No abstract

Accurate predictions of crop yield are critical for developing effective agricultural and food policies at the regional and global scales. We evaluated a machine-learning method, Random Forests (RF), for its ability to predict crop yield responses to climate and biophysical variables at global and regional scales in wheat, maize, and potato in comparison with multiple linear regressions (MLR) serving as a benchmark. We used crop yield data from various sources and regions for model training and testing: 1) gridded global wheat grain yield, 2) maize grain yield from US counties over thirty years, and 3) potato tuber and maize silage yield from the northeastern seaboard region. RF was found highly capable of predicting crop yields and outperformed MLR benchmarks in all performance statistics that were compared. For example, the root mean square errors (RMSE) ranged between 6 and 14% of the average observed yield with RF models in all test cases whereas these values ranged from 14% to 49% for MLR models. Our results show that RF is an effective and versatile machine-learning method for crop yield predictions at regional and global scales for its high accuracy and precision, ease of use, and utility in data analysis. RF may result in a loss of accuracy when predicting the extreme ends or responses beyond the boundaries of the training data.

No abstract

Groundnut (Arachis hypogaea L.) is an important cash crop for tropical farmers. It is an annual legume and its seeds contain high amounts of edible oil (43-55%) and protein (25-28%). Even though it is fairly drought-tolerant, production fluctuates considerably as a result of rainfall variability. To develop a water stress response function in groundnut, research has been done to improve the performance under varying degrees of stress at various physiological stages of crop growth. This review summarizes recent information on the drought resistance characteristics of groundnut with a view to developing appropriate genetic enhancement strategies for water-limited environments. It is suggested that there are considerable gains to be made in increasing yield and stabilizing the yield in environments characterized by terminal drought stress and further exploiting drought escape strategy, by shortening crop duration. Many traits conferring dehydration avoidance and dehydration tolerance are available, but integrated traits, expressed at a high level of organization, are likely to be more useful in crop improvement programs. Possible genetic improvement strategies are outlined, ranging from empirical selection for yield in drought environments to a physiological-genetic approach. It is also suggested that in view of recent advances in understanding drought resistance mechanisms, the latter strategy is becoming more feasible. It is concluded that the use of this recently derived knowledge in a systematic manner could lead to significant gains in yield and yield stability in the world's groundnut production. Research is needed to develop transferable technologies to help farmers in arid and semi-arid regions. Increasing soil moisture storage by soil profile management and nutrient management for quick recovery from drought are some of the areas which need to be explored.

The effects of CO 2 enrichment on the growth and physiology of maize were investigated at the molecular, biochemical, leaf, and canopy levels. Maize plants were grown in sunlit soil-plant-atmosphere research (SPAR) chambers at ambient (370 lmol mol À1 ) or elevated (750 lmol mol À1 ) atmospheric carbon dioxide concentration (C a ) under wellwatered and fertilized conditions. Canopy gas exchange rates and leaf temperatures were monitored continuously during the growing season. CO 2 enrichment did not enhance the growth or canopy photosynthesis of maize plants. However, canopy evapotranspiration rates decreased by 22% and daytime leaf temperatures were increased about 1 1C in response to CO 2 enrichment. Leaf carboxylation efficiency and leaf nitrogen concentration also decreased at elevated C a . Transcription profiling using maize cDNA microarrays revealed that approximately 5% of tested genes responded to CO 2 enrichment. Of the altered transcripts, several were known to encode proteins involved in stomatal development or photosynthesis. For the majority of the altered transcripts, however, it was difficult to link their functions with specific physiological factors partly because many of these genes encoded unknown proteins. We conclude that maize did not exhibit enhanced growth or photosynthesis in response to CO 2 enrichment but a number of molecular and physiological processes including those involved in stomatal relations were affected by growth in elevated C a .