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The use of process-based modelling is increasing in most disciplines of plant science, but criteria for what is acceptable modelling work have rarely been made explicit. Unlike empirical work, modelling does not provide direct information on nature, and the goal is generally to explain natural phenomena, or predict their consequences, rather than reveal new phenomena or test specific hypotheses. Goals, methods and results of modelling and empirical work thus differ and they should be judged by different criteria. This note shows how the four criteria of explanation, testability, novelty and good modelling practice can be applied to modelling papers in the plant sciences. The practical implementation of these criteria is discussed, and a checklist of eight questions is derived with which papers can be evaluated. To illustrate the use of the criteria, they are applied to a classic publication from the crop modelling literature [Simulation of Assimilation, Respiration and Transpiration of Crops. Pudoc, Wageningen]. [Copyright &y& Elsevier]

Unmanned aerial vehicle-based hyperspectral imaging (HSI) and machine learning (ML) techniques are applied for crop field data collection such as yield, nitrogen content, leaf chlorophyll, biomass estimation, leaf area index (LAI), and biotic and abiotic stress. It is very difficult to identify with certainty best practices for specific applications and for targeted crop species because the results are frequently contradictory; models or indices sometimes perform well, but other times they do not. ML and HSI are useful and sophisticated techniques, but treating them as first-option methods may be detrimental in the long term. Favoring HSI in situations where a multispectral sensor performs equally well only delays end-user adoption of technology owing to cost and complexity. The past few years have seen increased interest in unmanned aerial vehicle (UAV)-based hyperspectral imaging (HSI) and machine learning (ML) in agricultural research, concomitant with an increase in published research on these topics. We provide an updated review, written for agriculturalists, highlighting the benefits in the retrieval of biophysical parameters of crops via UAVs relative to less sophisticated options. We reviewed >70 recent papers and found few consistent results between similar studies. Owing to their high complexity and cost, especially when applied to crops of low value, the benefits of most of the research reviewed are difficult to explain. Future effort will be necessary to distill research findings into lower-cost options for end-users. [ABSTRACT FROM AUTHOR]

Barley is one of the most relevant crops worldwide and an essential component of agriculture in Europe in general, and in the Mediterranean region in particular. As cropping areas will hardly rise in the future, yield must be improved to enhance global crop production. Naturally, understanding how yield is affected by environmental and genetic factors in two- and six-rowed barley can help us to develop more efficient management and breeding strategies to increase current yield gains. We aimed to determine the relative importance of genetic and environmental factors on numerical and physiological components of GN for two- and six-rowed barley types. To generate a large and unbiased database, we compiled data of yield and its numerical and physiological components from crop-based experiments (i.e., excluding controlled-conditions experiments and/or approaches using isolated plants) reported in figures and tables in every single paper having the word "barley" in the title published over 25 years in four rigorous and prestigious international journals: Field Crop Research, European Journal of Agronomy, Crop Science and Crop and Pasture Science (formerly Australian Journal of Agricultural Research) between January 1996 and December 2021, both inclusive. Spike number (SN) was the most relevant numerical component explaining GN regardless of the source of variation. Regarding physiological components, it seemed that when the driving force was environmental factors, spike dry weight at flowering (SDW F) was more relevant than fruiting efficiency (FE); whilst when the differences were due to genotypic factors, clearly the FE was the component mostly responsible for the changes in GN. When the analysis was restricted to two- and six-rowed barley types, GN improvements were mainly explained by changes in SN for both two- and six-rowed barley types. However, when the physiological components were considered, the responsiveness of GN was more related to SDW F than to FE in two-rowed genotypes, while the opposite was true for the six-rowed type. In barley, SN always explained the responses of GN better than grain number per spike (GNS), regardless the source of variation and the type of barley. Respect to the physiological components, environmental factors affected GN mainly through affecting SDW F , while genotypic factors affected GN through affecting FE. SDW F and FE were more relevant for explaining changes in GN two- and six-rowed barleys, respectively. Breeders and agronomists can be aware that it will be more likely to achieve significant gains in yield through focusing more on SN than on GNS regardless of the barley type, whilst regarding the physiological components it would be more relevant to focus on SDW F in two-rowed barley, and on FE in six-rowed barley. • We quantified grain number components depending on source of variation in barley. • Spike number (SN) explaining grain number regardless of the source of variation. • Spike dry weight (SDW F) was the most relevant component for environment factor. • Fruiting efficiency was more relevant for genotypic factor. • Grain number was more related to SDW F in two-rowed, while FE in six-rowed type. [ABSTRACT FROM AUTHOR]

Abstract: Tillage might be unnecessary for crop production, but no practical mechanised system can avoid field traffic, usually by wheels. Wheels can cause soil damage, but this can be limited to a small proportion of field area by restricting all heavy wheels to permanent traffic lanes. Widespread adoption of controlled traffic in Australia, and permanent raised beds in Mexico has demonstrated the effectiveness and practicability of Controlled Traffic Farming (CTF) systems in very different cropping environments. This paper considers the system impact of wheel traffic on productivity and sustainability of mechanised cropping, citing comparisons between CTF and conventional “random traffic” cropping systems where possible. Evidence of the extent and effects of wheeling on soil structure is summarised in terms of hydrology and crop performance. Soil erosion and broader environmental effects are considered briefly. Tillage and traffic effects on greenhouse gas emissions from cropping are discussed, including emissions from fuel, herbicide and fertiliser inputs. Soil emissions are considered in some detail, citing evidence from soil compaction studies, and where emissions have been monitored from wheeled and non-wheeled soil. Outcomes have been encapsulated in a spreadsheet comparison of emissions from cropping systems using tillage with random traffic, no-till with random traffic and CTF no-till. Using data from extensive grain production systems in Australia this indicates that CTF could provide a major reduction in cropping emissions. CTF can improve productivity, and all measures of sustainability; it also overcomes some important constraints to the adoption of conservation agriculture. As precise guidance becomes progressively cheaper, machine system width compatibility remains the only major impediment to a significant improvement in food security and the environmental footprint of cropping. Width compatibility is simple in principle, but complex in practice, and will occur only with the active engagement of the farm machinery industry. The paper urges ISTRO to join with regional farmer CTF groups to draw attention to this issue and provide a forum for the development of compatibility standards. [Copyright &y& Elsevier]

Cultivated land productivity potential improvement (CLPPI) assessment is the fundamental basis to launch land consolidation, which is one of the most important way to increase the grain productive capacity. Previous studies on CLPPI assessment have focused on factors related to natural conditions of cultivated land, but they ignored the impacts of utilization conditions, including plot characteristics and agricultural infrastructure, which account for substantial CLPPI from land consolidation. Based on the crop-growth model and Agro-ecological Zoning (AEZ) methodology, this paper proposed a modified CLPPI assessment model to estimate the improvement of land productivity potential via land consolidation. Meanwhile, the contribute rates of different factors involved in determining the CLPPI were also analysed to reveal the ideal work focus and policy direction for land consolidation. Results showed that the calculated CLPPI values had obvious spatial variety in Shenyang, of which the average was 326.18. For the consolidation case, total crop production in Shenyang could be increased by as much as 149.89 × 107 kg, 20% of the current yield. CLPPI is the comprehensive outcome of both natural and utilization qualities of land use, and the current productivity potential of cultivated land in Shenyang relied much less on natural conditions such as soil than on utilization conditions such as agricultural infrastructure. In addition, medium-productivity lands were most appropriate target areas for the implication of land consolidation projects. Actually, the arrangement of land consolidation projects should not only consider CLPPI as in the past, but also add the theoretical productivity potential into consideration. Moreover, the realization of estimated CLPPI also calls for active changes of the whole land management system. An integrated institution for the full implementation of land consolidation, proper regulations and laws on the follow-up protection of cultivated land productivity potential, economic policies to stimulate the willingness of farmers, and a transfer mechanism for cultivated land are all needed policy changes. [ABSTRACT FROM AUTHOR]

Crop production not only creates economic values, but also has ecological functions. The carbon sink function of crops plays an important role in mitigating climate changes. This paper collected and analyzed the carbon cost data of staple crops in China, estimated the carbon sink and carbon source effects of farmlands, and quantitatively evaluated the carbon inputs and outputs of crop production systems. The results showed that the carbon footprints of crops in six typical agriculture regions were quite different, and the major crops production showed as carbon sinks in general. The carbon sequestration of different crops in the same region were significantly different, as well as the same crop in different regions. China’s farmland ecosystem showed carbon sequestration effect: the total annual net carbon sink of three major crops, rice, wheat, and corn, was about 165.76 TgC, of which rice was the highest, accounting for 48.71%. This study also proposed the key ways for energy conservation and emission reduction of crop production in every region, and suggested the technology direction for improving carbon sink function. This study provided important basis for policy formulation and planning about the low-carbon agriculture development in China. [ABSTRACT FROM AUTHOR]

In crop science, widely used theoretical concepts of production ecology comprise a hierarchy in growth defining, limiting, and reducing factors, which determine corresponding potential, limited, and actual production levels. These concepts give insight in theoretically achievable production, yield gaps, and yield gap mitigation. Concepts of production ecology have been demonstrated to be applicable to livestock science, but so far they have not been used quantitatively for livestock production. This paper aims to define theoretical concepts of production ecology for livestock systems in more detail, to express livestock production in suitable units, and to provide a framework to analyse production levels for livestock systems and combined crop–livestock systems. Growth defining (genotype and climate), growth limiting (feed quality and quantity), and growth reducing factors (diseases and stress) in livestock production are described analogous to the growth factors in crop production. Management practices, such as housing, feeding, culling, and slaughter are specified. From the perspective of a livestock system, production is expressed per animal, per unit of animal body mass, and per unit of feed intake, whereas from the perspective of a combined crop–livestock system, production is recommended to be expressed in kg livestock product ha − 1 year − 1 . The quantitative framework is illustrated for Charolais cattle ( Bos taurus subsp.) in two beef production systems in France, differing in feeding strategies. System A produces heavier calves than system B, whereas cattle in system B are fed a higher fraction of concentrates in the diet compared with system A. Potential beef production was similar for systems A and B, and estimated to be 152 kg beef animal − 1 year − 1 and 251 g beef kg − 1 live weight year − 1 , while there was a minor difference when expressed per unit of feed intake (54.5 vs 54.8 g beef kg − 1 DM). Actual production was lower for system A than for system B (24.9 vs 31.2 g beef kg − 1 DM). Potential production for combined crop–livestock systems was again similar for systems A and B (631 vs 634 kg beef ha − 1 year − 1 ), while actual production was much lower for system A than for system B (133 vs 180 kg beef ha − 1 year − 1 ). The yield gap for crop–livestock systems was 79% of potential production for system A and 72% for system B. We conclude that the framework is effective to reveal the scope to increase production and resource use efficiency in livestock production. [ABSTRACT FROM AUTHOR]

Most of the required increases in food production over the next decades are expected to be achieved through increases in crop yield. As wheat is essential for food security it is worrying that its yield gains over the last two decades were small. To achieve further yield increases it is critical to continue increasing number of grains per unit area (GN m-2), the trait best related to yield. In this context, it is relevant to identify the main determinants of GN m-2 in response to genetic and environmental factors as well as the trade-offs between them. In the present study we compiled a large database across the literature to analyse the relative importance of components when affected by genetic or environmental factors, producing small or large changes in GN m-2 and its components, either numerical (the number of spikes per m2, SN m-2; and the number of grains per spike, GN spike-1) or physiological (spike dry weight at anthesis, SDWa; and fruiting efficiency, FE) determinants. The database included 367 papers published in: (i) Field Crop Research (FCR), (ii) European Journal of Agronomy (EJA), (iii) Crop Science (CS) and (iv) Crop and Pasture Science (CPS, formerly Australian Journal of Agricultural Research) between 1990 and 2020. The complete dataset was split into classes, depending on the source of experimental variation, environment or genotype and was normalised to remove the differences between experiments and determine the environmental and genotypic effects within each experiment. Normalised data showed that the responsiveness of GN m-2 was similarly explained by changes in both SN m-2 and GN spike-1, but in terms of physiological components SDWa was more relevant than FE for explaining the variations in GN m-2. Considering the numerical components of GN m-2 genotypic and environmental factors modified more GN spike-1 than in SN m-2. On the other hand, physiological components were differently modified by genotype and environment: for genotypic effects FE was more critical than SDWa and the other way around for environmental factors. A trade-off between numerical and physiological components was observed although was greater between physiological than between numerical components. • We quantified physiological/numerical components (and trade-offs) of grains/m-2 in wheat. • We recognised differences depending on magnitude and source of variation (genetic/environmental). • Grains/spike-1 explained better grains/m-2 than spikes/m-2, particularly for genotypes. • Genotypes affected more fruiting efficiency than spike-dry-weight-at-anthesis, environments the opposite. • Trade-offs seemed more relevant for physiological than for numerical components. [ABSTRACT FROM AUTHOR]

Abstract: Crop growth simulation models are a useful tool to assess the impact of environment, crop management, genetics and breeding strategies, as well as climate change and variability on growth and yield. Any crop science experiment that measures key physiological processes, tests these productive processes, their interaction with other processes, environment, and intra- and inter-specific variation, is valuable to inform and refine crop simulation models. This paper focuses on crop science experiments in three key areas—crop development, seed or fruit-set at high temperature, and water use—illustrating some of the experiments used to understand key processes and, equally importantly, quantify these processes for crop models in a robust and repeatable manner. One particularly useful experimental method for determining stages of development responsive to photoperiod and temperature (the main drivers of ontogenic development), and sensitive to abiotic stresses such as temperature extremes and water deficit, is transfer experiments between different environments or treatments. Once sensitive stages are defined, then responses and genotypic differences can be accurately quantified. Understanding and modeling transpiration, and particularly genotypic differences in processes affecting transpiration is also key process for crop modeling. Experiments to determine genotypic differences in soil water availability thresholds that control when transpiration is reduced, relations between transpiration and vapor pressure deficit (VPD), and patterns of soil water uptake are also described along with new insights from this work. One of the biggest constraints to improving models with crop science experiments—and exploiting advances in genomics—is the limited capacity to phenotype traits and physiological mechanisms. Most crop science experiments have quantified responses in only a limited number of genotypes and the diversity of genotypic responses is not well represented. Today there is an increased demand for good quality phenotyping which can serve both genomics and modeling, and there is an urgent need to re-invest in crop physiology for high quality phenotyping. [Copyright &y& Elsevier]

Abstract: Brassinosteroids (BRs) are steroid hormones that participate in multiple biological processes. In this paper, we characterized a classic rice mutant Fn189 (dwarf54, d54) showing semi-dwarf stature and erect leaves. The coleoptile elongation and root growth was less affected in Fn189 than wild-type plant by the exogenous application of eBL, the most active form of BRs. Lamina joint inclination assay and morphological analysis in darkness further showed that Fn189 mutant plant was insensitive to exogenous eBL. Through map-based cloning, Fn189 was found to be a novel allelic mutant of the DWARF 61 (D61) gene, which encodes the putative BRs receptor OsBRI1. A single base mutation caused the I834F substitution in the OsBRI1 kinase domain. Consequently, kinase activity of OsBRI1 was found to decrease dramatically. Taken together, the kinase activity of OsBRI1 is essential for brassinosteroids to regulate normal plant growth and development in rice. [Copyright &y& Elsevier]

Abstract: In this century climate change is assumed to be the major driver for changes in agricultural systems and crop productivity at the global scale. However, due to spatial differences in cropping systems and in the magnitude of climatic change regional variations of climate change impact are expected. Furthermore, the recent climate projections are highly uncertain for large parts of West Africa. In particular with respect to annual precipitation and variability the projections vary between trends with decreasing precipitation and trends with slightly increasing precipitation within the next decades. On the other hand, the extensive fallow systems in this region suffer from increasing population pressure, which compromises soil fertility restoration. In the Republic of Benin, the demographic projections for the first half of this century indicate a continuous growth of the population with a narrow interval of confidence. Thus, in the absence of an adequate soil fertility management with judicious use of mineral fertilizers, the soil degradation process with decreasing crop yields is expected to continue. The objective of this paper was, therefore, to quantify the regional effect of future population growth on crop yields in West Africa and to compare it with the potential effects of climate change scenarios. Three land use scenarios (L1, L2 and L3) for the Upper Ouémé catchment where derived from different demographic projections combined with assumptions regarding future road networks and legal frameworks for forest protection using the CLUE-S modeling approach. The fallow-cropland ratio decreased in the three scenarios from 0.87 in the year 2000 to 0.66, 0.48 and 0.68 for L1, L2 and L3, respectively in 2050. Based on the projected ratio of fallow and cropland, trends of maize yield for the three land use scenarios were calculated using the EPIC (Environmental Policy Integrated Climate) model coupled with a spatial database. Maize yields followed the decreasing trend of the fallow-cropland ratio and estimated yield reductions amounted to up to 24% in the period 2021–2050. This trend was compared with the impact of the SRES climate scenarios A1B and B1 based on the output of the GCM ECHAM5 downscaled with the REMO model and the A1B scenario output of the GCM HADC3Q0 downscaled with the RCMs SMHIRCA and HADRM3P. The yield reductions due to the projected climate change in the three models accounted for a yield decrease of up to 18% (REMO A1B scenario) in the same period. Taking into account the smaller uncertainties in the scenario assumptions and in the model output of the land use scenarios, it is concluded that, in low input fallow systems in West Africa, land use effects will be at least as important as climate effects within the next decades. [Copyright &y& Elsevier]

Abstract: Characterizing the carbon footprint (CF) of agricultural production offers key information for pursuing low carbon agriculture and food consumption. While China has long strived for increasing food production capacity for its large and still growing population, the high emissions cost, especially from the over use of agro-chemicals, has been widely debated for the last decade. However, the CF of China''s crop production has not yet been assessed. This paper reports a basic estimate of CF of crop production using national statistical data available for the period of 1993–2007. The dataset includes the amount of individual agricultural inputs (fertilizer, pesticide, diesel, plastic film, etc.), cultivation area and total of production whole crops. Using the emission factors estimated for China''s agricultural features and available abroad, the mean overall CF of China''s crop production was estimated to be 0.78±0.08tCEha−1 yr−1 and 0.11±0.01tCEt−1 yr−1, for land use and bulk production respectively. For the duration the data covered, the carbon intensity under cultivation land use was seen to increase since 1993. Among the total, fertilizer induced emissions exerted the largest contribution of ∼60%, being 0.45±0.04tCE per ha and 0.07±0.01tCE per ton of production, on average. Compared to the UK, the estimated overall CF of China''s crop production was higher in terms of cultivation land use. While there was a significant positive correlation of carbon intensity with total production, carbon efficiency was shown in a decreasing trend during 2003-2007. Therefore, low carbon agriculture should be pursued, and the priority should be given to reducing fertilizer application in agriculture of China. However, for developing best management practices for climate change mitigation in crop production of China, further studies of crop and regional specific CFs and the variation with climate conditions and agricultural managements are needed. [Copyright &y& Elsevier]

Abstract: The application of mobile devices to the food and agriculture sector has been increased notably in the last years, being most of these devices endowed with Global Positioning System by satellites (GPS). This paper presents a new software application developed with LabVIEW for determining extraterrestrial solar radiation, equivalent evaporation and other parameters related to solar position from Global Position Data in handheld devices. These parameters are useful in many applications, such as validating the data supplied by agricultural weather stations, estimating the water needs of the crops where there are no close weather stations, or providing essential information when considering a determined place for installing photovoltaic panels or solar water heating systems. There is currently no software in the market which confers this utility to a mobile device. A comparison between data calculated by the proposed application and data supplied by an agricultural weather station was carried out for evaluation and validation purposes. [Copyright &y& Elsevier]

Abstract: We examine the potential global risk of increasing surface ozone (O3) exposure to three key staple crops (soybean, maize, and wheat) in the near future (year 2030) according to two trajectories of O3 pollution: the Intergovernmental Panel on Climate Change Special Report on Emissions Scenarios (IPCC SRES) A2 and B1 storylines, which represent upper- and lower-boundary projections, respectively, of most O3 precursor emissions in 2030. We use simulated hourly O3 concentrations from the Model for Ozone and Related Chemical Tracers version 2.4 (MOZART-2), satellite-derived datasets of agricultural production, and field-based concentration:response relationships to calculate crop yield reductions resulting from O3 exposure. We then calculate the associated crop production losses and their economic value. We compare our results to the estimated impact of O3 on global agriculture in the year 2000, which we assessed in our companion paper [Avnery et al., 2011]. In the A2 scenario we find global year 2030 yield loss of wheat due to O3 exposure ranges from 5.4 to 26% (a further reduction in yield of +1.5–10% from year 2000 values), 15–19% for soybean (reduction of +0.9–11%), and 4.4–8.7% for maize (reduction of +2.1–3.2%) depending on the metric used, with total global agricultural losses worth $17–35 billion USD2000 annually (an increase of +$6–17 billion in losses from 2000). Under the B1 scenario, we project less severe but still substantial reductions in yields in 2030: 4.0–17% for wheat (a further decrease in yield of +0.1–1.8% from 2000), 9.5–15% for soybean (decrease of +0.7–1.0%), and 2.5–6.0% for maize (decrease of + 0.3–0.5%), with total losses worth $12–21 billion annually (an increase of +$1–3 billion in losses from 2000). Because our analysis uses crop data from the year 2000, which likely underestimates agricultural production in 2030 due to the need to feed a population increasing from approximately 6 to 8 billion people between 2000 and 2030, our calculations of crop production and economic losses are highly conservative. Our results suggest that O3 pollution poses a growing threat to global food security even under an optimistic scenario of future ozone precursor emissions. Further efforts to reduce surface O3 concentrations thus provide an excellent opportunity to increase global grain yields without the environmental degradation associated with additional fertilizer application or land cultivation. [Copyright &y& Elsevier]

Abstract: Precision farming relies on diverse sensor techniques to collect site-specific information at field scale. To comprehend and interpret miscellaneous information referring to each specific soil, crop and weather conditions, different case studies are needed. This paper presents two case studies. A horizontal dielectric penetrometer, an EM38 (Geonics Ltd., Canada) and a yield sensor (RDS Technology Ltd., UK) were used. Several parameters, volumetric soil water content (VSWC), penetration resistance (PR), apparent electrical conductivity (ECa) and crop yield, were investigated. A case study (20ha, Warleberg Farm, Kiel, Germany; crops: rapeseed (Brassica napus L.) in 2007/2008, winter wheat (Triticum aestivum L.) in 2008/2009) indicated that VSWC maps at a depth of 20cm conformed to both ECa maps and yield maps over two years. Another case (7.7ha, Dikopshof Experimental Farm, Bonn, Germany; crops: winter wheat (T. aestivum L.) in 2007/2008, winter barley (Hordeum vulgare L.) in 2008/2009) had similar results except a yield map of 2009. For soil strength distribution at the depth of 20cm, a PR map at Warleberg Farm generally agreed to other maps (VSWC, ECa and yield), whereas the PR map from Dikopshof Experimental Farm only partly agreed to those. In brevity, this study concludes: (i) an assessment for the availability of the horizontal dielectric penetrometer applied at field scale; (ii) ECa pattern measured by EM38 can be viewed as a fingerprint within a field for predicting the distribution of soil water content and crop yield; (iii) PR pattern on top layer is relatively difficult to interpret than ECa pattern. [Copyright &y& Elsevier]

Abstract: Soil degradation and the high cost of inorganic fertilizers have contributed to reduced crop yields and farm incomes which has further exacerbated poverty among farming households. The adoption of human excreta as nutrient and organic matter source in crop production is investigated. The paper examines cultural attitude and farmers’ perception on its use. It also identifies the factors that influence its use, its economic benefits and the constraints. A stratified random sampling of farmers was employed in Manya Krobo district of Ghana, where excreta – specifically faecal sludge from unsewered public toilets 15 and septic tanks, is used in crop production. The data were analyzed through the use of descriptive statistics, budgetary analysis and the probit model. The result showed that there are no cultural and religious barriers to the use of excreta in crop cultivation. Farmers attested to the agronomic benefits of excreta, users of excreta make three times the net income of non-users. They attested that the use of excreta when treated does not contaminate crops. It is recommended that the use of excreta should be supported by making it available in the required quantity and quality. In addition, farmers need to be educated on precautionary measures to avoid health hazard. [ABSTRACT FROM AUTHOR]

Summary: This paper examines the agricultural science needs of small farms. The green revolution successfully negotiated two tightropes: agricultural productivity increases were larger than the fall in prices that resulted from producing more food; and output per hectare rose faster than output per worker, thus increasing the demand for labor. The current challenge is to generate technology that helps poor farmers in low potential areas. Since research capacity is increasingly private, incentives to produce the needed technology are needed, perhaps through contracts to produce varieties with specific characteristics. Development of seeds needs complementary work on water, for which economists, plant scientists, and engineers need to pool their skills. [ABSTRACT FROM AUTHOR]

Abstract: With the advances in electronic and information technologies, various sensing systems have been developed for specialty crop production around the world. Accurate information concerning the spatial variability within fields is very important for precision farming of specialty crops. However, this variability is affected by a variety of factors, including crop yield, soil properties and nutrients, crop nutrients, crop canopy volume and biomass, water content, and pest conditions (disease, weeds, and insects). These factors can be measured using diverse types of sensors and instruments such as field-based electronic sensors, spectroradiometers, machine vision, airborne multispectral and hyperspectral remote sensing, satellite imagery, thermal imaging, RFID, and machine olfaction system, among others. Sensing techniques for crop biomass detection, weed detection, soil properties and nutrients are most advanced and can provide the data required for site specific management. On the other hand, sensing techniques for diseases detection and characterization, as well as crop water status, are based on more complex interaction between plant and sensor, making them more difficult to implement in the field scale and more complex to interpret. This paper presents a review of these sensing technologies and discusses how they are used for precision agriculture and crop management, especially for specialty crops. Some of the challenges and considerations on the use of these sensors and technologies for specialty crop production are also discussed. [ABSTRACT FROM AUTHOR]

Abstract: The compaction of cultivated soils by agricultural machines considerably affects both the structure and physical properties of soil, thus having a major impact on crop production and the environment. Soil mechanical resistance is highly variable both in time and space because it depends on soil texture, soil porosity and soil water state (matric suction). This paper is devoted to the effect of soil matric suction on the compression index C c, which is one of the mechanical parameters that describes the soil mechanical resistance to compression. We performed oedometer compression tests to study the compression index of a loamy soil and a sandy clay, with matric suction control, by using the osmotic technique. Soil samples were prepared by compacting soil passed through a 2mm sieve at dry bulk densities of 1.1 and 1.45Mgm− 3. The mechanical stress and matric suction ranges considered corresponded to field condition, with vertical stress less than 800kPa and matric suction less than 200kPa. The results show that the compression index C c was constant or changed little with matric suctions for the two soils at different initial densities. For the loamy soil, the average compression index C c equals 0.73 for an initial bulk density of 1.1Mgm− 3 and 0.41 for 1.45Mgm− 3 for matric suction higher than 20kPa. For the sandy clay, the average compression index C c is 0.35. From a practical point of view, our study shows that the mathematical determination of mechanical parameters should be standardized due to the S-shaped compression curves that may significantly impact the compression index estimation. The observation of constant compression index with matric suction is a useful result for modelling soil strain due to traffic and predicting the compaction of cultivated soils. [Copyright &y& Elsevier]

Abstract: The 2004 Indian Ocean tsunami inundated about 37,500ha of coastal farmland in Aceh, and crops planted after the tsunami were severely affected by soil salinity. This paper describes the changes of soil salinity over time on tsunami affected farms and the implications for resuming crop production after natural disasters. Soil salinity and salt leaching processes were assessed across the tsunami affected region by measuring soil apparent electrical conductivity (ECa) using an electromagnetic induction soil conductivity instrument (EM38) combined with limited soil analysis. The ECa was measured 5 times between August 2005 and December 2007 in both the vertical (EMv) and horizontal (EMh) dipole orientations at 23 sites across Aceh. The level of salinity and direction of salt movement were assessed by comparing changes in mean profile ECa and relative changes in EMv and EMh. Eight months after the tsunami the average soil salinity in the 0–1.2m soil depth varied from ECe 22.6 to 1.6dSm−1 across sites in the affected region and three years after the tsunami it varied from 13.0 to 1.4dSm−1. Soil salinity tended to be higher in rice paddy areas that trapped saline tsunami sediments and held seawater for longer periods. Leaching of salts occurred slowly by both vertical displacement and horizontal movement in surface waters. Hence, soil salinity persisted at a level which could reduce crop production for several years after the 2004 tsunami. High soil salinity persisted three years after the tsunami even though there had been more than 3000–7000mm of accumulated rainfall to leach salts. The slow leaching is likely to have been due to the loss of functional drainage systems and general low relief of the affected areas. Monitoring of soil salinity with EM38 assisted local agricultural extension agencies to identify sites that were too saline for crops and determine when they were suitable for cropping again. The methodology used in this study could be used after similar disasters where coastal agriculture areas become inundated by seawater from storm surges or future tsunamis. [Copyright &y& Elsevier]

Abstract: Oil palm is a significant and developing crop in many developing countries. The introduction of oil palm puts pressure on natural resources because it is often planted in cleared-cut land that previously supported other crops or was forested. This has led to environmental concerns which require attention. Hence it is important that new plantations are managed in a sustainable way to reduce the impact of oil palm cultivation on ecosystems whilst maximising yield and productivity to farmers. The application of arbuscular mycorrhizal fungi (AMF) technology is one option that can benefit both agronomic plant health and ecosystems. AMF have the potential to increase conventional agricultural productivity and are crucial for the sustainable functioning of agricultural ecosystems. This paper provides an insight into how AMF application might benefit oil palm cultivation through more sustainable management and the practical use of AMF for oil palm plantations. [Copyright &y& Elsevier]

This paper presents a computational method of forecasting based on high-order fuzzy time series. The developed computational method provides a better approach to overcome the drawback of existing high-order fuzzy time series models. Its simplicity lies with the use of differences in consecutive values of various orders as forecasting parameter and a w-step fuzzy predictor in place of complicated computations of fuzzy logical relations. The objective of the present study is to examine the suitability of various high-order fuzzy time series models in forecasting. The general suitability of the developed method has been tested by implementing it in the forecasting of student enrollments of the University of Alabama and in the forecasting of crop (Lahi) production, a case of high uncertainty in time series data. The results obtained have been compared in terms of average error of forecast to show superiority of the proposed model. [Copyright &y& Elsevier]

Abstract: This paper presents a survey of the empirical literature on the effects of climate change and weather conditions on the transport sector. Despite mixed evidence on many issues, several patterns can be observed. On a global scale especially shifts in tourism and agricultural production due to increased temperatures may lead to shifts in passenger and freight transport. The predicted rise in sea levels and the associated increase in frequency and intensity of storm surges and flooding incidences may furthermore be some of the most worrying consequences of climate change, especially for coastal areas. Climate change related shifts in weather patterns might also cause infrastructure disruptions. Clear patterns are that precipitation affects road safety by increasing accident frequency but decreasing severity. Precipitation also increases congestion, especially during peak hours. Furthermore, an increased frequency of low water levels may considerably increase costs of inland waterway transport. Despite these insights, the net impact of climate change on generalised costs of the various transport modes are uncertain and ambiguous, with a possible exception for inland waterway transport. [Copyright &y& Elsevier]

Crop yield is a key element in rural development and an indicator of national food security. A method that could estimate crop yield over large hilly areas would be highly desirable. Methods including high spatial resolution satellite imagery have the potential to achieve this objective. This paper describes a method of integrating QuickBird imagery with a production efficiency model (PEM) to estimate crop yield in Zhonglianchuan, a hilly area on Loess Plateau, China. In the PEM model, crop yield is a function of the photosynthetic active radiation (PAR), fraction of absorbed photosynthetically active radiation (fAPAR) and light-use efficiency (LUE). Based on the high spatial resolution QuickBird imagery, a land cover classification is used to attribute a class-specific LUE. The fAPAR is related to spectral vegetation indices (SVI), which can be derived from the satellite images. The LUE, fAPAR and incident PAR data were combined to estimate the crop yield. Farmer-reported crop yield data in 80 representative plots were used to validate the model output. The results indicated QuickBird imagery can improve the accuracy of predicted results relative to the Landsat TM image. The predicted yield approximated well with the data reported by the farmers (r 2 =0.86; n =80). The spatial distributions of crop yield derived here also offers valuable information to manage agricultural production and understand ecosystem functioning. [Copyright &y& Elsevier]

Abstract: Recent research on crop-water relations has increasingly been directed towards the application of locally acquired knowledge to answering the questions raised on larger scales. However, the application of the local results to larger scales is often questionable. This paper presents a GIS-based tool, or a GEPIC model, to estimate crop water productivity (CWP) on the land surface with spatial resolution of 30arc-min. The GEPIC model can estimate CWP on a large-scale by considering the local variations in climate, soil and management conditions. The results show a non-linear relationship between virtual water content (or the inverse of CWP) and crop yield. The simulated CWP values are generally more sensitive to three parameters, i.e. potential harvest index for a crop under ideal growing conditions (HI), biomass-energy ratio indicating the energy conversion to biomass (WA), and potential heat unit accumulation from emergence to maturity (PHU), than other parameters. The GEPIC model is a useful tool to study crop-water relations on large scales with high spatial resolution; hence, it can be used to support large-scale decision making in water management and crop production. [Copyright &y& Elsevier]

Abstract: The quantity of water available for irrigation is getting scarce in many countries and it assumes great importance for assured crop production, especially in view of the erratic behavior of the monsoon. Thus, there is a pressing need to improve the water efficiency of irrigation systems. One-way of improving the efficiency of the irrigation system is reusing the return flow from the irrigation system. This task requires quantification of return flow, which still remains as a grey area in irrigation water management. The estimation of return flow from the irrigation system is usually obtained using thumb rules depending upon the site-specific conditions like command area conditions and soil properties. In this paper, a hierarchical modeling technique, namely, regression tree is developed for return flow estimation. Regression tree is built through binary recursive partitioning. The effective rainfall, inflow, consumptive water demand, and percolation loss are taken as predictor variables and return flow is treated as the target variable. The applicability of the hierarchical model is demonstrated through a case study of Periyar–Vaigai Irrigation System in Tamil Nadu, India. The model performance shows a good match between the simulated and the field measured return flow values. Results of statistical analysis indicated that the correlation coefficients are high for both single as well as double crop seasons. [Copyright &y& Elsevier]

An extensive knowledge of the temporal variability of soil fertility parameters and how this variation affects the environment is imperative to a wide range of disciplines within agricultural science for optimal crop production and ecosystem preservation. This paper examines the temporal variability of soil pH, organic matter (OM), cation exchange capacity (CEC), total nitrogen (TN), total phosphorus (TP), available phosphorus (PAv), and available potassium (KAv) on Cambosols (Entisols) (n =179) and Anthrosols (Inceptisols) (n =95) in Zhangjiagang County, China from 1980 to 2004. Nutrient input was monitored from 1983 to 2004. Annual N fertilizer rates were significantly different during three periods (1983–1989, 1989–1999, 1999–2004), where annual rates increased significantly after 1989 and then decreased after 1999. Annual P fertilizer rates were significantly different during two periods (1983–1993, 1993–2004) where annual rates increased after 1993. No change was found in K fertilizer rates. Soil pH marginally increased by 0.14 units in Cambosols, but significantly decreased by 1.02 units in Anthrosols. OM, CEC, and TN increased in both soil orders an average of 2.15gkg−1, 1.6cmolkg−1, and 0.21gkg−1, respectively. TP decreased in Anthrosols by 70mgkg−1, PAv increased in Cambosols by 4.83mgkg−1, and KAv decreased in Cambosols by 15mgkg−1. Fertilizer input rates are causing nutrient imbalances, contributing to acidification in Anthrosols, and decreasing C/N ratios. Nutrient loading of N and deficiency of K is also a potential problem in the area. Efforts should be made to readjust soil nutrient inputs to reach an optimal, sustainable level. [Copyright &y& Elsevier]

Abstract: Increases in crop production per unit of water used is imperative for supplying adequate food, feed, and fiber in an environment where future water supplies are expected to decrease. Previous work on crop productivity per unit of water used (water use efficiency; WUE) has primarily dealt with crops grown under water limited conditions and have usually not considered crop management factors other than irrigation. Crop management can strongly influence yields when water is not limited. The aim of this paper is to demonstrate that transpiration per unit of productivity can vary greatly with agronomic management of crops when soil water supply is adequate or fixed. Moreover, when yield from crops with common development patterns are increased by better crop management and improved cultivars, WUE is also increased. In recent decades high yields of maize have been accomplished with increased fertilizer and cultivars that tolerate high plant populations and uniform spacing. Although transpiration and soil evaporation (ET) occur simultaneously in the field, they are difficult to measure as separate components. However, the crop simulation model CERES maize can reasonably estimate each component. The CERES Maize model was used to assess how plant population, genetic type and weather influence yields and WUE. Simulated yield response of an old and modern hybrid to a wide range of plant densities and uniformity patterns agreed reasonably well with observations suggesting that plant densities need to be near 10–11plantm−2 and uniformly spaced to obtain near maximum yield and WUE for Midwest USA climate. [Copyright &y& Elsevier]

Abstract: It is increasingly argued that we are entering into a “biotech century”, in which biotechnology promises major advances in agricultural productivity. The development of biotechnology is not a straightforward affair, however, and the advent of GMOs has led to public protest and consumer resistance. This paper draws upon a comparative Australian–UK project concerned with the role of regulation and governance in mediating the debates and managing the associated risks. Regulatory responses and the mediation of conflicts by the Australian and UK governments have been shaped by the institutional and policy environments in these two countries. The implications of these public debates and regulatory responses for the capture of competitive opportunities are considered. The fact that the two countries have broadly similar systems of governance and regulation reveals how alike the circumstances are in many respects. But at the same time there are important differences in both the style and the content of the policy debates. In both the UK and Australia, the respective central governments remain committed to a ‘biotechnology future’. Against this background, there is little doubt that the choices about biotechnology will play a defining role in shaping the future of rural places. [Copyright &y& Elsevier]

Globally there have been a number of concerns about the development of genetically modified crops many of which relate to the implications of gene flow at various levels. In Europe these concerns have led the European Union (EU) to promote the concept of ‘coexistence’ to allow the freedom to plant conventional and genetically modified (GM) varieties but to minimise the presence of transgenic material within conventional crops. Should a premium for non-GM varieties emerge on the market, the presence of transgenes would generate a ‘negative externality’ to conventional growers. The establishment of maximum tolerance level for the adventitious presence of GM material in conventional crops produces a threshold effect in the external costs. The existing literature suggests that apart from the biological characteristics of the plant under consideration (e.g. self-pollination rates, entomophilous species, anemophilous species, etc.), gene flow at the landscape level is affected by the relative size of the source and sink populations and the spatial arrangement of the fields in the landscape. In this paper, we take genetically modified herbicide tolerant oilseed rape (GM HT OSR) as a model crop. Starting from an individual pollen dispersal function, we develop a spatially explicit numerical model in order to assess the effect of the size of the source/sink populations and the degree of spatial aggregation on the extent of gene flow into conventional OSR varieties under two alternative settings. We find that when the transgene presence in conventional produce is detected at the field level, the external cost will increase with the size of the source area and with the level of spatial disaggregation. On the other hand when the transgene presence is averaged among all conventional fields in the landscape (e.g. because of grain mixing before detection), the external cost will only depend on the relative size of the source area. The model could readily be incorporated into an economic evaluation of policies to regulate adoption of GM HT OSR. [Copyright &y& Elsevier]

Abstract: Bioregenerative life support systems (BLSS) with different coefficients of closure are considered. The 66.2% coefficient of closure achieved in “BIOS-3” facility experiments has been taken as a base value. The increase in coefficient of closure up to 72.6–93.0% is planned due to use of soil-like substrate (SLS) and concentrating of urine. Food values were estimated both in a base variant (“BIOS-3”), and with increases in the coefficient of closure. It is shown that food requirements will be more fully satisfied by internal crop production with an increase in the coefficient of closure of the BLSS. Changes of massflow rates on an ‘input–output’ and inside BLSS are considered. Equations of synthesis and degradation of organic substances in BLSS were examined using a stoichiometric model. The paper shows that at incomplete closure of BLSS containing SLS there is a problem of nitrogen balancing. To compensate for the removal of nitrogen from the system in urine and feces, it is necessary to introduce food and a nitrogen-containing additive. [Copyright &y& Elsevier]

As systems intensify, crops and livestock become increasingly integrated. Forage from crops becomes a larger component of overall forage supply in small-scale systems. This paper integrates information from field trials, studying the effect of varying maize planting density, with modelling approaches to compare this with supplementation of maize stover, genetic improvement of stover digestibility and replacement of the maize crop with planted forage in east and southern Africa. Aggregate analyses for small-scale intensive (SSI) systems producing milk were carried out using a suite of models including CERES, CROPGRO, DRASTIC and ANORAC, scaling-up to regional level using GIS information. Increasing planting density increased the yield of thinnings, but decreased grain and stover yields. Model predictions of milk production from the thinnings and stover produced from one hectare of maize indicated that economic benefits to increased planting density could be achieved when the grain:milk price ratio was low, despite the negative effect on grain yield. Supplementation showed the greatest economic returns with small positive impacts on soil fertility and maize production. Replacing maize with planted forage inevitably increased milk at the expense of maize production. Again, for this intervention, grain:milk price ratios ranging from 0.19 to 2.88 across sub-Saharan Africa are likely to influence the decision of the farmer whether or not to trade milk for grain. Genetic enhancement of the digestibility of maize stover was found to have little impact on milk production because diets based on stover were deficient in nitrogen, preventing animals from benefiting from the increased energy supply resulting from digestibility increases. Other factors such as market access and stability, as well as individual objectives such as cash flow, food security and risk minimisation, were not explored in the present study but will influence household decisions. More complex analyses, accounting for these factors, may be required to predict adoption behaviour, however, the results of the study can be used to evaluate the potential returns to investment in research in the different areas using an economic surplus model. [Copyright &y& Elsevier]

In examining the global food supply and demand, the balance of research has favored analysis of the prospects for increased crop production, at the expense of examination of the potential for reducing the production requirements by increases in efficiency and productivity, or by shifts in diets. This has implied that there is a lack of coherent evaluations of efficiency and diet as options for keeping down the long-term production requirements for crops and other food phytomass. This paper presents estimates of current efficiency and phytomass appropriation of major food commodities, performed by modeling all principal flows of biomass in the food system. Estimated overall efficiencies varied from 0.35% for beef cattle meat, to 31% for starchy root tubers (global averages, gross energy basis). The results indicate that there is a most substantial potential for efficiency improvements within the animal food sector, particularly for ruminant systems in non-industrialized regions. It is also concluded that a considerable reduction of the phytomass production might be achieved by shifts in diet, even if assuming no changes with respect to the total share of meat in the diet. [Copyright &y& Elsevier]

This paper describes a study of the influence of the extraction system, crop season and production area on the chemical composition and quality of Cornicabra virgin olive oils (n=152) from five successive crop seasons (from 1994/1995 to 1998/1999). Analysis of the effect of the extraction system (dual-phase, triple-phase decanters and pressure) on the values of analytical determinations, revealed statistically significant differences (P⩽0.05) in a few parameters only, mainly in antioxidant content (total phenols and α-tocopherol) and oxidative stability. All quality indices and major fatty acid and sterol compositions presented significant statistical differences (P⩽0.001) with respect to the year of production, with the exception of total phenols. The crop season is therefore a critical variable, since the chemical composition of the olive oil may vary considerably from one year to the next. Many of the analytical parameters varied among the five production areas considered, in the provinces of Toledo and Ciudad Real. The results appear to confirm the general consensus on the quality of Cornicabra virgin olive oils from Castilla-La Mancha, namely that oils from mills located in the south and southeast of the province of Toledo are generally of higher quality. [Copyright &y& Elsevier]

Despite the fact that soil erosion by water causes considerable on-site and off-site problems, farmers in Europe are reluctant to adopt prevention and control measures when such measures require additional labour and material inputs. This paper documents the impact of multiple sowing of small grains on concentrated flow erosion rates and grain production for a winter triticale field (X Triticosecale Wittmack ex. A. Camus) in the Belgian loess belt. Multiple sowing refers to drilling more than once in zones of concentrated flow erosion in order to increase the total root mass in this zone. Multiple sowing strongly altered the morphology of erosion channels and reduced soil loss significantly. Statistical analysis confirmed that differences in channel dimensions could be explained by the seedling density. Doubling the root mass in the topsoil by multiple sowing, resulted on average in a reduction of soil loss by 42% for the whole growing season. For the winter period, soil loss reduction, mainly attributed to the triticale roots, amounted even to 53%, showing the tremendous impact of seedling roots on soil erosion by concentrated overland flow in the early stages of vegetation growth. Furthermore, total grain yield in the multiple drilled zones was not significantly smaller compared to the conventionally drilled parts of the field. Grain size of cereals was slightly smaller. The results of this case study indicate that double sowing in concentrated overland flow zones may be a viable soil erosion control technique. [Copyright &y& Elsevier]

Innovation is central to the strategic orientations of many agronomic research institutes. Little attention has been paid, however, to the links between knowledge production and design processes, defined as processes resulting in the creation of new objects in pursuit of specific goals. Our aim was to analyze the conditions and specificities of the production of scientific knowledge on agro-ecosystems through design processes. Drawing on design theory, we carried out a cross-analysis of nine research projects that included design processes and produced innovative objects (for example blending rules for variety mixtures in low-input crop management routes). These projects were managed by researchers from a range of disciplines (agronomists, geneticists, crop physiologists, and ecologists), and varied in their duration (from three to 15 years) and scale (from plot to landscape). We combined semi-structured interviews with these researchers and the analysis of various documents (scientific papers, PhD theses, technical publications, and research projects or reports). Our findings show that in all case studies, original and general scientific knowledge on agro-ecosystem functioning was produced at various stages throughout the design processes. The originality of this knowledge lies with the new representations that emerged, either of the agro-ecosystem processes at stake, or of farmers' practices. We show that these representations were formed gradually, through successive iterations of both refined formulations of the design target and new knowledge produced, required for its design. Finally, our results highlight the role of confrontation with real-life situations (particularly through agronomic diagnosis or experiments) in the evolution of these representations. Engaging in design processes can thus be seen as a research practice that leads to the production of original knowledge, allowing for a greater diversity of actors' ways of knowing to be taken into account. • In nine agricultural research projects studied, design processes led to the production of scientific knowledge. • The knowledge produced through design processes partly contrasted with dominant knowledge in the scientific field. • The design targets, the representations of agro-ecosystems, and the targeted knowledge have evolved together. • We revealed three types of drivers for such co-evolutions, pertaining to various diagnosis and experimentation practices. [ABSTRACT FROM AUTHOR]

Much has been published on the application of genetically modified (GM) crops in Africa, but agricultural performance has hardly been addressed. This paper discusses the main consequences of GM crops on agricultural performance in Ethiopia. Three main criteria of performance – productivity, equitability and sustainability – are evaluated in the context of the Ethiopian agricultural sector. We conclude that the application of GM crops can improve the agricultural productivity and sustainability, whereas equitability cannot be stimulated and might even exacerbate the gap between socioeconomic classes. Before introducing GM crops to Ethiopian agriculture, regulatory issues should be addressed, public research should be fostered, and more ex ante values and socioeconomic studies should be included. [ABSTRACT FROM AUTHOR]