1- Introduction

2- Background

3- Theoretical Framework

4- Econometric model

5- Data

6- Results and discussion

7- Conclusion and policy implications

References

Abstract

This study investigates the factors affecting farmland rental prices in China. Special emphasis is put on the capitalization of China’s grain subsidy program into land rental rates. Using national representative farm-level data, Heckman sample selection model, and quantile regression (QR) approach, we find that a 10% increase in grain subsidy payments for contracted farmland increases the farmland rental price by about 1%. However, quantile regression results show that the capitalization rate is heterogeneous and varies across the distribution. Findings suggest that family labor input and farm location are important factors driving up farmland rental prices. Moreover, for farm size, rental experience, and natural disaster we detect a negative impact on land rental prices.

Introduction

To promote grain production, ensure food security, and improve rural household income, China’s government implemented a national grain subsidy program in 2004 (Yi et al., 2015). Since its inception, the program’s size has increased continuously (Huang et al., 2013), and the program accounted for 22% of the government’s annual agricultural and environmental expenditures in 2014 (Yi and McCarl, 2018). The government initially designed the grain subsidy program (GSP) to increase grain production and to ensure national food security. Thus, researchers focused their efforts on estimating the effects of GSP on agricultural output and rural livelihoods. For instance, Tan et al. (2006) using micro survey data found that the direct grain subsidy has had a modest impact on farmers’ income and has reduced income inequality in villages. However, Huang et al. (2011) detected that grain subsidies have no impact on grain production and demand for production inputs. In a recent study, Huang and Yang (2017) stated that the grain subsidy’s impact on farmers’ income was negligible because the size of the subsidy per farmer was minimal. While there has recently been ample research on developments in land use and rural adjustments in China (e.g. Zhang et al., 2019; Liu et al., 2018; Liu, 2018; Yang et al., 2018; Liu and Li, 2017; Liu et al., 2014; Li et al., 2014; Wang et al., 2013), no study has examined China’s GSP from the perspective of human-land relationships, or specifically rural households’ land rental activities (e.g., farmland rental behavior, farmland rental prices). During the transition of China’s production mode and land use pattern, the farmland rental market is believed to be an essential channel in solving land fragmentation and small-scale nature of Chinese farms (Zhou et al., 2019).

Occurrence and Functions of Mucilage

A Model of a Mucilage-Supported Diazotrophic Microbiota

Disassembly of the Complex Mucilage Polysaccharide

Sugar Utilization to Support Nitrogenase Activity

Reduction of Oxygen Levels in the Mucilage Environment

Maintaining Low Nitrogen Levels in the Mucilage Environment

Concluding Remarks

Acknowledgement

References

Role for Nitrogen Fixation in Cereal Crops

Nitrogen-fixing microbial associations with nonlegumes, especially cereals, have been a topic of intense interest for more than a century, since such associations could reduce the requirement for nitrogen fertilizers [1–4]. For instance, sugarcane associates with diazotrophic endophytes that contribute to its nitrogen nutrition in some environments [5–7] and a study based on 15N dilution experiments in Miscanthus × giganteus concluded that this bioenergy feedstock could acquire about 16% of its nitrogen from the air [8]. These examples indicate that some monocots have the potential to associate with diazotrophs and acquire small, but significant, amounts of fixed nitrogen from the atmosphere. It has been shown that the model C4 grass Setaria viridis can obtain most of its fixed N from associative nitrogen fixation following inoculation with diazotrophs [9]. The possibility that cereal crops obtain a significant proportion of total N by associative nitrogen fixation has also been suggested by a 50-year assessment of global nitrogen budgets in maize (Zea mays), rice (Oryza sastiva), and wheat (Triticum aestivum), which concluded that up to 24% of the total nitrogen in these crops was derived from nonlegume symbiotic nitrogen fixation [10]. Interestingly, mucilage on aerial roots of sorghum (Sorghum bicolor) with an inset micrograph of Azospirillum brasilense was highlighted on the cover page of the proceedings of a conference on cereal nitrogen fixation held in India in 1984 [11], suggesting that it was suspected more than 35 years ago that sorghum mucilage harbors a diazotrophic microbiota. However, no report on nitrogen fixation in sorghum mucilage was published in the 1984 proceedings volume or elsewhere.

Occurrence and Functions of Mucilage

A key feature of the Sierra Mixe maize landrace mucilage is the abundance of sugars that potentially serve as a source of energy for the diazotrophs. The monosaccharide composition indicated that the mucilage primarily comprises fucose (41%), galactose (36%), arabinose (14%), xylose (3%), glucuronic acid (3%), and mannose (3%) [12]. This composition is similar to the mucilage reported for maize underground roots [15,16]. Osborne et al. found that underground root mucilage contained fucose (61.0%) and glucose (31.4%), while Chaboud found the mucilage to contain galactose (30.7%), fucose (19.3%), glucose (18.5%), xylose (15.2%), and arabinose (13.4%). Both of these previous studies showed high amounts of fucose, xylose, arabinose, and galactose, which agrees qualitatively with the analysis of the Sierra Mixe aerial root mucilage. This monosaccharide composition is not commonly found in plant cell wall polysaccharides and may play a role in signaling associative diazotrophic bacteria that can degrade the mucilage complex polysaccharide and use the released monosaccharides to support growth and nitrogen fixation.

Key Features of Pollen Germination in Cereals

Genetic and Proteomic Screening for Key Factors in Pollen Germination

Key Pathways Identified for Pollen Germination in Cereals

Concluding Remarks

References

Germination of Pollen

In flowering plants, the distribution of pollen (see Glossary) across land by wind and/or animals drives the spread of genetic variation within a species. Agriculturally, successful fertilization of flowers in an increasingly harsh and unpredictable climate is the key determinant of grain production and yield in cereal crops [1]. Mature pollen usually contains only two cell types – sperm cells and the much larger vegetative (or tube) cell – and desiccates before release from the anther. On adhering to a compatible stigma, pollen grains respond to signals from the mother plant and become active, undergoing cytoplasmic reorganization and activation of stored RNA and protein to produce a pollen tube originating from the vegetative cell. The pollen tube elongates within the pistil until it reaches the egg cell, where the sperm cell divides to enable the double-fertilization event typical of plants (Figure 1, Key Figure).
The factors that control successful pollen germination have been the focus of plant reproduction, evolution, and breeding research to increase crop yield and to overcome hybridization barriers [1,2]. Barriers to fertilization include interspecific incompatibility as well as self-incompatibility, which maintains genetic diversity within a local population. However, overcoming some of these constraints in a breeding environment can contribute to the production of novel elite lines for specific end-uses. Since 2003, pollen transcriptomic studies, together with identified mutants, have rapidly expanded our knowledge of the regulatory mechanisms that govern the fertilization process, including signaling pathways and cytoskeleton proteins [3–11]. However, most of this research has occurred in model plant species such as arabidopsis; despite massive agronomic and economic interest, relatively little is known about these molecular processes in cereal crops (the Poaceae). This review focuses on the unique characteristics of pollen grain adhesion, hydration, germination, and pollen tube growth in monocot cereals, and provides an overview of our current understanding of the regulators governed by the male gametophyte in the best-studied species, rice (Oryza sativa) and maize (Zea mays) (Figure 1C).

Cereals have a long history of interaction with humans. At around 40–50 thousand years ago (kA), late Neanderthals consumed wild Triticeae grains in a cooked form as suggested by the analysis of the dental calculus from multiple locations in Europe, the Near East, and Africa [1]. The first fossil remnants of plants exhibiting characteristics of the domesticated cereal crops have been discovered at the multiple archaeological sites dated to 8–10 kA — the historic period marking a transition from the huntergatherer lifestyle to the early sedentary agricultural societies. The most prominent examples are the non-brittle spikes of the proto-domesticated wheat (diploid, tetraploid and hexaploid Triticum species) and barley (Hordeum vulgare ssp. vulgare) discovered in the excavations in the Fertile Crescent area of the Near East; the nonshattering panicles of rice (Oryza sativa) from the Yangtze river valley, China; and the starchy enlarged seeds of maize (Zea mays ssp. mays) from the Central Balsas river valley, Mexico, which distinguish maize from its wild progenitor teosinte (Z. mays ssp. parviglumis) [2– 6]. The archaeobotanical analyses of the fossil findings provided direct empirical evidence on the temporal scale and the location of the early events of cereal domestication history, which was packaged in the so-called domestication models [2,3,7]. However, to expand on the archaeological models, detailed understanding of genetic relationships between the cultivated and wild populations is crucial. In the pre-genomics era, the pioneering molecular studies suggested explicit demographic models of cereal domestication based on the population genetic analyses of nucleotide variation in isolated genes and genomic regions [8–12]. The molecular evolutionary models favored a monophyletic origin of crops and strong selective pressures under domestication. On the contrary, the archaeological models assumed a polycentric origin of domestication traits and a millennia-long process of fixation of these traits in the cultivated populations. Advancements in the genome sequencing technologies enabled the elucidation of the genetic ancestry and evolutionary history of domesticated genotypes at the unprecedented resolution and scale [13,14 ,15]. It was anticipated that the genome-wide diversity estimates would provide a solid basis to the demographic history reconstruction. However, for many cereals, the interpretation of the revealed patterns remained controversial hinting at the complexity of their evolutionary history [15,16 ]. Population genomics has recently revealed intriguing patterns in the cultivated barley genomes that shed light on the trajectory of barley domestication [17,18,19].

Because of the growing consumer demand for healthy, natural and convenient foods, attemps are being made to improve snack foods nutritional values by modifying their nutritive composition (Bhaskaran and Hardley, 2002; Gray et al., 2003). Cereal bars are a popular and convenient food and, therefore, would be an ideal food format to deliver fruit derived phenolic antioxidants (Sun-Waterhouse et al., 2010; Damasceno et al., 2016). Phenolics compounds, e.g. flavonoids and phenolics acids, belong to an important class of secondary metabolites and own recognized antioxidant activity. Antioxidant compounds neutralise free radicals and inhibit or interrupt the chain of propagation of oxidative reactions, converting free radicals into less harmful molecules and repairing the oxidative damage in human cells (Borges et al., 2014). This class of compounds is also relevant to insertion in the elaboration of cereal bars. The banana is one of the most extensively consumed fruits in the world and represents approximately 40 per cent of the world fruit trade. World banana production was 102 Mt in 2012, and Brazil was the sixth most important banana-producing country with a total production of 7 Mt (FAO, 2016). The banana peel represents 30-40 per cent of the total weight of the fruit, it is rich in minerals (Emaga et al., 2007) and its quantity of total dietary fiber reaches 43.2 to 49.7 per cent (Mohapatra et al., 2010). González-Montelongo et al. (2010) reported that banana peels contain large amounts of dopamine and l-dopamine, catecholamines that exhibit antioxidant activity, and depending on the variety, ripeness, and on the type of phenolic compound extraction used, the banana peel has from 3.1 to 380 mg GAE.g1 of total phenolic compounds (González-Montelongo et al., 2010; Rebello et al., 2014). In addition, banana peel contains low but permissible concentrations of toxic elements and may be recommended as dietary supplement, especially considering that banana peel contains lower quantities of toxic elements than other by-products, as pineapple peel (Kuppusamy et al., 2017). The application of banana peel flour in cereal bars was performed using a simplex centroid design for mixtures of banana peel flour, rice flakes and oat flour, and the products evaluated regarding sensory acceptability and profile (Carvalho and Conti-Silva, 2018). The cereal bars with 21 and 27.72 per cent of banana peel flour had good overall acceptability and aroma acceptability, respectively, even with different sensory profiles, indicating a relevant use to this by-product, which may favor the development of new products.

Soil physical and chemical properties and crop yields vary spatially and temporally on different scales. The variability is largely influenced by pedogenesis processes (Gilliam and Dick, 2010; Moradi et al., 2016), topography (Jankowski et al., 2011), and agricultural practices including tillage operations, compaction, chemical application, and harvesting (Alaoui et al., 2011; Gajda et al., 2016; Ozpinar and Ozpinar, 2015; Schjønning et al., 2009). Knowledge about soil variability is essential in precise determination of the most appropriate and localized management practices and amendments to improve and align soil conditions and quality for an effective use of water and nutrients and crop growth (Bölenius et al., 2017; Kumhálová and Matějková, 2017; Usowicz and Lipiec, 2017). For example, variable-rate management practices such as fertilization and irrigation based on spatial data of chemical and soil water status (Sadler et al., 2005; Pedrera-Parrilla et al., 2016; Mubarak et al., 2016) help to limit the use of agricultural chemical and water and to reduce leaching and environmental pollution (Adamchuk and Viscarra Rossel, 2011; Bogunovic et al., 2014; Hedley and Yule, 2009). Further, analysis of the spatial dependency of soil water status along with weather conditions are key issues for modelling soil water dynamics and balance (Awe et al., 2015; Kędzior and Zawadzki, 2016; Schwen et al., 2014). The spatial distribution of different soil properties can be evaluated by classical and spatial statistics using direct semivariograms and cross-semivariograms (Goovaerts, 1999; Webster, 2008). Semivariograms describe the dependence of the values of a given variable on the distance between the sampling sites and thereby the spatial structure of the variation. Thus, they help in designing a sampling setup including the number of samples required for adequate description of the soil and yield in agricultural areas (Jabro et al., 2010; Moradi et al., 2016). When different variables are related, their joint spatial patterns can be evaluated by cross-semivariograms. Cross-semivariogram data and maps obtained with the co-kriging procedure allow prediction of time-consuming and/or costly variables from those measured more easily. Using cross-semivariograms, Jabro et al. (2010) found that soil penetration resistance was spatially correlated with water content, total porosity, and saturated hydraulic conductivity. The study by Walter et al. (2002) showed spatial interdependence between weed species density and soil properties such as clay, phosphorus contents and pH, and the extent of the spatial dependence varied among the study years. However, little information is available about the spatial and inter-annual variability of crop yields and soil properties, especially on a field scale, although it is the main methodological means for implementing precision agriculture technology of different intensity to compensate and improve soil conditions for strengthening crop growth (Diacono et al., 2013; Usowicz et al., 2009; Webster, 2008).

مقاله سال 2016

تاثیرات مصرف دانه و مکمل آنزیم کربوهیدرات در فیزیولوژی گوارش مرغ مورد بررسی قرار گرفت. مجموع 625 عدد جوجه یک روزه (راس 308) به طور تصادفی با پنج روش تیمار مختلف در طرحی کاملا تصادفی قرار گرفتند. تیمار ، شامل دو نوع مختلف از دانه ها (گندم و جو) می شد که با مکمل یا بدون مکمل کربوهیدرات چندگانه بود. رژیم ذرت نیز مطرح شده تا به عنوان یک تنظیم کننده بکار رود. مصرف خوراک جو با مکمل کربوهیدرات چندگانه منجر به جذب بیشتر خوراک (P <0.01) نسبت به آن دسته که از رژیم های غذایی ذرت و گندم در تغذیه شان استفاده کرده بودند می شود . پرندگانی که از رژیم غذایی جو و گندم تغذیه کردند افزایش وزن کمتری داشتند با وجود اینکه میزان جذب بالاتری در خوراک داشتند (P <0.01).تعداد کل و شمار مختلفی از باکتری ها از جمله گرم منفی، اشریشیا کلی، و کلستریدیا پس از تغذیه گندم و جو کاهش یافت اما تعداد لاکتوباسیل و بیفیدوباکتریوم افزایش یافت (P <0.01). تغذیه رژیم جو و گندم ارتفاع پرزها در قسمت های مختلف روده کوچک را در مقایسه با آنهایی که از رژیم ذرت تغذیه کردند کاهش می دهد.با این حال ، مکمل آنزیمی جو و رژیم غذایی گندم وزن مفید و میزان جذب غذا را افزایش داده و در نتیجه تعداد باکتری E. coli و کلستریدیا کاهش داده و تعداد لاکتوباسیل ها و بیفیدوباکتریوم را افزایش می دهد ، و همچنین اثرات منفی بر روی ارتفاع پرزهای روده (P <0.01) را ترمیم می کند. فعالیت های پانکراس α-آمیلاز و لیپاز (P <0.01) در جوجه هایی که خوراک گندم و رژیم های غذایی جو داشتند در مقایسه با تغذیه اصلاح شده رژیم غذایی ذرت افزایش یافته بود .مکمل آنزیمی فعالیت های پانکراس α-آمیلاز و لیپاز (P <0.01) را کاهش می دهد. در نتیجه، رژیم های غذایی مختلف بدون نشاسته پلی ساکاریدی که فاقد مکمل آنزیمی هستند ، تاثیر سوء بر گرانروی مواد هضمی ، فلور روده، مورفولوژی پرز و فعالیت آنزیم پانکراس می گذارند.

مقاله سال 2016