This paper assesses the influence of heat and drought stress on the economic performance of the European dairy sector. Climatic data from the Gridded Agro-Meteorological data in Europe were combined with dairy enterprise data from the Farm Accountancy Data Network, resulting in a data set of 4412 farms in 22 European Union (EU) countries over the period 2007–2013. Since the performance of dairy farms is influenced by the context in which they operate, farms were grouped into areas representing similar climatic conditions through the use of a latent class analysis. Technical efficiency (TE) and economic downside risk were used as performance indicators against which the effect of climatic stress factors was evaluated. TE was estimated using a ‘true-fixed’ effect stochastic frontier model. Economic downside risk was based on gross margin deviations. Regression analysis suggests a significant negative effect of drought and heat stress on both TE and the downside gross margin difference in most climatic classes, with few exceptions. Results imply that both drought and heat stress-related issues need to be considered when designing adaptation strategies to address threats to the economic performance of the EU dairy sector.

This paper describes the relationships between large-scale modes of climate variability and its related weather types with the fluctuations in the yield of maize crops in Veneto, Italy. The teleconnections analysed in this work are the winter North Atlantic Oscillation (NAO) and the summer North Atlantic Oscillation (SNAO); the West African monsoon (WAM) and the Intertropical Front (ITF). Despite that these indices are not rigorously linked to one another, they result in being considerably related to atmospheric circulation regimes and associated weather types. They have an impact on temperature and precipitation patterns in Italy and on yields of maize crops in Veneto, a region located in northeast Italy. Yields are strongly affected by large-scale temperate and tropical variability directly through three main circulation regimes. Troughing weather regimes that produced below average temperatures depress yields over the entire Veneto region, as does the zonal regime that affects rainfall. Results confirm the relevance of large-scale modes and associated weather regimes and types on maize crop yields fluctuations in Veneto.

Understanding and representing the transformation of agricultural production systems has attracted increasing interest due to its importance for identifying drivers of changes and coping mechanisms in response to global challenges. These challenges are all the most pressing in North African countries exposed to a dramatic reduction in rainfall and increasing temperatures that affect sustainability in more than half of this semi-arid territory. This paper describes an improved way to understand such transformations through a cross-cutting analysis of crop–livestock system indicators over a period of 10 years in one community in Southern Tunisia. Our methodology is divided into four steps: (i) systems identification, (ii) indicator-based assessment of system crop–livestock sustainability, (iii) hierarchical clustering to identify sustainable intensification (SI)-based farm types and, finally, (iv) analysis of trajectories of these farm types. Results showed that the sustainability of the systems studied increasingly depends on diversification rather than intensification, which dominated in the 2000s. However, diversification has not necessarily improved socio-economic viability. Over the 10-year period, results revealed a dramatic increase of almost 50% in the population of small-scale farms whose viability depends on a range of on- and off-farm activities to meet the short-term needs that correspond to a buffer strategy. Additionally, the dominant SI processes were shown to be mostly based on diversification to livestock activities with both milking and fattening. Our holistic and timeline approach to system transformation makes it possible to account for sustainability between (systems) generations, which will be highly needed in future discussions about sustainability.

Soil carbon dioxide (CO2) emissions from the field of corn (Zea mays L.) play an important role in global warming. This study investigated temporal variability of soil CO2 fluxes (Rs) with soil temperature (Ts) and moisture (θ) and built DAYCENT models for predicting future impacts of climate changes on Rs using the measured high-frequency data. Rs trend was tested by Mann–Kendall and Sen Estimator. Predicted Rss under different climate scenarios were compared using Parallel-line Analysis. The findings indicated that daily Rs exponentially increased with Ts constrained by θ. During the θ of 27–31%, there was a strong exponential relationship between Rs and Ts, but the relationship was weaker for the θ of 38–41% and 22–26%. Soil environmental index (SEI, Ts × θ) significantly impacted Rs with linear regression Rs0.5 = 0.4599 + 0.002059 × SEI in 2008, 2009 and 2011. At the diurnal scale, there were different trends in Rss and relationships among Rs and Ts and θ in different years. Predicted yearly Rss, root Rss and corn yield in 2014–2049 increased with an increase in temperature scenarios, but the Rss significantly increased as temperature rose by 1°C or higher. Predicted yearly Rss, root Rss and yield reduced with precipitation scenario increase, and the root Rss and yield significantly diminished as precipitation increased by 15 and 30%. Predicted yearly Rs from cornfields had a significantly increasing trend. Future research is needed to explore methods for mitigating cornfield Rs and evaluating sensitivities of different cropland Rss to temperature changes.

Coffee forests are the most valuable land-use systems that provide multiple benefits such as biodiversity conservation, carbon sequestration and source of income. This study aimed to estimate the carbon stock of coffee agroforestry systems and the contribution of coffee plants (Coffea arabica L.) to carbon sequestration in the entire coffee agroforestry systems in southwestern Ethiopia. The carbon stock in trees was estimated by field-based measurements and allometric equations, whereas the carbon stocks in litter and soil were determined using field sampling and laboratory analysis. The carbon stocks of the coffee agroforestry systems in the study site ranged from 254.9 t C/ha in the Syzygium-shaded coffee forest to 321.8 t C/ha in the Albizia-shaded coffee forest. The overall mean carbon sequestration in the present coffee agroforestry systems was 287.1 t C/ha. The net carbon sequestered by coffee plants in the agroforestry systems ranged from 18.8 t C/ha in the Syzygium-shaded coffee stratum to 48.5 t C/ha in the Albizia-shaded coffee stratum. This demonstrates that Albizia is the most compatible shade tree for coffee plants. On average, coffee plants contributed 37.5 t C/ha, accounting for approximately 12.8% of the total carbon sequestered in the coffee agroforestry systems. Hence, we recommend coffee forests for all-in-one benefits such as climate change mitigation, sustainable landscape management and income generation.

Integrated pest management (IPM) seeks to minimize the environmental impact of pesticide application, and reduce risks to human and animal health. IPM is based on two important aspects – prevention and monitoring of diseases and insect pests – which today are being assisted by sensing and artificial-intelligence (AI) techniques. In this paper, we surveyed the detection and diagnosis, with AI, of diseases and insect pests, in cotton, which have been published between 2014 and 2021. This research is a systematic literature review. The results show that AI techniques were employed – mainly – in the context of (i) classification, (ii) image segmentation and (iii) feature extraction. The most used algorithms, in classification, were support vector machines, fuzzy inference, back-propagation neural-networks and recently, convolutional neural networks; in image segmentation, k-means was the most used; and, in feature extraction, histogram of oriented gradients, partial least-square regression, discrete wavelet transform and enhanced particle-swarm optimization were equally used. The most used sensing techniques were cameras, and field sensors such as temperature and humidity sensors. The most investigated insect pest was the whitefly, and the disease was root rot. Finally, this paper presents future works related to the use of AI and sensing techniques, to manage diseases and insect pests, in cotton; for instance, implement diagnostic, predictive and prescriptive models to know when and where the diseases and insect pests will attack and make strategies to control them.

Bambara groundnut (Vigna subterranea L. Verdc; BGN) is an important legume grown mainly by small-scale subsistence farmers in sub-Saharan Africa, in parts of Thailand and Indonesia. It has a high concentration of seed carbohydrate (55–70%), protein (17–25%), fat (1.4–12%) and dietary fibre (5.2–6.4%). A range of biotic and abiotic stresses together with socio-economic constraints affect its productivity, yield and quality. The changing climate and a growing world population are putting pressure on food production, as world food supply is heavily reliant on few crops. As such, there is a need to broaden crop usage and increase yield of minor crops such as BGN. Improvements in production can potentially be achieved by a combination of advanced phenotyping, genotyping, environmental characterization and overall management approaches. Breeding for advanced lines is complicated by overreliance on landraces. This review aims to provide the current status of BGN production, production constraints and approaches to overcome these, as well as its grain composition and nutritional value. It further discusses and elaborates on potentially available opportunities for overall improvement, so that BGN, like all neglected crops, can play a valuable role in world food security. Efforts should be intensified to improve the overall utilization of BGN and its constituents to make it an economically viable crop.

Genetic gains (ΔG) are determined by the breeders' equation ΔG = [(ck σ2G)/(y σP)], where c, k and y are the parental control, a function of the selection intensity and number of years to complete one selection cycle, respectively, while σ2G and are σP the genetic variance and the square root of the phenotypic variance. Plant breeding programs should deliver above 1% of annual genetic gains after testing and selection. The aim of this research was to estimate genetic gains in potato breeding after testing of cultivars released in western Europe in the last 200 years under high yield potential, and stress-prone environments affected by a pest (late blight) or daylength. The annual genetic gains for tuber yield and flesh's starch content for potato breeding in Europe were about 0.3 and −0.1%, respectively, thus telling that the realized genetic gains of foreign cultivars for both traits are small or negative, respectively, in the Nordic testing sites. The national annual productivity gains in potato grown in Sweden were on average 0.7% in the last 60 years while the genetic gains for tuber yield considering only the table cultivars released after the 2nd World War were about 0.36%, thus showing that breeding contributed just above ½ of it. Furthermore, genetic gains for breeding low reducing sugars in the tuber flesh, and high host plant resistance to late blight were small (<0.2% per year). These results highlight that genetic gains are small when testing bred germplasm outside their target population of environments.

Banana is one of the main fruit crops in the world as it is a rich source of nutrients and has recently become popular for its fibre, particularly as a raw material in many industries. Mathematical models are crucial for strategic and forecasting applications; however, models related to the banana crop are less common, and reviews on previous modelling efforts are scarce, emphasizing the need for evidence-based studies on this topic. Therefore, we reviewed 75 full-text articles published between 1985 and 2021 for information on mathematical models related to banana growth and, fruit and fibre yield. We analysed results in order to provide a descriptive synthesis of selected studies. According to the co-occurrence analysis, most studies were conducted on the mathematical modelling of banana fruit production. Modellers often used multiple linear regression models to estimate banana plant growth and fruit yield. Existing models incorporate a range of predictor variables, growth conditions, varieties, modelling approaches and evaluation methods, which limits comparative evaluation and selection of the best model. However, the banana process-based simulation model ‘SIMBA’ and artificial neural network have proven their robust applicability to estimate banana plant growth. This review shows that there is insufficient information on mathematical models related to banana fibre yield. This review could aid stakeholders in identifying the strengths and limitations of existing models, as well as providing insight on how to build novel and reliable banana crop-related mathematical models.

The spatio-temporal variation of leaf chlorophyll content is an important crop phenotypic trait that is of great significance for evaluating crop productivity. This study used a soil-plant analysis development (SPAD) chlorophyll meter for non-destructive monitoring of leaf chlorophyll dynamics to characterize the patterns of spatio-temporal variation in the nutritional status of maize (Zea mays L.) leaves under three nitrogen treatments in two cultivars. The results showed that nitrogen levels could affect the maximum leaf SPAD reading (SPADmax) and the duration of high SPAD reading. A rational model was used to measure the changes in SPAD readings over time in single leaves. This model was suitable for predicting the dynamics of the nutrient status for each leaf position under different nitrogen treatments, and model parameter values were position dependent. SPADmax at each leaf decreased with the reduction of nitrogen supply. Leaves at different positions in both cultivars responded differently to higher nitrogen rates. Lower leaves (8th–10th positions) were more sensitive than the other leaves in response to nitrogen. Monitoring the SPAD reading dynamic of lower leaves could accurately characterize and assess the nitrogen supply in plants. The lower leaves in nitrogen-deficient plants had a shorter duration of high SPAD readings compared to nitrogen-sufficient plants; this physiological mechanism should be studied further. In summary, the spatio-temporal variation of plant nitrogen status in maize was analysed to determine critical leaf positions for potentially assisting in the identification of appropriate agronomic management practices, such as the adjustment of nitrogen rates in late fertilization.

The purpose of this study was to evaluate the quality of Marandu grass (Brachiaria brizantha) haylage according to different dry matter (DM) contents in storage. The design adopted was completely randomized with four treatments and five replications. The treatments were DM contents of the plant at the moment of storage (in natura, 30–40, 40–50 and 50–60% DM). The analyses to assess the quality of the haylage were performed after 90 days of storage. The chemical composition, microbiological population, gas quantification, pH, N-NH3, volatile fatty acids, soluble carbohydrates (CHO) and the aerobic stability were evaluated. The means were compared through the Tukey's test and linear regression. The treatment with 50–60% DM presented the highest DM and CHO contents which were 563.8 and 42.0 g/kg, respectively. There was a higher presence of oxygen in the haylage of in natura material, which was 4.8%. There was no difference between treatments for the population of lactic acid bacteria; however, the treatment with 50–60% DM had the highest concentration of enterobacteria. The haylage with 30–40% DM and 50–60% DM presented high concentrations of acetic acid. There was no break in aerobic stability for any treatment within 120 h after opening the bales. There was a smaller amount of N-NH3 in treatments with 40–50% DM and 50–60% DM. The Marandu grass with a DM content of 50–60% for haylage making demonstrated better quality characterization of conserved forage.

Maize is the most important staple food crop in southern Africa with human consumption averaging 91 kg/capita/year. Most smallholder farmers and weaning children depend on maize for much of the daily food requirements and it is the largest contributor of dietary proteins. Despite the development of quality protein maize (QPM) with high tryptophan and lysine content, stunting and kwashiorkor remain high in southern Africa partly due to low adoption of QPM varieties. The objective of this study was to compare the agronomic performance and farmer preferences of new generation of QPM with non-QPM varieties under conservation agriculture on-farm conditions. Eight QPM and four non-QPM varieties were tested on on-farm trials in Zimbabwe during the 2014/15 and 2015/16 cropping seasons at five different locations. Significant differences were detected among the genotypes for the measured traits in the two seasons. Similarly, genotype plus genotype × environment interactions were significant for both seasons for grain yield. Three QPM varieties, SC527, SC535 and SC643, recorded the highest and stable yield. Four QPM varieties, SC643, SC535, SC527 and MQ623, and a non-QPM variety, PAN413, were ranked high among farmers for overall ear characteristics as their most preferred varieties. The high-yielding and stable QPM varieties are likely to be adopted by farmers in southern Africa.

The present study aimed to evaluate the effects of chitosan instead of microbial inoculants on fermentation profile, losses, chemical composition, in vitro degradation, and aerobic stability of sugarcane silage (SS). Forty experimental silos (PVC tubes with 28 cm i.d., 25 cm height) were used in a randomized block design to evaluate the following treatments: (I) Control (CON): SS with no additive; (II) LB: SS ensiled with 5.0 × 105 colony forming units (CFU) of Lactobacillus buchneri (NCIM 40788)/g as-fed; (III) LPPA: SS ensiled with 1.6 × 105 CFU of L. plantarum and 1.6 × 105 CFU of Pediococcus acidilactici/g as-fed; and (IV) Chitosan (CHI): SS ensiled with 6 g/kg dry matter (DM) of chitosan. Microbial inoculation of SS reduced (P ≤ 0.05) silage pH relative to CON and CHI treatment. The LPPA decreased ammonia-nitrogen and LB decreased (P ≤ 0.05) ethanol content and increased acetic acid content relative to other treatments. The LPPA-silos had higher (P ≤ 0.05) gas losses and lower (P ≤ 0.05) DM recovery than other treatment silos. Consequently, LPPA reduced (P ≤ 0.05) DM and non-fibre carbohydrates and increased (P ≤ 0.05) neutral detergent fibre (NDF) silage content compared to other treatments. Treatments did not affect (P ≥ 0.212) DM and NDF in vitro degradation and silage pH after aerobic exposure. However, LB reduced silage temperature after aerobic exposure. Thus, LB reduces alcoholic fermentation and improves SS aerobic stability. Inoculation of LPPA reduces DM recovery and negatively affects SS chemical composition. Although CHI positively affects SS conservation relative to CON, it shows higher gas losses and decreased SS temperature after aerobic exposure compared to LB.

Determination of sample size (the number of replications) is a key step in the design of an observational study or randomized experiment. Statistical procedures for this purpose are readily available. Their treatment in textbooks is often somewhat marginal, however, and frequently the focus is on just one particular method of inference (significance test, confidence interval). Here, we provide a unified review of approaches and explain their close interrelationships, emphasizing that all approaches rely on the standard error of the quantity of interest, most often a pairwise difference of two means. The focus is on methods that are easy to compute, even without a computer. Our main recommendation based on standard errors is summarized as what we call the 1-2-3 rule for a difference of two treatment means.

Intercropping maize (Zea mays L.) with cover crops (Crotalaria spectabilis and Urochloa ruziziensis) is a sustainable cultivation strategy that can generate ecological benefits combined with grain yield (GY). However, cover crops may require nitrogen (N) fertilization management to be adjusted to obtain a high GY in intercropping systems. This study was carried out over 2 years in southeastern Brazil using randomized complete block design in a split-plot scheme. The plots were composed of three cropping systems: sole maize, maize + U. ruziziensis and maize + C. spectabilis. The subplots consisted of four N levels: 0, 70, 140 and 210 kg/ha. The GY of the maize + U. ruziziensis may be reduced by 13% compared to the sole maize. The GY of the sole maize increased up to 11.3 Mg/ha for 95 kg/ha of N in the first year and 6.7 Mg/ha for 169 kg/ha of N in the second year. The GY of the maize + U. ruziziensis intercropping system showed linear increments of 120 kg/ha for every 10 kg/ha of N applied. In the maize + C. spectabilis intercropping, GY increased up to 9.8 Mg/ha for 201 kg/ha of N in the first year, without any variation during the second year. The land equivalent ratio (LER) of intercropping was increased by more than 35% compared to that of sole maize, and N fertilization increased the LER of the sole maize and maize + U. ruziziensis intercropping. Maize intercropping had higher LER values with greater demand for nitrogen to obtain similar yields compared to sole maize cropping.

The objective of this study was to describe and explain the effect of adding corn meal (CM) on losses, fermentation characteristics and nutritional value of silages from two elephant grass [Cenchrus purpureus (Schumach.) Morrone] genotypes (Taiwan A-146 2.37 and IRI-381) mixed with butterfly pea (Clitoria ternatea L.) legume. The forage was harvested at 75 days of regrowth from elephant grass plots intercropped with butterfly pea legume and ensiled with or without CM at 5% of dry matter (DM) content. Greater gas losses (12 g/kg) and pH (4.2) were observed in the Taiwan A-146 2.37 + butterfly pea silages. The greatest crude protein content was observed in the ‘Taiwan A-146 2.37’ + butterfly pea silage added with CM (116 g/kg). Silages with additive and those containing IRI-381 had a greater acid detergent fibre content (367 and 366 g/kg, respectively). CM increased the silage DM (221 g/kg), remaining water-soluble carbohydrates contents (26 g/kg) and in vitro digestibility of DM. The aerobic stability was maintained until 45 h after opening the silos. All silages presented a good fermentative profile and were not affected by the relatively large proportion of butterfly pea (>34%) in the ensiled mass as indicated by the reduced contents of butyric acid and ammonia nitrogen. CM reduces total losses, increases DM recovery and improves the nutritional value of silages from mixed elephant grass–butterfly pea legume.

The wild asparagus Asparagus acutifolius L. is common in the Mediterranean Basin. Wild asparagus spears are an important food source within their native range, and can be used as a sustainable nutrition source. In addition, interest has risen in wild relative species of Asparagus as a source of genetic improvement in Asparagus officinalis L. In this study, the quality traits (spear colour, total soluble solid content, dry matter content and chlorophyll and sugar fractions) and health-related compounds (total phenolics and antioxidant capacity) of fresh spears of wild and cultivated asparagus grown in Turkey were compared using the same three harvest periods for two consecutive years. The results of this study indicated that spears of wild asparagus contained a higher level of greenness (–a*), hue angle, total soluble solid, dry matter, chlorophyll, sugars, total phenolic content and antioxidant activity, compared to cultivated asparagus. Although there was no significant difference in the total soluble solid, glucose, sucrose and antioxidant activity in the contents of the spears of both species throughout the season, the colour, dry matter, chlorophyll, fructose, total sugar and total phenolic content were subject to seasonal variations. Colour, chlorophyll and total phenolic content showed some minor fluctuations over the course of the season, but the patterns of fructose and total sugar differed, which tended to increase throughout the harvest season. The present work suggests greater quality traits and biochemical compounds of the spears of A. acutifolius compared with those of commonly cultivated species.

The use of ‘cut-and-carry’ (the mechanical harvesting and feeding of fresh grass) has increased in some temperate regions in recent years and evidence suggests that sward management practices in this system differ to conventional grazing. In order to investigate this further, a 2 × 3 × 2 factorial experiment was used to examine the effect of low (1489 kg dry matter (DM)/ha; LHM) and high (2142 kg DM/ha; HHM) pre-cutting herbage mass; three ryegrass cultivars, diploid perennial ryegrass (Lolium perenne; DIP), tetraploid perennial ryegrass (TET) and a hybrid ryegrass (Lolium multiflorum × L. perenne; HY); and the inclusion of red clover (Trifolium pratense) on sward herbage production, nutritive value and ryegrass morphology. Plots were harvested according to herbage mass from March to November in 2018 and 2019. Annual DM production was 1489 kg DM/ha higher in HHM than in LHM swards. Pre-cutting herbage mass had no effect on organic matter digestibility (OMD) in early season for DIP and TET swards or in late season for all cultivars. There was an interaction between ryegrass cultivar and clover inclusion in annual yield whereby red clover increased DM production in all cultivars however, its effect was largest in HY swards. Red clover inclusion increased DM production but reduced OMD in early and mid-seasons. Overall, TET swards were lowest in neutral detergent fibre and highest in OMD compared to HY and DIP. Pre-cutting herbage mass, ryegrass cultivar and red clover inclusion require careful consideration when establishing and managing pastures in cut-and-carry systems.