity factors and ecosystem services on the economic farm status.

Comparison of Various Nitrogen and Water Dual Stress Effects for Predicting Relative Water Content and Nitrogen Content in Maize Plants through Hyperspectral Imaging

Water and nitrogen (N) are major factors in plant growth and agricultural production. However, these are often confounded and produce overlapping symptoms of plant stress. The objective of this study is to verify whether the different levels of N treatment influence water status prediction and vice versa with hyperspectral modeling. We cultivated 108 maize plants in a greenhouse under three-level N treatments in combination with three-level water treatments. Hyperspectral images were collected from those plants, then Relative Water Content (RWC), as well as N content, was measured as ground truth. A Partial Least Squares (PLS) regression analysis was used to build prediction models for RWC and N content. Then, their accuracy and robustness were compared according to the different N treatment datasets and different water treatment datasets, respectively. The results demonstrated that the PLS prediction for RWC using hyperspectral data was impacted by N stress difference (Ratio of Performance to Deviation; RPD from 0.87 to 2.27). Furthermore, the dataset with water and N dual stresses improved model accuracy and robustness (RPD from 1.69 to 2.64). Conversely, the PLS prediction for N content was found to be robust against water stress difference (RPD from 2.33 to 3.06). In conclusion, we suggest that water and N dual treatments can be helpful in building models with wide applicability and high accuracy for evaluating plant water status such as RWC.

Analysis of the spatial-temporal evolution of Green and low carbon utilization efficiency of agricultural land in China and its influencing factors under the goal of carbon neutralization

Agricultural land is the most basic input factor for agricultural production and an essential component of terrestrial ecosystems, which plays a vital role in achieving carbon neutrality. Giving full play to the carbon-neutral contribution of agricultural land is a crucial part of China's economic transformation and green development. It incorporates carbon and pollution emissions from agricultural land use into the unexpected outputs of the Green and Low-carbon Utilization Efficiency of Agricultural Land (GLUEAL) evaluation system. The study utilized several advanced analytical tools, including the super-efficient Slacks-Based Measure (SBM) model, Exploratory Spatial-Temporal Data Analysis (ESTDA) method, Geodetector, and Geographically and Temporally Weighted Regression (GTWR) model. The objective was to examine the spatial-temporal evolution of GLUEAL and identify the factors that influenced it in all 31 provinces of China from 2005 to 2020. The results show that: (1) The overall spatial-temporal evolution of GLUEAL showed an increasing trend, but the disparity between provinces and regions became wider. (2) Most provinces have not yet made significant spatial and temporal jumps. They have high spatial cohesion with specific "path-dependent" characteristics. (3) The Geodetector results reveal that the Number of Rural Labor Force with Higher Education (NRLFHE) and Technology Support for Agriculture (TSA) have insufficient explanatory power on average for GLUEAL. Agricultural Economic Development Level (AEDL), Urbanization Level (UL), Multiple Crop Index (MCI), Planting Structure (PS), Degree of Crop Damage (DCD), Financial support for agriculture (FSA), and Agricultural mechanization level (AML) had stronger explanatory power on average for GLUEAL and were important factors influencing GLUEAL levels. (4) The average influence of AEDL, UL, FSA, and AML on GLUEAL changed from negative to positive. The average influence of MCI and DCD on GLUEAL was negative, and the average influence of PS on GLUEAL changed from positive to negative. This study provides a comprehensive description of the spatial and temporal evolution of GLUEAL in China. It reveals the key factors influencing GLUEAL and analyzes their spatial variations and impact patterns. These findings offer robust evidence for government policymakers to formulate policy measures for sustainable agricultural development and optimized resource allocation, promoting the transformation of agricultural land towards green and low-carbon practices and advancing the achievement of sustainable development goals.

The influence of agrotechnical measures on the number of melanin-synthesizing microorganisms

In connection with the growing scale of soil dehumification, studies of the patterns of synthesis of the precursors of humus molecules – melanins of bacterial origin – are becoming increasingly relevant. The purpose of this study was to establish the influence of the main factors of agricultural production on the spread of melaninsynthesizing microorganisms: the method of basic soil cultivation, mineral fertilizers, and the type of agricultural crop. Research methods: microbiological, laboratory-analytical, statistical, correlational. As a result, the study found for the first time that the main cultivation of the soil affects the number of melaninsynthesizing microorganisms: micromycetes, bacteria, аzotobacter. In the variant without the application of mineral fertilizers (control), the soil was characterized by the minimum amount of melanin-synthesizing bacteria using the No-till technology, 28.8% more – using disking, and 2.4 times more – using ploughing. The number of melaninsynthesizing micromycetes in the variant without fertilizers was also maximum upon ploughing, the average number was observed with No-till technologies, and the minimum number – using shallow disk tillage. Application of mineral fertilizers in a dose of N30P30K65 leads to an increase in the number of melanin-synthesizing bacteria in the ploughing option by 3.58 times, disking by 3.53 times, No-till technology by 2.28 times. An increase in the dose of mineral fertilizers to N150P100K120 contributes to an increase in the number of melanin-synthesizing bacteria by 5.04 times upon ploughing, 5.78 times upon disking, and 2.24 times upon no-till technologies. The medium-significant nature of the relationship between the content of humus and the number of melanin-synthesizing bacteria (r=0.528) and their share in the total number of microorganisms (r=0.470) suggested that in chernozem inherent in growing sunflowers, humus is formed mainly with the participation melanins of bacterial origin. Metabolites of polysaccharide-synthesizing bacteria take part in the formation of the resistance of humus molecules to microbial mineralization, the probability of the formation of colonies of which has a moderately significant relationship with the content of humus (r=0.532). The results of these studies can be used in the development of recommendations for regulating the content of humus in agricultural soils, preventing its excessive mineralization, which will allow preserving and increasing soil fertility

Prediction of Soil Water Content Based on Hyperspectral Reflectance Combined with Competitive Adaptive Reweighted Sampling and Random Frog Feature Extraction and the Back-Propagation Artificial Neural Network Method

The soil water content (SWC) is a critical factor in agricultural production. To achieve real-time and nondestructive monitoring of the SWC, an experiment was conducted to measure the hyperspectral reflectance of soil samples with varying levels of water content. The soil samples were divided into two parts, SWC higher than field capacity (super-θf) and SWC lower than field capacity (sub-θf), and the outliers were detected by Monte Carlo cross-validation (MCCV). The raw spectra were processed using Savitzky–Golay (SG) smoothing and then the spectral feature variable of SWC was extracted by using a combination of competitive adaptive reweighted sampling (CARS) and random frog (Rfrog). Based on the extracted feature variables, an extreme learning machine (ELM), a back-propagation artificial neural network (BPANN), and a support vector machine (SVM) were used to establish the prediction model. The results showed that the accuracy of retrieving the SWC using the same model was poor, under two conditions, i.e., SWC above and below θf, mainly due to the influence of the lower accuracy of the super-θf part. The number of feature variables extracted by the sub-θf and super-θf datasets were 25 and 18, respectively, accounting for 1.85% and 1.33% of the raw spectra, and the variables were widely distributed in the NIR range. Among the models, the best results were achieved by the BPANN model for both the sub-θf and the super-θf datasets; the R2p, RMSEp, and RRMSE of the sub-θf samples were 0.941, 1.570%, and 6.685%, respectively. The R2p, RMSEp, and RRMSE of the super-θf samples were 0.764, 1.479%, and 4.205%, respectively. This study demonstrates that the CARS–Rfrog–BPANN method was reliable for the prediction of SWC.

The halophilic bacteria Gracilibacillus dipsosauri GDHT17 alleviates salt stress on perennial ryegrass seedlings.

Adverse abiotic environmental conditions including excess salt in the soil, constantly challenge plants and disrupt the function of plants, even inflict damage on plants. Salt stress is one of the major limiting factors for agricultural productivity and severe restrictions on plant growth. One of the critical ways to improve plant salt tolerance is halotolerant bacteria application. However, few such halotolerant bacteria were known and should be explored furtherly. Halophilic bacterium strain was isolated from saline soil with serial dilution and identified with classical bacteriological tests and 16S rRNA analysis. Perennial ryegrass (Lolium perenne L) was used in this study to evaluate the potential effect of the bacteria. A halophilic bacterium strain GDHT17, was isolated from saline soil, which grows in the salinities media with 1.0%, 5.0%, and 10.0% (w/v) NaCl, and identified as Gracilibacillus dipsosauri. Inoculating GDHT17 can significantly promote ryegrass's seedling height and stem diameter and increase the root length, diameter, and surface area at different salt concentrations, indicating the significant salt stress alleviating effect of GDHT17 on the growth of ryegrass. The alleviating effect on roots growth showed more effective, especially on the root length, which increased significantly by 26.39%, 42.59%, and 98.73% at salt stress of 100 mM, 200 mM, and 300 mM NaCl when the seedlings were inoculated with GDHT17. Inoculating GDHT17 also increases perennial ryegrass biomass, water content, chlorophyll and carotenoid content under salt stress. The contents of proline and malonaldehyde in the seedlings inoculated with GDHT17 increased by 83.50% and 6.87%, when treated with 300 mM NaCl; however, the contents of MDA and Pro did not show an apparent effect under salt stress of 100 mM or 200 mM NaCl. GDHT17-inoculating maintained the Na+/K+ ratio in the salt-stressed ryegrass. The Na+/K+ ratio decreased by 26.52%, 6.89%, and 29.92% in the GDHT17-inoculated seedling roots treated with 100 mM, 200 mM, and 300 mM NaCl, respectively. The GDHT17-inoculating increased the POD and SOD activity of ryegrass seedlings by 25.83% and 250.79%, respectively, at a salt stress of 300 mM NaCl, indicating the properties of GDHT17, improving the activity of antioxidant enzymes of ryegrass at the salt-stress condition. Our results suggest that G. dipsosauri GDHT17 may alleviate salt stress on ryegrass in multiple ways; hence it can be processed into microbial inoculants to increase salt tolerance of ryegrass, as well as other plants in saline soil.

Impact of Temperature Extremes on Carbon Emissions from Crop Production in Hebei Province, China

The study investigated the impact of temperature extremes on carbon emissions (CE) from crop production. (1) Background: Many scholars have studied climate extremes. However, the research on the relationship between temperature extremes and CE is not extensive, which deserves attention. (2) Methods: The study adopted a fixed-effect model to analyze the impact of temperature extremes on CE from crop production, and the moderating effect was tested using total factor productivity (TFP) in agriculture. (3) Results: Temperature extremes in Hebei Province were mainly reflected in a decline in the cold day index (TX10p) and a rise in the warm spell duration index (WSDI) and the number of summer days (SU25). Additionally, TX10p was positively correlated with CE. For every 1% reduction in TX10p, CE dropped by 0.237%. There was no significant correlation between WSDI and CE. Finally, the agricultural TFP had a significant moderating effect on CE, with each 1% increase resulting in a corresponding 0.081% decrease in CE. (4) Conclusions: The results indicated a warming trend in Hebei Province, which resulted in a decrease in the number of winter days, and reduced CE from crop production. The improvement of input efficiency in agricultural production factors helped moderate the CE.

Spatial Network and Driving Factors of Agricultural Green Total Factor Productivity in China

Agricultural green total factor productivity (AGTFP) is an important indicator to reflect the sustainability level of agriculture. The AGTFP network reflects the spatial correlations of the AGTFP among regions; thus, exploring its network structure and influencing factors can provide targeted policy guidance to the coordinated development of the agriculture sector. This study builds an epsilon-based measurement data envelopment analysis (EBM-DEA) model to calculate 31 provincial AGTFPs in China from 2002 to 2020. Then, social network analysis (SNA) was utilized to explore the characteristics of the AGTFP network, and the quadratic assignment procedure (QAP) was applied to find its external influencing factors. We reached four central conclusions: (1) Overall, there was a gradual upward trend of AGTFP in China during 2002~2020, and the average value rose from 0.75 in 2002 to 0.90 in 2020, but there were some differences among regions. (2) There is a complex and stable network characteristic of AGTFP; the average network density is 0.3753, and the average network efficiency is 0.4714. Meanwhile, some eastern and central areas, such as Henan, Anhui, Hubei, Hebei, Jiangsu, etc., have relatively high centrality and are a bridge in the entire network. (3) The AGTFP network can be divided into eight blocks, including two net beneficial blocks (the central-eastern provinces with high centrality); two net spillover blocks, including the provinces located in the developed urban areas (Beijing, Tianjin, Shanghai, and Jilin), the underdeveloped northwest regions (Ningxia, Qinghai, Xinjiang, and Tibet). The other areas are two-way spillover blocks. (4) Transportation development gap, technological progress gap, and the similarities of the agricultural industry structure are critical factors influencing the AGTFP network. Hence, improving the efficiency of the logistics and transportation industry, promoting technology transfer from developed areas to underdeveloped areas, and developing characteristic agriculture are all conducive to promoting the whole region’s AGTFP. Our research provides policy implications for sustainable agricultural development in China and other developing countries.

Spatiotemporal Evolution of Cultivated Land Use Eco-Efficiency and Its Dynamic Relationship with Landscape Pattern Change from the Perspective of Carbon Effect: A Case Study of Henan, China

Cultivated land is a vital factor in agricultural production but faces multiple challenges, including declining total area, spatial transformation, and ecological degradation. It is imperative to enhance cultivated land use eco-efficiency (CLUE). This study aimed to evaluate the CLUE that considers both carbon sequestration and emissions using the SBM model at the county level. Next, spatial autocorrelation was employed to measure CLUE’s spatial correlation. The spatial agglomeration pattern of CLUE was determined, then time-series cluster analysis was used to identify the temporal evolution patterns of CLUE in various districts and counties. Furthermore, we explored the spatiotemporal dynamic relationship between CLUE and landscape pattern changes using landscape pattern index and geographically and temporally weighted regression (GTWR), considering spatiotemporal heterogeneity, and using interaction detectors to identify the interaction between landscape pattern factors on CLUE. The results show that: (1) From 2000 to 2020, CLUE in Henan Province varied between 0.50 and 0.70 in most years, indicating potential for improvement. There are four primary temporal evolution patterns: 26 Late-development, 22 Wave-rising, 27 Fluctuation-rising, and 29 Continuous-rising types of CLUE. (2) CLUE exhibits low values in the middle and eastern regions, i.e., areas with high values are concentrated in the southern districts, counties, and western and northern regions. CLUE has a significant positive spatial correlation with HH agglomeration areas mainly concentrated in Xinyang City, and LL agglomeration areas mainly located in the eastern and central regions. (3) Overall, different landscape factors exhibit varying degrees of spatiotemporal heterogeneity in their impact on CLUE. The total area and aggregation of cultivated land have a positive effect on CLUE, with the area of the positive influence of the total area gradually expanding over time and the aggregation gradually decreasing. The complexity of cultivated land shape has a negative effect. The impact of cultivated land patch density is two-sided, with the area of negative influence gradually expanding over time. (4) The interaction between the total area, shape, and aggregation of cultivated land is enhanced. Additionally, the interaction between cultivated land patch density and other factors has changed from a weakening to a strengthening one, and the “double-edged sword” effect has gradually shifted into a one-way effect. Therefore, in the process of land consolidation, it is recommended to prioritize regularized, larger, and more concentrated cropland patches whenever possible.

Transient drought during flowering modifies the grain proteome of bread winter wheat.

Drought is among the most limiting factors for sustainable agricultural production. Water shortage at the onset of flowering severely affects the quality and quantity of grain yield of bread wheat (Triticum aestivum). Herein, we measured oxidative stress and photosynthesis-related parameters upon applying transient drought on contrasting wheat cultivars at the flowering stage of ontogenesis. The sensitive cultivar (Darunok Podillia) showed ineffective water management and a more severe decline in photosynthesis. Apparently, the tolerant genotype (Odeska 267) used photorespiration to dissipate excessive light energy. The tolerant cultivar sooner induced superoxide dismutase and showed less inhibited photosynthesis. Such a protective effect resulted in less affected yield and spectrum of seed proteome. The tolerant cultivar had a more stable gluten profile, which defines bread-making quality, upon drought. Water deficit caused the accumulation of medically relevant proteins: (i) components of gluten in the sensitive cultivar and (ii) metabolic proteins in the tolerant cultivar. We propose specific proteins for further exploration as potential markers of drought tolerance for guiding efficient breeding: thaumatin-like protein, 14-3-3 protein, peroxiredoxins, peroxidase, FBD domain protein, and Ap2/ERF plus B3 domain protein.

Influences of Climatic Factors and Human Activities on Forest–Shrub–Grass Suitability in the Yellow River Basin, China

Natural and human factors co-drive changes in vegetation type and distribution. In this study, we constructed an index system covering 17 natural and human activity indicators in six dimensions by using climate data, county-level human activity data, and forest–shrub–grass suitability data from 448 sample counties in the Yellow River Basin of China in 2018. On this basis, we evaluated the influence of human activities and climatic factors on vegetation suitability using multiple regression and relative importance analysis methods. The multiple regression results demonstrate that climatic factors had positive effects on vegetation suitability in the Yellow River Basin, while the influence of human activities on vegetation suitability varied according to the situation. Specifically, economic factors such as per capita disposable income of urban residents and per capita disposable income of rural residents; urbanization factors such as population density, urbanization rate, and construction land area proportion; social development factors such as road density; and agricultural production factors such as the cultivated acreage proportion and the value added of the primary industries proportion all influence vegetation suitability. There is a great regional heterogeneity in the effects of human activities such as economic factors and urbanization factors on vegetation suitability. The relative importance analysis results show that the relative importance of the factors influencing vegetation suitability in the Yellow River Basin was as follows, in order of importance: climatic factors > agricultural production factors > urbanization factors > ecological projects > social development factors > economy factors; however, except for climatic factors, the importance of other influencing factors varied from region to region. This study provides a theoretical basis for optimizing vegetation adjustment schemes and forest and grass ecosystem layout according to regional characteristics.

Research on Spatial-Temporal Characteristics and Affecting Factors of Agricultural Green Total Factor Productivity in Jiangxi Province

Increasing green total factor productivity is the key to achieving green development in agriculture. This study measured the green total factor productivity of Jiangxi’s agriculture, and its regional and temporal evolution characteristics were examined. The fixed-effects model was then used to investigate the model’s fundamental components empirically. The study’s findings reveal the following: During the period under review, technical change was the primary element driving the rise in the green total factor productivity of agriculture. A rising “U”-shaped trend with notable regional variances characterizes the spatial and temporal evolution. The primary factors that affect changes in green total factor productivity in agriculture include the ease of transportation, the per capita disposable income of rural residents, the level of agricultural mechanization, the degree of urbanization, the level of financial support for agriculture, and the percentage of workers in secondary industries, with the impact effect values of 0.581, 0.647, −0.126, −0.729, −0.326, and −0.559, respectively. As a result, it is suggested that in order to substantially increase agricultural green total factor productivity, agricultural green technological support should be strengthened, more fully developed, and promoted in a multi-pronged approach.

МЕХАНІЗМ УПРАВЛІННЯ ТОВАРНОЮ СПЕЦІАЛІЗАЦІЄЮ АГРАРНИХ ПІДПРИЄМСТВ

The article reveals the organizational and economic principles of building a mechanism for managing the commodity specialization of agricultural enterprises. Factors affecting the reproduction of production resources as agricultural production factors are defined. It has been established that they have both a general economic character and are manifested at the level of subjects of agricultural management, are subjective or objective. The factors that determine the need for systemic legal influence on the management of commodity specialization of agricultural enterprises have been determined. The elements of the architecture of the organizational and economic mechanism of managing commodity specialization of agricultural enterprises have been developed and substantiated. The conceptual basis of the commodity specialization management mechanism assumes the definition of principles, goals, and tasks, as well as a set of tools for the agricultural specialization management mechanism, which is aimed at achieving sustainable functioning and development of enterprises. The specified concept takes into account the trends in the formation of economic potential, the internal infrastructure of the enterprise, the leading architectural solutions, and standards, the management model and requirements for management processes, and also defines the principles of transition from the existing state of the enterprise to the target one. It has been proven that this mechanism allows the implementation of adaptive strategies for the development of industrial and commercial activity due to the careful consideration of the effects of external and internal environmental factors when mobilizing the components of production and economic potential, as well as determining the configuration of product specialization management systems in enterprise management.

Impact of Land Ownership in Enhancing Agricultural Productivity in Rural Areas of Eastern Cape Province

Land is a principal and calamitous factor in agricultural production and the growth of livelihood prospects in Sub-Saharan Africa. Land ownership is an indispensable resource for agrarian efficiency in the pastoral regions of South Africa. It leads to sustainable and feasible farming. However, the mainstream rural dwellers struggle to access and obtain land ownership, thus leading to low agricultural productivity. Therefore, the study seeks to investigate the effect of land tenure in enhancing agrarian efficiency in rural areas of Eastern Cape Province. The study used a cross-sectional research approach and a multi-stage sampling procedure. A semi-structured questionnaire was used to collect data from 250 smallholder farmers. The analysis tools used were descriptive statistics, Logit regression, and Propensity Score Matching. Farmers were landowners, with 70% and 60% having small-sized farms, which they utilise for agricultural production. About 17% of the farmers did not utilise the land they own because of a lack of funds, water availability and farming equipment. The farmers' age, gender, years spent in school, members of farm organisations, access to extension services, household income, and hired permanent labour were socio-economic and institutional factors influencing land ownership. PSM results revealed that fully owned small-sized farms achieved high agricultural production than rented large-sized farms. The study concludes that full land ownership impacts agricultural productivity more than rented land. Hence, productivity is high. Therefore, the study recommends that the South African government and land reform policy must fast-track land redistribution among rural dwellers and farmers to enhance agricultural productivity.

Does agricultural factor misallocation hinder agricultural green production efficiency? Evidence from China

The sustainable development of agriculture is challenged by two major issues: increasing resource constraints and environmental pollution. Sustainable agricultural development is achievable by improving green total factor productivity from the perspective of resource allocation. To promote the green development of agriculture, this paper utilizes the SBM super-efficiency mode and thus calculates the agricultural resource misallocation index and agricultural green production efficiency index in China between 2001 and 2019. Furthermore, this paper discusses the temporal and spatial evolution characteristics of agricultural green production efficiency, using a fixed model and spatial econometric models to estimate the influence effect of agricultural resource misallocation on green production efficiency. Below are the results. First, China's agricultural green total factor productivity is growing at an impressive rate, with high efficiency in the northeast, northwest, and southeast coastal areas and low efficiency in the central and inland areas. Second, agricultural capital misallocation, labor misallocation, and land misallocation all negatively impact agricultural green production efficiency. Accordingly, the misallocation of agricultural factors will hamper the growth of agricultural green production efficiency in this region and also in the surrounding areas. Third, the indirect impact on the own agricultural green production efficiency exceeds its direct impact on neighboring regions' efficiency. Fourth, the mechanisms are the upgrading of agricultural industry structure and green technology innovation. According to the findings, reducing resource misallocation can substantially enhance agricultural green productivity, which is an imperative step in addressing agricultural green production. Hence, policies should be formulated that highlight the regional allocation of agricultural production factors and green production-oriented concept of agricultural production. Also, the government should promote the transformation and upgrading of the agricultural industrial structure, as well as the application of green agricultural technologies.

The Impact of Green Finance on China’s Agricultural Trade

Enhancing the effectiveness of green development of the agricultural trade economy with green finance is a practical need to promote the healthy development of agricultural trade. This manuscript empirically analyzes the impact of green finance on China’s agricultural products import and export trade by using provincial-level panel data from 30 Chinese provinces from 2001–2019. The findings show that: (1) Green finance positively impacts China’s agricultural import and export trade at the 1% significant level, expanding the scale of agricultural imports and exports. (2) The positive impact of green finance on China’s agricultural import and export trade is heterogeneous across regions. Accordingly, this paper puts forward policy suggestions such as strengthening the support of green finance to agriculture, focusing on the improvement of green total factor productivity in agriculture, and promoting synergistic regional development through the implementation of differentiation of green finance.